From c65b4eda4c1f0ab5f2298455c4d80920695354b7 Mon Sep 17 00:00:00 2001 From: Anson Biggs Date: Mon, 3 May 2021 21:25:47 -0700 Subject: [PATCH 1/4] Mostly finished with Eclipse Determination. --- .../air-propulsion-simulation.Rmd | 2 +- .../air-propulsion-simulation.html | 2 + .../figure-html5/unnamed-chunk-6-J1.png | Bin 22805 -> 23076 bytes .../figure-html5/unnamed-chunk-7-J1.png | Bin 49257 -> 48394 bytes .../citations.bib | 29 ++++ .../iss-eclipse-determination.Rmd | 57 ++++-- .../iss-eclipse-determination.html | 150 ++++++++++------ .../figure-html5/unnamed-chunk-6-J1.png | Bin 21978 -> 22194 bytes .../figure-html5/unnamed-chunk-7-J1.png | Bin 0 -> 22194 bytes docs/index.html | 42 ++--- docs/index.xml | 24 +-- .../figure-html5/unnamed-chunk-6-J1.png | Bin 22805 -> 23076 bytes .../figure-html5/unnamed-chunk-7-J1.png | Bin 49257 -> 48394 bytes .../index.html | 10 +- .../citations.bib | 29 ++++ .../index.html | 164 +++++++++++------- .../figure-html5/unnamed-chunk-6-J1.png | Bin 21978 -> 22194 bytes .../figure-html5/unnamed-chunk-7-J1.png | Bin 0 -> 22194 bytes docs/posts/posts.json | 52 +++--- docs/search.json | 8 +- docs/sitemap.xml | 14 +- 21 files changed, 389 insertions(+), 194 deletions(-) create mode 100644 _posts/2021-04-14-iss-eclipse-determination/citations.bib create mode 100644 _posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination_files/figure-html5/unnamed-chunk-7-J1.png create mode 100644 docs/posts/2021-04-14-iss-eclipse-determination/citations.bib create mode 100644 docs/posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination_files/figure-html5/unnamed-chunk-7-J1.png diff --git a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd index 7a71b12..6282d4b 100644 --- a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd +++ b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd @@ -24,7 +24,7 @@ For Capstone my team was tasked with designing a system capable of moving mining ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE, results = 'hide') library(JuliaCall) -#julia_setup(JULIA_HOME = "/opt/julia-1.6.0/bin/") +julia_setup(JULIA_HOME = "/opt/julia-1.6.0/bin/") ``` ```{julia, code_folding=TRUE} diff --git a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html index 21f980c..276f3bb 100644 --- a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html +++ b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html @@ -110,6 +110,8 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */ + + @@ -1456,7 +1458,7 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */ @@ -1473,13 +1475,13 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */
Astrodynamics
-

Determining how much sunlight a body is receiving.

+

Determining how much sunlight a body orbiting a planet is receiving.

Anson Biggs https://ansonbiggs.com -
04-01-2021 +
05-01-2021
@@ -1488,9 +1490,11 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */
Geometry of an Eclipse
+

The above image is a simple representation of what an eclipse is. You’ll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn’t much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.

Body Radius’s and Position Vectors
+

Here is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius’s that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS’s orbit. Rsun and Rbody are the radius’s of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft.

The Code

@@ -1505,75 +1509,109 @@ Show code theme(:ggplot2)
+

In order to get the orbit for the ISS I used a Two-Line Element which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below and now we have access to the information to start making our ISS orbit.

ISS = tle"""
 ISS (ZARYA)
 1 25544U 98067A   21103.84943184  .00000176  00000-0  11381-4 0  9990
 2 25544  51.6434 300.9481 0002858 223.8443 263.8789 15.48881793278621
 """
+
1-element Vector{TLE}:
+ TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)
+
+

Now that we have the TLE we can pass that into SatelliteToolbox’s orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.

+
+
ISS[1].n
-
orbit = init_orbit_propagator(Val(:twobody), ISS[1]);
-time = 0:0.1:((24 / ISS[1].n) .* 60 * 60);
-o, r, v = propagate!(orbit, time);
+
orbit = init_orbit_propagator(Val(:twobody), ISS[1]);
+time = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.
+o, r, v = propagate!(orbit, time);
+

Now we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math.

+

add more discussion about the math

-
function sunlight(Rbody, r_sun_body, r_body_sc)
-    Rsun = 695_700u"km"
-    
-    hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)
-    
-    θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))
-
-    θu = atan(Rbody / hu)
-    du = hu * sin(θu) / sin(θe + θu)
-
-    θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))
-    dp = Rbody * sin(θp) / cos(θe - θp)
-
-    S = 1
-    if (θe < π / 2) && (norm(r_body_sc) < du)
-        S = 0
-    end
-    if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))
-        S = (norm(r_body_sc .|> u"km") - du) / (dp - du) |> ustrip
-    end
-
-    return S
-end
+
function sunlight(Rbody, r_sun_body, r_body_sc)
+    Rsun = 695_700u"km"
+    
+    hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)
+    
+    θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))
+
+    θu = atan(Rbody / hu)
+    du = hu * sin(θu) / sin(θe + θu)
+
+    θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))
+    dp = Rbody * sin(θp) / cos(θe - θp)
+
+    S = 1
+    if (θe < π / 2) && (norm(r_body_sc) < du)
+        S = 0
+    end
+    if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))
+        S = (norm(r_body_sc .|> u"km") - du) / (dp - du) |> ustrip
+    end
+
+    return S
+end
+

Then we can pass all the values we’ve gathered into the function we just made.

-
S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u"m")
+
S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u"m");

Plotting the Results

+

The sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant.

Show code -
light_range = range(colorant"black", stop = colorant"yellow", length = 101);
-light_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];
-
-plot(
-    LinRange(0, 24, length(S)),
-    S .* 100,
-    linewidth = 5,
-    legend = false,
-    color = light_colors,
-);
-
-xlabel!("Time (hr)");
-ylabel!("Sunlight (%)");
-title!("ISS Sunlight Over a Day")
+
# Get fancy with the line color. 
+light_range = range(colorant"black", stop = colorant"orange", length = 101);
+light_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];
+
+plot(
+    LinRange(0, 24, length(S)),
+    S .* 100,
+    linewidth = 5,
+    legend = false,
+    color = light_colors,
+);
+
+xlabel!("Time (hr)");
+ylabel!("Sunlight (%)");
+title!("ISS Sunlight Over a Day")
-
-Rocket Motor Data: [@thrustcurve] +
+ISS Sunlight

-Figure 1: Rocket Motor Data: [@thrustcurve] +Figure 1: ISS Sunlight

-
+

Looking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region.

+Time in Sun: +
+
sun = length(S[S.==1])/length(S) * 100
+
62.03323593209401
+
+Time in Darkness: +
+
umbra = length(S[S.==0])/length(S) * 100
+
37.64408511553699
+
+Time in Penumbra: +
+
penumbra = 100 - umbra - sun
+
0.322678952369003
+
+

The ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes.

+
+
+
+“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/. +
+
@@ -1586,6 +1624,8 @@ Figure 1: Rocket Motor Data: [@t
+

References

+

Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

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Anson's Projects

+ + +
+
May 1, 2021
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+
Anson Biggs
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ISS Eclipse Determination

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Julia
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Astrodynamics
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Determining how much sunlight a body orbiting a planet is receiving.

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Air Propulsion Simulation

@@ -2233,26 +2253,6 @@ function init_posts_list() {

Simulating the performance of an air propulsion system as an alternative to solid rocket motors.

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April 1, 2021
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Anson Biggs
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ISS Eclipse Determination

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Julia
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Astrodynamics
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Determining how much sunlight a body is receiving.

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diff --git a/docs/index.xml b/docs/index.xml index 0bfe54a..28431b0 100644 --- a/docs/index.xml +++ b/docs/index.xml @@ -7,7 +7,18 @@ Anson's Projects Distill - Thu, 01 Apr 2021 00:00:00 +0000 + Sat, 01 May 2021 00:00:00 +0000 + + ISS Eclipse Determination + Anson Biggs + https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination + Determining how much sunlight a body orbiting a planet is receiving. + Julia + Astrodynamics + https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination + Sat, 01 May 2021 00:00:00 +0000 + + Air Propulsion Simulation Anson Biggs @@ -17,16 +28,7 @@ Capstone https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation Thu, 01 Apr 2021 00:00:00 +0000 - - - ISS Eclipse Determination - Anson Biggs - https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination - Determining how much sunlight a body is receiving. - Julia - Astrodynamics - 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-

Determining how much sunlight a body is receiving.

+

Determining how much sunlight a body orbiting a planet is receiving.

Anson Biggs https://ansonbiggs.com -
04-01-2021 +
05-01-2021
@@ -2124,9 +2132,11 @@ document.addEventListener('DOMContentLoaded', function() {
Geometry of an Eclipse
+

The above image is a simple representation of what an eclipse is. You’ll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn’t much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.

Body Radius’s and Position Vectors
+

Here is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius’s that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS’s orbit. Rsun and Rbody are the radius’s of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft.

The Code

@@ -2141,75 +2151,109 @@ Show code theme(:ggplot2)
+

In order to get the orbit for the ISS I used a Two-Line Element which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below and now we have access to the information to start making our ISS orbit.

ISS = tle"""
 ISS (ZARYA)
 1 25544U 98067A   21103.84943184  .00000176  00000-0  11381-4 0  9990
 2 25544  51.6434 300.9481 0002858 223.8443 263.8789 15.48881793278621
 """
+
1-element Vector{TLE}:
+ TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)
+
+

Now that we have the TLE we can pass that into SatelliteToolbox’s orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.

+
+
ISS[1].n
-
orbit = init_orbit_propagator(Val(:twobody), ISS[1]);
-time = 0:0.1:((24 / ISS[1].n) .* 60 * 60);
-o, r, v = propagate!(orbit, time);
+
orbit = init_orbit_propagator(Val(:twobody), ISS[1]);
+time = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.
+o, r, v = propagate!(orbit, time);
+

Now we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math.

+

add more discussion about the math

-
function sunlight(Rbody, r_sun_body, r_body_sc)
-    Rsun = 695_700u"km"
-    
-    hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)
-    
-    θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))
-
-    θu = atan(Rbody / hu)
-    du = hu * sin(θu) / sin(θe + θu)
-
-    θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))
-    dp = Rbody * sin(θp) / cos(θe - θp)
-
-    S = 1
-    if (θe < π / 2) && (norm(r_body_sc) < du)
-        S = 0
-    end
-    if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))
-        S = (norm(r_body_sc .|> u"km") - du) / (dp - du) |> ustrip
-    end
-
-    return S
-end
+
function sunlight(Rbody, r_sun_body, r_body_sc)
+    Rsun = 695_700u"km"
+    
+    hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)
+    
+    θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))
+
+    θu = atan(Rbody / hu)
+    du = hu * sin(θu) / sin(θe + θu)
+
+    θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))
+    dp = Rbody * sin(θp) / cos(θe - θp)
+
+    S = 1
+    if (θe < π / 2) && (norm(r_body_sc) < du)
+        S = 0
+    end
+    if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))
+        S = (norm(r_body_sc .|> u"km") - du) / (dp - du) |> ustrip
+    end
+
+    return S
+end
+

Then we can pass all the values we’ve gathered into the function we just made.

-
S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u"m")
+
S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u"m");

Plotting the Results

+

The sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant.

Show code -
light_range = range(colorant"black", stop = colorant"yellow", length = 101);
-light_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];
-
-plot(
-    LinRange(0, 24, length(S)),
-    S .* 100,
-    linewidth = 5,
-    legend = false,
-    color = light_colors,
-);
-
-xlabel!("Time (hr)");
-ylabel!("Sunlight (%)");
-title!("ISS Sunlight Over a Day")
+
# Get fancy with the line color. 
+light_range = range(colorant"black", stop = colorant"orange", length = 101);
+light_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];
+
+plot(
+    LinRange(0, 24, length(S)),
+    S .* 100,
+    linewidth = 5,
+    legend = false,
+    color = light_colors,
+);
+
+xlabel!("Time (hr)");
+ylabel!("Sunlight (%)");
+title!("ISS Sunlight Over a Day")
-
-Rocket Motor Data: [@thrustcurve] +
+ISS Sunlight

-Figure 1: Rocket Motor Data: [@thrustcurve] +Figure 1: ISS Sunlight

-
+

Looking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region.

+Time in Sun: +
+
sun = length(S[S.==1])/length(S) * 100
+
62.03323593209401
+
+Time in Darkness: +
+
umbra = length(S[S.==0])/length(S) * 100
+
37.64408511553699
+
+Time in Penumbra: +
+
penumbra = 100 - umbra - sun
+
0.322678952369003
+
+

The ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes.

+
+
+
+“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/. +
+
+

References

+

Corrections

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://gitlab.com/lander-team/air-prop-simulation, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

- 
Biggs (2021, April 1). Anson's Projects: ISS Eclipse Determination. Retrieved from https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination/
+ 
Biggs (2021, May 1). Anson's Projects: ISS Eclipse Determination. Retrieved from https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination/

BibTeX citation

@misc{biggs2021iss,
   author = {Biggs, Anson},
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diff --git a/docs/posts/posts.json b/docs/posts/posts.json
index 37302f4..5b0d490 100644
--- a/docs/posts/posts.json
+++ b/docs/posts/posts.json
@@ -1,4 +1,26 @@
 [
+  {
+    "path": "posts/2021-04-14-iss-eclipse-determination/",
+    "title": "ISS Eclipse Determination",
+    "description": "Determining how much sunlight a body orbiting a planet is receiving.",
+    "author": [
+      {
+        "name": "Anson Biggs",
+        "url": "https://ansonbiggs.com"
+      }
+    ],
+    "date": "2021-05-01",
+    "categories": [
+      "Julia",
+      "Astrodynamics"
+    ],
+    "contents": "\nDetermining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space with no solar radiation to power the solar panels and keep the spacecraft from freezing.\nWhat is an Eclipse\nGeometry of an EclipseThe above image is a simple representation of what an eclipse is. You’ll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn’t much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.\nBody Radius’s and Position VectorsHere is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius’s that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS’s orbit. Rsun and Rbody are the radius’s of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft.\nThe Code\n\n\nShow code\nusing Unitful\nusing LinearAlgebra\nusing SatelliteToolbox\nusing Plots\nusing Colors\ntheme(:ggplot2)\n\nIn order to get the orbit for the ISS I used a Two-Line Element which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below and now we have access to the information to start making our ISS orbit.\n\nISS = tle\"\"\"\nISS (ZARYA)\n1 25544U 98067A   21103.84943184  .00000176  00000-0  11381-4 0  9990\n2 25544  51.6434 300.9481 0002858 223.8443 263.8789 15.48881793278621\n\"\"\"\n1-element Vector{TLE}:\n TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)\n\nNow that we have the TLE we can pass that into SatelliteToolbox’s orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.\n\nISS[1].n\n\n\norbit = init_orbit_propagator(Val(:twobody), ISS[1]);\ntime = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.\no, r, v = propagate!(orbit, time);\n\nNow we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math.\nadd more discussion about the math\n\nfunction sunlight(Rbody, r_sun_body, r_body_sc)\n    Rsun = 695_700u\"km\"\n    \n    hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)\n    \n    θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))\n\n    θu = atan(Rbody / hu)\n    du = hu * sin(θu) / sin(θe + θu)\n\n    θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))\n    dp = Rbody * sin(θp) / cos(θe - θp)\n\n    S = 1\n    if (θe < π / 2) && (norm(r_body_sc) < du)\n        S = 0\n    end\n    if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))\n        S = (norm(r_body_sc .|> u\"km\") - du) / (dp - du) |> ustrip\n    end\n\n    return S\nend\n\nThen we can pass all the values we’ve gathered into the function we just made.\n\nS = r .|> R -> sunlight(6371u\"km\", [0.5370, 1.2606, 0.5466] .* 1e8u\"km\", R .* u\"m\");\n\nPlotting the Results\nThe sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant.\n\n\nShow code\n# Get fancy with the line color. \nlight_range = range(colorant\"black\", stop = colorant\"orange\", length = 101);\nlight_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];\n\nplot(\n    LinRange(0, 24, length(S)),\n    S .* 100,\n    linewidth = 5,\n    legend = false,\n    color = light_colors,\n);\n\nxlabel!(\"Time (hr)\");\nylabel!(\"Sunlight (%)\");\ntitle!(\"ISS Sunlight Over a Day\")\n\n\nFigure 1: ISS Sunlight\n\n\n\nLooking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region.\nTime in Sun:\n\nsun = length(S[S.==1])/length(S) * 100\n62.03323593209401\n\nTime in Darkness:\n\numbra = length(S[S.==0])/length(S) * 100\n37.64408511553699\n\nTime in Penumbra:\n\npenumbra = 100 - umbra - sun\n0.322678952369003\n\nThe ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes.\n\n\n\n“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/.\n\n\n\n\n",
+    "preview": "posts/2021-04-14-iss-eclipse-determination/preview.png",
+    "last_modified": "2021-05-03T21:23:45-07:00",
+    "input_file": {},
+    "preview_width": 1292,
+    "preview_height": 703
+  },
   {
     "path": "posts/2021-04-01-air-propulsion-simulation/",
     "title": "Air Propulsion Simulation",
@@ -14,29 +36,11 @@
       "Julia",
       "Capstone"
     ],
-    "contents": "\r\nFor Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just napkin math to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.\r\n\r\n\r\nShow code\r\nusing Plots\r\ntheme(:ggplot2); # In true R spirit\r\n\r\nusing Unitful\r\nusing DataFrames\r\nusing Measurements\r\nusing Measurements: value, uncertainty\r\nusing CSV\r\n\r\nThe Simulation\r\nI chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.\r\n\r\n# Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/\r\nV = (85 ± 5)u\"inch^3\"\r\nP0 = (4200.0 ± 300)u\"psi\"\r\nWtank = (2.3 ± 0.2)u\"lb\"\r\nPmax = (250 ± 50)u\"psi\" # Max Pressure that can come out the nozzle\r\n\r\nThe nozzle diameter was changed until the air prop system had a burn time similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.\r\n\r\n# Params\r\nd_nozzle = ((1 // 18) ± 0.001)u\"inch\"\r\na_nozzle = (pi / 4) * d_nozzle^2\r\n\r\nThese are just universal values for what a typical day would look like during the summer in Northern Arizona. (Çengel and Boles 2015)\r\n\r\n# Universal Stuff\r\nP_amb = (1 ± 0.2)u\"atm\"\r\nγ = 1.4 ± 0.05\r\nR = 287.05u\"J/(kg * K)\"\r\nT = (300 ± 20)u\"K\"\r\n\r\nThe actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate \\(\\dot{m}\\), which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by \\(\\dot{m}\\) and recalculate pressure using the new mass then repeat the whole process.\r\nThe bulk of the equations in the simulation came from (Çengel and Boles 2015), while the Thrust and \\(v_e\\) equations came from (Sutton and Biblarz 2001, eq: 2-14).\r\n\\[ T = \\dot{m} \\cdot v_\\text{Exit} + A_\\text{Nozzle} \\cdot (P - P_\\text{Ambient}) \\]\r\nThe initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and burn time vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.\r\n\r\ndf = let\r\nt = 0.0u\"s\"\r\nP = P0 |> u\"Pa\"\r\nM = V * (P / (R * T)) |> u\"kg\"\r\nts = 1u\"ms\"\r\ndf = DataFrame(Thrust=(0 ± 0)u\"N\", Pressure=P0, Time=0.0u\"s\", Mass=M)\r\n  while M > 0.005u\"kg\"\r\n      # Calculate what is leaving tank\r\n      P = minimum([P, Pmax])\r\n      ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |> u\"m/s\"\r\n      ρ = P / (R * T) |> u\"kg/m^3\"\r\n      ṁ = ρ * a_nozzle * ve |> u\"kg/s\"\r\n  \r\n      Thrust = ṁ * ve + a_nozzle * (P - P_amb) |> u\"N\"\r\n  \r\n      # Calculate what is still in the tank\r\n      M = M - ṁ * ts |> u\"kg\"\r\n      P = (M * R * T) / V |> u\"Pa\"\r\n      t = t + ts\r\n  \r\n      df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M)\r\n      append!(df, df_step)\r\n  end\r\n  df\r\nend\r\n\r\nAnalysis\r\nBelow in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.\r\n\r\n\r\nShow code\r\n\r\nthrust_values = df.Thrust .|> ustrip .|> value;\r\nthrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;\r\n\r\nair = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|> u\"s\" .|> ustrip);\r\n\r\n\r\nplot(df.Time .|> ustrip, thrust_values, \r\n    title=\"Thrust Over Time\", \r\n    ribbon=(thrust_uncertainties, thrust_uncertainties), \r\n    fillalpha=.2,label=\"Thrust\",\r\n    xlabel=\"Time (s)\", \r\n    ylabel=\"Thrust (N)\",\r\n    size = (1200, 800),\r\n    )\r\n\r\n\r\nFigure 1: Air Proplsion Simulation\r\n\r\n\r\n\r\nIn Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.\r\n\r\n\r\nShow code\r\n\r\nf10 = CSV.read(\"AeroTech_F10.csv\", DataFrame);\r\nf15 = CSV.read(\"Estes_F15.csv\", DataFrame);\r\ng8 = CSV.read(\"AeroTech_G8ST.csv\", DataFrame);\r\n\r\n\r\nplot(air.Time, air.Thrust, label=\"Air Propulsion\", fillalpha=.1, legend=:topleft, size = (1200, 800));\r\n\r\nfor (d, l) in [(f10, \"F10\"), (f15, \"F15\"), (g8, \"G8ST\")]\r\n    plot!(d[!,\"Time (s)\"], d[!, \"Thrust (N)\"], label=l);\r\nend\r\n\r\ntitle!(\"Propulsion Comparison\");\r\nxlabel!(\"Time (s)\");\r\nylabel!(\"Thrust (N)\")\r\n\r\n\r\nFigure 2: Rocket Motor Data: (Coker, n.d.)\r\n\r\n\r\n\r\nIn the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.\r\nFuture Work\r\nAfter determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.\r\n\r\n\r\n\r\nCoker, John. n.d. “Rocket Motor Data.” https://www.thrustcurve.org/.\r\n\r\n\r\nÇengel, Yunus A., and Michael A. Boles. 2015. Thermodynamics: An Engineering Approach. Eighth edition. New York: McGraw-Hill Education.\r\n\r\n\r\nSutton, George P., and Oscar Biblarz. 2001. Rocket Propulsion Elements. 7th ed. New York: John Wiley & Sons.\r\n\r\n\r\n\r\n\r\n",
-    "preview": {},
-    "last_modified": "2021-04-25T12:19:22-07:00",
-    "input_file": {}
-  },
-  {
-    "path": "posts/2021-04-14-iss-eclipse-determination/",
-    "title": "ISS Eclipse Determination",
-    "description": "Determining how much sunlight a body is receiving.",
-    "author": [
-      {
-        "name": "Anson Biggs",
-        "url": "https://ansonbiggs.com"
-      }
-    ],
-    "date": "2021-04-01",
-    "categories": [
-      "Julia",
-      "Astrodynamics"
-    ],
-    "contents": "\r\nDetermining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space with no solar radiation to power the solar panels and keep the spacecraft from freezing.\r\nWhat is an Eclipse\r\nGeometry of an EclipseBody Radius’s and Position VectorsThe Code\r\n\r\n\r\nShow code\r\nusing Unitful\r\nusing LinearAlgebra\r\nusing SatelliteToolbox\r\nusing Plots\r\nusing Colors\r\ntheme(:ggplot2)\r\n\r\n\r\nISS = tle\"\"\"\r\nISS (ZARYA)\r\n1 25544U 98067A   21103.84943184  .00000176  00000-0  11381-4 0  9990\r\n2 25544  51.6434 300.9481 0002858 223.8443 263.8789 15.48881793278621\r\n\"\"\"\r\n\r\n\r\norbit = init_orbit_propagator(Val(:twobody), ISS[1]);\r\ntime = 0:0.1:((24 / ISS[1].n) .* 60 * 60);\r\no, r, v = propagate!(orbit, time);\r\n\r\n\r\nfunction sunlight(Rbody, r_sun_body, r_body_sc)\r\n    Rsun = 695_700u\"km\"\r\n    \r\n    hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)\r\n    \r\n    θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))\r\n\r\n    θu = atan(Rbody / hu)\r\n    du = hu * sin(θu) / sin(θe + θu)\r\n\r\n    θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))\r\n    dp = Rbody * sin(θp) / cos(θe - θp)\r\n\r\n    S = 1\r\n    if (θe < π / 2) && (norm(r_body_sc) < du)\r\n        S = 0\r\n    end\r\n    if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))\r\n        S = (norm(r_body_sc .|> u\"km\") - du) / (dp - du) |> ustrip\r\n    end\r\n\r\n    return S\r\nend\r\n\r\n\r\nS = r .|> R -> sunlight(6371u\"km\", [0.5370, 1.2606, 0.5466] .* 1e8u\"km\", R .* u\"m\")\r\n\r\nPlotting the Results\r\n\r\n\r\nShow code\r\nlight_range = range(colorant\"black\", stop = colorant\"yellow\", length = 101);\r\nlight_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];\r\n\r\nplot(\r\n    LinRange(0, 24, length(S)),\r\n    S .* 100,\r\n    linewidth = 5,\r\n    legend = false,\r\n    color = light_colors,\r\n);\r\n\r\nxlabel!(\"Time (hr)\");\r\nylabel!(\"Sunlight (%)\");\r\ntitle!(\"ISS Sunlight Over a Day\")\r\n\r\n\r\nFigure 1: Rocket Motor Data: [@thrustcurve]\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
-    "preview": {},
-    "last_modified": "2021-04-25T12:27:18-07:00",
-    "input_file": {}
+    "contents": "\nFor Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just napkin math to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.\n\n\nShow code\nusing Plots\ntheme(:ggplot2); # In true R spirit\n\nusing Unitful\nusing DataFrames\nusing Measurements\nusing Measurements: value, uncertainty\nusing CSV\n\nThe Simulation\nI chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.\n\n# Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/\nV = (85 ± 5)u\"inch^3\"\nP0 = (4200.0 ± 300)u\"psi\"\nWtank = (2.3 ± 0.2)u\"lb\"\nPmax = (250 ± 50)u\"psi\" # Max Pressure that can come out the nozzle\n\nThe nozzle diameter was changed until the air prop system had a burn time similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.\n\n# Params\nd_nozzle = ((1 // 18) ± 0.001)u\"inch\"\na_nozzle = (pi / 4) * d_nozzle^2\n\nThese are just universal values for what a typical day would look like during the summer in Northern Arizona. (Çengel and Boles 2015)\n\n# Universal Stuff\nP_amb = (1 ± 0.2)u\"atm\"\nγ = 1.4 ± 0.05\nR = 287.05u\"J/(kg * K)\"\nT = (300 ± 20)u\"K\"\n\nThe actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate \\(\\dot{m}\\), which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by \\(\\dot{m}\\) and recalculate pressure using the new mass then repeat the whole process.\nThe bulk of the equations in the simulation came from (Çengel and Boles 2015), while the Thrust and \\(v_e\\) equations came from (Sutton and Biblarz 2001, eq: 2-14).\n\\[ T = \\dot{m} \\cdot v_\\text{Exit} + A_\\text{Nozzle} \\cdot (P - P_\\text{Ambient}) \\]\nThe initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and burn time vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.\n\ndf = let\nt = 0.0u\"s\"\nP = P0 |> u\"Pa\"\nM = V * (P / (R * T)) |> u\"kg\"\nts = 1u\"ms\"\ndf = DataFrame(Thrust=(0 ± 0)u\"N\", Pressure=P0, Time=0.0u\"s\", Mass=M)\n  while M > 0.005u\"kg\"\n      # Calculate what is leaving tank\n      P = minimum([P, Pmax])\n      ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |> u\"m/s\"\n      ρ = P / (R * T) |> u\"kg/m^3\"\n      ṁ = ρ * a_nozzle * ve |> u\"kg/s\"\n  \n      Thrust = ṁ * ve + a_nozzle * (P - P_amb) |> u\"N\"\n  \n      # Calculate what is still in the tank\n      M = M - ṁ * ts |> u\"kg\"\n      P = (M * R * T) / V |> u\"Pa\"\n      t = t + ts\n  \n      df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M)\n      append!(df, df_step)\n  end\n  df\nend\n\nAnalysis\nBelow in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.\n\n\nShow code\n\nthrust_values = df.Thrust .|> ustrip .|> value;\nthrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;\n\nair = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|> u\"s\" .|> ustrip);\n\n\nplot(df.Time .|> ustrip, thrust_values, \n    title=\"Thrust Over Time\", \n    ribbon=(thrust_uncertainties, thrust_uncertainties), \n    fillalpha=.2,label=\"Thrust\",\n    xlabel=\"Time (s)\", \n    ylabel=\"Thrust (N)\",\n    size = (1200, 800),\n    )\n\n\nFigure 1: Air Proplsion Simulation\n\n\n\nIn Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.\n\n\nShow code\n\nf10 = CSV.read(\"AeroTech_F10.csv\", DataFrame);\nf15 = CSV.read(\"Estes_F15.csv\", DataFrame);\ng8 = CSV.read(\"AeroTech_G8ST.csv\", DataFrame);\n\n\nplot(air.Time, air.Thrust, label=\"Air Propulsion\", fillalpha=.1, legend=:topleft, size = (1200, 800));\n\nfor (d, l) in [(f10, \"F10\"), (f15, \"F15\"), (g8, \"G8ST\")]\n    plot!(d[!,\"Time (s)\"], d[!, \"Thrust (N)\"], label=l);\nend\n\ntitle!(\"Propulsion Comparison\");\nxlabel!(\"Time (s)\");\nylabel!(\"Thrust (N)\")\n\n\nFigure 2: Rocket Motor Data: (Coker, n.d.)\n\n\n\nIn the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.\nFuture Work\nAfter determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.\n\n\n\nCoker, John. n.d. “Rocket Motor Data.” https://www.thrustcurve.org/.\n\n\nÇengel, Yunus A., and Michael A. Boles. 2015. Thermodynamics: An Engineering Approach. Eighth edition. New York: McGraw-Hill Education.\n\n\nSutton, George P., and Oscar Biblarz. 2001. Rocket Propulsion Elements. 7th ed. New York: John Wiley & Sons.\n\n\n\n\n",
+    "preview": "posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-6-J1.png",
+    "last_modified": "2021-05-03T19:31:26-07:00",
+    "input_file": {},
+    "preview_width": 1200,
+    "preview_height": 800
   }
 ]
diff --git a/docs/search.json b/docs/search.json
index 7855e13..942bb99 100644
--- a/docs/search.json
+++ b/docs/search.json
@@ -5,15 +5,15 @@
       "title": "Hi, I'm Anson.",
       "description": "I'm an Astronautical Engineer studying at Embry-Riddle Prescott.",
       "author": [],
-      "contents": "\r\nI mostly write code, but sometimes I make 3D Models. This website is where I plan on breaking down some of my more interesting findings and sharing them with the World Wide Web. If you think I could be a could fit at your company then take a look at my Resume, otherwise you can reach me on Telegram or by Email.\r\n\r\n\r\n\r\n",
-      "last_modified": "2021-04-30T22:47:07-07:00"
+      "contents": "\nI mostly write code, but sometimes I make 3D Models. This website is where I plan on breaking down some of my more interesting findings and sharing them with the World Wide Web. If you think I could be a could fit at your company then take a look at my Resume, otherwise you can reach me on Telegram or by Email.\n\n\n\n",
+      "last_modified": "2021-05-03T21:24:36-07:00"
     },
     {
       "path": "index.html",
       "title": "Anson's Projects",
       "author": [],
-      "contents": "\r\n\r\n\r\n\r\n",
-      "last_modified": "2021-04-30T22:47:08-07:00"
+      "contents": "\n\n\n\n",
+      "last_modified": "2021-05-03T21:24:37-07:00"
     }
   ],
   "collections": ["posts/posts.json"]
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index ad90148..9ef6d72 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -2,18 +2,18 @@
 
   
     https://projects.ansonbiggs.com/about.html
-    2021-04-14T22:36:57-07:00
+    2021-05-03T19:29:58-07:00
   
   
     https://projects.ansonbiggs.com/
-    2021-04-02T14:53:47-07:00
-  
-  
-    https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation/
-    2021-04-25T12:19:22-07:00
+    2021-04-01T20:38:43-07:00
   
   
     https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination/
-    2021-04-25T12:27:18-07:00
+    2021-05-03T21:23:45-07:00
+  
+  
+    https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation/
+    2021-05-03T19:31:26-07:00
   
 

From bd67c9682abcffa24f2bb9bdc2582755c56a3d5c Mon Sep 17 00:00:00 2001
From: Anson Biggs 
Date: Mon, 3 May 2021 21:37:31 -0700
Subject: [PATCH 2/4] Update Air Prop Thumbnail

---
 .../air-propulsion-simulation.Rmd             |   2 +-
 .../air-propulsion-simulation.html            |   2 +-
 .../figure-html5/unnamed-chunk-6-J1.png       | Bin 23076 -> 22805 bytes
 .../figure-html5/unnamed-chunk-7-J1.png       | Bin 48394 -> 49257 bytes
 docs/index.html                               |   2 +-
 docs/index.xml                                | 122 +++++++++++++++++-
 .../figure-html5/unnamed-chunk-6-J1.png       | Bin 23076 -> 22805 bytes
 .../figure-html5/unnamed-chunk-7-J1.png       | Bin 48394 -> 49257 bytes
 .../index.html                                |   6 +-
 docs/posts/posts.json                         |   6 +-
 docs/search.json                              |   4 +-
 docs/sitemap.xml                              |   2 +-
 12 files changed, 132 insertions(+), 14 deletions(-)

diff --git a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd
index 6282d4b..083db74 100644
--- a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd
+++ b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd
@@ -112,7 +112,7 @@ end
 
 Below in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it's technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that's actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of. 
 
-```{julia, code_folding=TRUE, results='show',layout="l-body-outset", fig.cap = "Air Proplsion Simulation", preview=TRUE}
+```{julia, code_folding=TRUE, results='show',layout="l-body-outset", fig.cap = "Air Proplsion Simulation", preview=FALSE}
 
 thrust_values = df.Thrust .|> ustrip .|> value;
 thrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;
diff --git a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html
index 276f3bb..526223f 100644
--- a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html
+++ b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html
@@ -1580,7 +1580,7 @@ Show code
     )
-Air Proplsion Simulation +Air Proplsion Simulation

Figure 1: Air Proplsion Simulation

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- +

Air Propulsion Simulation

diff --git a/docs/index.xml b/docs/index.xml index 28431b0..b289d4f 100644 --- a/docs/index.xml +++ b/docs/index.xml @@ -23,12 +23,130 @@ Air Propulsion Simulation Anson Biggs https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation - Simulating the performance of an air propulsion system as an alternative to solid rocket motors. + + + +<p>For Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just <em>napkin math</em> to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.</p> +<pre class="julia"><code>using Plots +theme(:ggplot2); # In true R spirit + +using Unitful +using DataFrames +using Measurements +using Measurements: value, uncertainty +using CSV</code></pre> +<h2 id="the-simulation">The Simulation</h2> +<p>I chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.</p> +<pre class="julia"><code># Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/ +V = (85 ± 5)u&quot;inch^3&quot; +P0 = (4200.0 ± 300)u&quot;psi&quot; +Wtank = (2.3 ± 0.2)u&quot;lb&quot; +Pmax = (250 ± 50)u&quot;psi&quot; # Max Pressure that can come out the nozzle</code></pre> +<p>The nozzle diameter was changed until the air prop system had a <em>burn time</em> similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.</p> +<pre class="julia"><code># Params +d_nozzle = ((1 // 18) ± 0.001)u&quot;inch&quot; +a_nozzle = (pi / 4) * d_nozzle^2</code></pre> +<p>These are just universal values for what a typical day would look like during the summer in Northern Arizona. <span class="citation">(Çengel and Boles 2015)</span></p> +<pre class="julia"><code># Universal Stuff +P_amb = (1 ± 0.2)u&quot;atm&quot; +γ = 1.4 ± 0.05 +R = 287.05u&quot;J/(kg * K)&quot; +T = (300 ± 20)u&quot;K&quot;</code></pre> +<p>The actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate <span class="math inline">\(\dot{m}\)</span>, which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by <span class="math inline">\(\dot{m}\)</span> and recalculate pressure using the new mass then repeat the whole process.</p> +<p>The bulk of the equations in the simulation came from <span class="citation">(Çengel and Boles 2015)</span>, while the Thrust and <span class="math inline">\(v_e\)</span> equations came from <span class="citation">(Sutton and Biblarz 2001, eq: 2-14)</span>.</p> +<p><span class="math display">\[ T = \dot{m} \cdot v_\text{Exit} + A_\text{Nozzle} \cdot (P - P_\text{Ambient}) \]</span></p> +<p>The initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and <em>burn time</em> vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.</p> +<pre class="julia"><code>df = let +t = 0.0u&quot;s&quot; +P = P0 |&gt; u&quot;Pa&quot; +M = V * (P / (R * T)) |&gt; u&quot;kg&quot; +ts = 1u&quot;ms&quot; +df = DataFrame(Thrust=(0 ± 0)u&quot;N&quot;, Pressure=P0, Time=0.0u&quot;s&quot;, Mass=M) + while M &gt; 0.005u&quot;kg&quot; + # Calculate what is leaving tank + P = minimum([P, Pmax]) + ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |&gt; u&quot;m/s&quot; + ρ = P / (R * T) |&gt; u&quot;kg/m^3&quot; + ṁ = ρ * a_nozzle * ve |&gt; u&quot;kg/s&quot; + + Thrust = ṁ * ve + a_nozzle * (P - P_amb) |&gt; u&quot;N&quot; + + # Calculate what is still in the tank + M = M - ṁ * ts |&gt; u&quot;kg&quot; + P = (M * R * T) / V |&gt; u&quot;Pa&quot; + t = t + ts + + df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M) + append!(df, df_step) + end + df +end</code></pre> +<h2 id="analysis">Analysis</h2> +<p>Below in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.</p> +<pre class="julia"><code> +thrust_values = df.Thrust .|&gt; ustrip .|&gt; value; +thrust_uncertainties = df.Thrust .|&gt; ustrip .|&gt; uncertainty; + +air = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|&gt; u&quot;s&quot; .|&gt; ustrip); + + +plot(df.Time .|&gt; ustrip, thrust_values, + title=&quot;Thrust Over Time&quot;, + ribbon=(thrust_uncertainties, thrust_uncertainties), + fillalpha=.2,label=&quot;Thrust&quot;, + xlabel=&quot;Time (s)&quot;, + ylabel=&quot;Thrust (N)&quot;, + size = (1200, 800), + )</code></pre> +<div class="figure"> +<img src="file571aee56c6a_files/figure-html/unnamed-chunk-6-J1.png" alt="Air Proplsion Simulation" width="600" /> +<p class="caption"> +(#fig:unnamed-chunk-6)Air Proplsion Simulation +</p> +</div> +<p>In Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.</p> +<pre class="julia"><code> +f10 = CSV.read(&quot;AeroTech_F10.csv&quot;, DataFrame); +f15 = CSV.read(&quot;Estes_F15.csv&quot;, DataFrame); +g8 = CSV.read(&quot;AeroTech_G8ST.csv&quot;, DataFrame); + + +plot(air.Time, air.Thrust, label=&quot;Air Propulsion&quot;, fillalpha=.1, legend=:topleft, size = (1200, 800)); + +for (d, l) in [(f10, &quot;F10&quot;), (f15, &quot;F15&quot;), (g8, &quot;G8ST&quot;)] + plot!(d[!,&quot;Time (s)&quot;], d[!, &quot;Thrust (N)&quot;], label=l); +end + +title!(&quot;Propulsion Comparison&quot;); +xlabel!(&quot;Time (s)&quot;); +ylabel!(&quot;Thrust (N)&quot;)</code></pre> +<div class="figure"> +<img src="file571aee56c6a_files/figure-html/unnamed-chunk-7-J1.png" alt="Rocket Motor Data: [@thrustcurve]" width="600" data-distill-preview=1 /> +<p class="caption"> +(#fig:unnamed-chunk-7)Rocket Motor Data: <span class="citation">(Coker, n.d.)</span> +</p> +</div> +<p>In the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.</p> +<h2 id="future-work">Future Work</h2> +<p>After determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.</p> +<pre class="r distill-force-highlighting-css"><code></code></pre> +<div id="refs" class="references csl-bib-body hanging-indent"> +<div id="ref-thrustcurve" class="csl-entry"> +Coker, John. n.d. <span>“Rocket <span>Motor</span> <span>Data</span>.”</span> <a href="https://www.thrustcurve.org/">https://www.thrustcurve.org/</a>. +</div> +<div id="ref-cengel_thermodynamics" class="csl-entry"> +Çengel, Yunus A., and Michael A. Boles. 2015. <em>Thermodynamics: An Engineering Approach</em>. Eighth edition. New York: McGraw-Hill Education. +</div> +<div id="ref-sutton_rocket_2001" class="csl-entry"> +Sutton, George P., and Oscar Biblarz. 2001. <em>Rocket Propulsion Elements</em>. 7th ed. New York: John Wiley &amp; Sons. +</div> +</div> + dbf2ace5c1414ee7c72e89cac1535434 Julia Capstone https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation Thu, 01 Apr 2021 00:00:00 +0000 - + diff --git a/docs/posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-6-J1.png b/docs/posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-6-J1.png index 250f2d906255b23410337d30c46b6df969943ddd..2030850df301d6088c9d9941a0acc087719ae4a2 100644 GIT binary patch literal 22805 zcmb@ucRW|`8$YghOGXq$G7}jY$rj4Y&WN&JS=p4D%zsIllAMfM5&biNhU-xxi^LbrwA1F!_;!)t?;NTF-+?P|QIcW);Bjmr&m8qdPIJ7u268F@cJ}nHt_@r$V!|`WJO(UmY=o}rs zmzSiN816fQXs$Whrj)!)PujGWH-2PBUj9Kg_i}7bpE)}jWFjGbC5LI`$}iTF+pkW% z=b_EK(DDzi%u7W z6OGq(;Qu&{#JDHORrp4nCPoj2M}?2}*JQ}@4%D-?cmCEAiSGZcW!1=*FAHC^T`cT# zUr(gb$<>$a^u~F2=N0iwD*I8ltwMrt-ekJuVkI-NE>%NOU+KD@Q zF%ihe%g5JOGRYQs+gLI8(L#0Uv#F*!e=?;{{I;75{a2U68x5!1V#@VueFCG;y!2rp z{^x7r=AdC8_F*{Afy{GSH zob$rDK7F{ij43ctW(<8XuQe)YJyH?4teLA{$C^{Y<+i(ij)d{f&SWS;5+$W}Y0=$| z3-nTVR(_DsO9lLPS+3+8@#x8T=&@Z(<1lRB_m<>_RmIBpvox+_-eg>nEkE9pkllR5 z`Fy&CxCW>l&aR`GuI5)ao*?O;Arwr(W0q67>0B!q=dx6qnNwAko{miwJ-{+jS>+qI zSHWb@3$OoziL6f09BnU^FOT%~Z7t-tTj}cI#upcF6$4Qi9m8ak_u#ik<5=d){w@o- z4Hu*-J4QyTRuW^K#^3S>&9p{GG*4MoA8Z;mhcD(fP&ZIH4&jVWwz56WODZpSfjzLa zwCrK?zszQ4X&H0dxNV@&++)Qb^W{;letp1|2FmC1h3&V4CXRMu#wAF z`Do?J&TMGh{$zc*jzhl@o!5L$^&zm&;;8Y;cwJ7_t{LvwA5Wr@$*&qZ_78E#%I34@ zN1tu&9YO2(8$8ney!-fIPTc?M6gFbRmRFf4L(P} z1b_x1|KjziCEC?@&NQsAmme!z>`)a7d`R%T_L%Y?<#;etS#T8R*O2Ql6>i(x_ zZ5hK((4K(fyp-`U(|vz}M)Yud0*<9)eK5^YptbA7=+VI_U;pB2Gl$1)yl>S?p!NQo zM)hu^k~^3C{`LuKkB$V%xV@nnhmjXEz#t9PM+eIhHy=L(F@Ul8e%hcRh>&i70|Y~i z<4AvJXJ>!^i5gsBLyfG*`O`o^x24hBXQAKpJucybpi8=Mti|I&2I0IvoXbv490*_Q%PPMNYn#t~%VE_td?C z^V4RgT(MGjNXkx~@5X=jp5qMZqd51lE5j@s;w^I654(ygV>XB1=a z?12+ipJz@&^w1PDil2U7wC)j7`lsIxqcPr#68ZZXTXt+Xkw$)J{(}a?euQ+?AGY z00C*&%G2k%(~Qa1X~kLK7Y0H12jRk_(-w4Ij+OH|bY370Eb|7_Q)A2Ao`GKmvd+aYN&E+#0ALTS*=v)@)rn^HsX4? zGehJ0_d8JCvU6qo6_M+cp%UBb?K%$L7k>EcB~KbKKQButulKjR7adK{b|fPFL0p3f zy1<+>`}5U@^Iw(a5PswU4gfwFjysbH3;V?6$LnzkCn=Cx4CmtC@Zt)iiD;q40##DU z=$y5xc9A`c(UsA?kuAlKoMS#$txD#z%Yy`_KO+0M?A%vg^lrAu;>Vi{!^6Xsm6g^- z;v3oT>7_TV1r`gs*h~JrrrG~GGZEFYN8NhmC|-&vjF z$s~LEosRgQcQ1p2fdazzr0RrIeekub{tu9^Vdw=(8Sb2v^`y`3L-urOebylk$e zsi`P>u%6?#Xx`I|TijS++6Baq0Ii|pZu7h+_8UmdWRGS!g3gn&EJR{c+wT5asv&%Zd8H=BZ}~=PW0GzK^aj@U&W+(70+8%B+;g zgm<-2ZR6qoG+*`3qP0hPW9{JJAYWYf*_Q>k3`t))t0*w{yuHQO+trod7=GpUQ$)EU z)68+-$n@u^a)NV$9Qk&^`7eu3onSiL^s)inQqh0Dr#z$lp+Xcl_9uO?c9rXn+tx4{ z?^O}WDkBW|#OYXcITR<_1m`s)1$ybx(5sK9FFyuUfH;7^f)o zF7937MnkUh#iBtuV8`_?r7i3I;bnKnX0~FBia{U3tGqA%{LVEH5)@E*|{#71h?6sWj{T@))d!zab2ARU28>mWKf+(^&{dKp8B70^AyU-o98oTD4QT zvC4u&5owNlBJDQK_P4W#4M*EF4KyD65!L%s>8h#hngz3Y&Fs-4Zo6ykqNCOAh^Yi} z8WwJv53}JiYVy0pifEEA+NG=T1Jx~k3H!L6wHXfGifz!JqPw$+(gEbRjG8{o`7K({ zYK`vp;&W8|{UuJ+8Y{e~8n>%vuhJ^%e;LvKV3;($K8;_s(`s$C`fl#ES0BdXK=g1z z)F&{UX2G$RkdM;gw_e=#j~kcSH0@e$HMD%ZHBs27>jDzPx@u<{PEu)#zdS)W`~zE- z+HJi9bkANJXo>2b=;}zIEzI^Zhpuav0$(NQVMP5!*#+WQyoG&=Dg9f6PXq779qrE` z#1O-cl%L*TYmWmFJ_CyW&<*U12y3@_Ekxqf6Wy8qXpqsj`cTKV?h+i^GQ?^E;u6;g zjjRN*ovLYTYXduMW*m4Mq&r91Y{KCpSVl8(9*1>gn2HtB#Dfg{i<_I9Ru%hCs)47s zz;qM^(QggrcwlOHB){!Aqq%ZYKNw)PASPm;w+U$IzL*Nr(Cx2w17o#+pW);?US%Cj z8O~inHcVB;qnnCxB5rFh7%^@eJ-}M>kz7U-_PFA>auMv7R#r=KY5C>l<$}3Q(OH*P zz$g*{OB7~g?J_v{wB=*2!{R`8b~ae3Y7wUh=q8_)!oDEG?%IL*7%T96db)u*q8S{E zmYKE1#l_GYN+WY}^NWj!49B?dOcB>~r>i1Lovr=ou}+rz`fP{R$6FhSAp>S4uf=ap zy&5lUS1OIow-X8q3I|(NKyh12>v`vZ`Q9w8LbINq@9FtGlv&lk{Qjy}Tc4HR7>$9u z8L_dkz>GyjMVrW*k#S zV({g-nL?YuVd7?bMT~><`5xHl;PA=Pp2EQ~dGHS%xKy4OaZljjP<*(Hi-Ys)Gl&eF zmuJ9f_&}PVWy*{U(}ZR5u*2W)XFbMA;&ACm{p%1L4_uce zEOsaOXgk;t0p3wWBDKefR_`92 z#=m?AOiVg2;LW1^{O9m4ofq&FVu34xJLVwD0dIQh!<(ZIG&K4^hh!Yl@L3Jb^<;|U zW@_XtjXoM4>FMG5c9LDYZBsQe3k==T6CD`|~5+buVHu z#!yph>);7~tXR=^T93?T!^5E|@&?T?)A*`MzCD*2MeA!|G|%H{AC#F73+350CnZ<8JIIn7)h7 z&d<*uU?mrOl>bzr(BLajqcw`>VDF1=rStdKr%&Gb<14Zre`2Y>r{`hf&Dhqb(b3Uo zJC$V=B$bmcU5sdbitjBZ5~o!5&IcTCO-;>brP{Ep0w%wK!NCJ`WwM4`R|wyioDw~6 z?yqc;ohp($U}|m-R>agZ0j$_z8dx})dj!vD@BDdrk{Y-PRsD#HpaT1w&g*ghQ#fTD zm?~G`0j)~sjm~5_a6~7sTyLjHwkIrso@W+ zm1<|Ju@D-`XcZp3vKg!K2Jg@rgBexe8|H=pMX<;IL`+P~GB_#iLdzAvMvQ(5(x3&v z*FR5ZXJ_}xb+r)@wTN{EGpgJhULJ9B0~ujrs7zW|SZE27O8R`rlNJ-acr_)1>*glS zS-*OF!_`biUz?QsK4#agaGE$F2g)*I^M1BY`DVN?H69%$L{tpw1F)lG*wi@PB8z^o z%*?p=

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-Air Proplsion Simulation +Air Proplsion Simulation

Figure 1: Air Proplsion Simulation

diff --git a/docs/posts/posts.json b/docs/posts/posts.json index 5b0d490..1b2ba66 100644 --- a/docs/posts/posts.json +++ b/docs/posts/posts.json @@ -37,9 +37,9 @@ "Capstone" ], "contents": "\nFor Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just napkin math to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.\n\n\nShow code\nusing Plots\ntheme(:ggplot2); # In true R spirit\n\nusing Unitful\nusing DataFrames\nusing Measurements\nusing Measurements: value, uncertainty\nusing CSV\n\nThe Simulation\nI chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.\n\n# Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/\nV = (85 ± 5)u\"inch^3\"\nP0 = (4200.0 ± 300)u\"psi\"\nWtank = (2.3 ± 0.2)u\"lb\"\nPmax = (250 ± 50)u\"psi\" # Max Pressure that can come out the nozzle\n\nThe nozzle diameter was changed until the air prop system had a burn time similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.\n\n# Params\nd_nozzle = ((1 // 18) ± 0.001)u\"inch\"\na_nozzle = (pi / 4) * d_nozzle^2\n\nThese are just universal values for what a typical day would look like during the summer in Northern Arizona. (Çengel and Boles 2015)\n\n# Universal Stuff\nP_amb = (1 ± 0.2)u\"atm\"\nγ = 1.4 ± 0.05\nR = 287.05u\"J/(kg * K)\"\nT = (300 ± 20)u\"K\"\n\nThe actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate \\(\\dot{m}\\), which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by \\(\\dot{m}\\) and recalculate pressure using the new mass then repeat the whole process.\nThe bulk of the equations in the simulation came from (Çengel and Boles 2015), while the Thrust and \\(v_e\\) equations came from (Sutton and Biblarz 2001, eq: 2-14).\n\\[ T = \\dot{m} \\cdot v_\\text{Exit} + A_\\text{Nozzle} \\cdot (P - P_\\text{Ambient}) \\]\nThe initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and burn time vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.\n\ndf = let\nt = 0.0u\"s\"\nP = P0 |> u\"Pa\"\nM = V * (P / (R * T)) |> u\"kg\"\nts = 1u\"ms\"\ndf = DataFrame(Thrust=(0 ± 0)u\"N\", Pressure=P0, Time=0.0u\"s\", Mass=M)\n while M > 0.005u\"kg\"\n # Calculate what is leaving tank\n P = minimum([P, Pmax])\n ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |> u\"m/s\"\n ρ = P / (R * T) |> u\"kg/m^3\"\n ṁ = ρ * a_nozzle * ve |> u\"kg/s\"\n \n Thrust = ṁ * ve + a_nozzle * (P - P_amb) |> u\"N\"\n \n # Calculate what is still in the tank\n M = M - ṁ * ts |> u\"kg\"\n P = (M * R * T) / V |> u\"Pa\"\n t = t + ts\n \n df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M)\n append!(df, df_step)\n end\n df\nend\n\nAnalysis\nBelow in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.\n\n\nShow code\n\nthrust_values = df.Thrust .|> ustrip .|> value;\nthrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;\n\nair = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|> u\"s\" .|> ustrip);\n\n\nplot(df.Time .|> ustrip, thrust_values, \n title=\"Thrust Over Time\", \n ribbon=(thrust_uncertainties, thrust_uncertainties), \n fillalpha=.2,label=\"Thrust\",\n xlabel=\"Time (s)\", \n ylabel=\"Thrust (N)\",\n size = (1200, 800),\n )\n\n\nFigure 1: Air Proplsion Simulation\n\n\n\nIn Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.\n\n\nShow code\n\nf10 = CSV.read(\"AeroTech_F10.csv\", DataFrame);\nf15 = CSV.read(\"Estes_F15.csv\", DataFrame);\ng8 = CSV.read(\"AeroTech_G8ST.csv\", DataFrame);\n\n\nplot(air.Time, air.Thrust, label=\"Air Propulsion\", fillalpha=.1, legend=:topleft, size = (1200, 800));\n\nfor (d, l) in [(f10, \"F10\"), (f15, \"F15\"), (g8, \"G8ST\")]\n plot!(d[!,\"Time (s)\"], d[!, \"Thrust (N)\"], label=l);\nend\n\ntitle!(\"Propulsion Comparison\");\nxlabel!(\"Time (s)\");\nylabel!(\"Thrust (N)\")\n\n\nFigure 2: Rocket Motor Data: (Coker, n.d.)\n\n\n\nIn the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.\nFuture Work\nAfter determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.\n\n\n\nCoker, John. n.d. “Rocket Motor Data.” https://www.thrustcurve.org/.\n\n\nÇengel, Yunus A., and Michael A. Boles. 2015. Thermodynamics: An Engineering Approach. Eighth edition. New York: McGraw-Hill Education.\n\n\nSutton, George P., and Oscar Biblarz. 2001. Rocket Propulsion Elements. 7th ed. New York: John Wiley & Sons.\n\n\n\n\n", - "preview": "posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-6-J1.png", - "last_modified": "2021-05-03T19:31:26-07:00", - "input_file": {}, + "preview": "posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-7-J1.png", + "last_modified": "2021-05-03T21:36:23-07:00", + "input_file": "air-propulsion-simulation.utf8.md", "preview_width": 1200, "preview_height": 800 } diff --git a/docs/search.json b/docs/search.json index 942bb99..a9cc35d 100644 --- a/docs/search.json +++ b/docs/search.json @@ -6,14 +6,14 @@ "description": "I'm an Astronautical Engineer studying at Embry-Riddle Prescott.", "author": [], "contents": "\nI mostly write code, but sometimes I make 3D Models. This website is where I plan on breaking down some of my more interesting findings and sharing them with the World Wide Web. If you think I could be a could fit at your company then take a look at my Resume, otherwise you can reach me on Telegram or by Email.\n\n\n\n", - "last_modified": "2021-05-03T21:24:36-07:00" + "last_modified": "2021-05-03T21:28:01-07:00" }, { "path": "index.html", "title": "Anson's Projects", "author": [], "contents": "\n\n\n\n", - "last_modified": "2021-05-03T21:24:37-07:00" + "last_modified": "2021-05-03T21:28:01-07:00" } ], "collections": ["posts/posts.json"] diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 9ef6d72..899b56f 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -14,6 +14,6 @@ https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation/ - 2021-05-03T19:31:26-07:00 + 2021-05-03T21:36:23-07:00 From 3da697bfeb771aba9bb0ddca1da1436cdf68d97b Mon Sep 17 00:00:00 2001 From: Anson Biggs Date: Mon, 3 May 2021 21:54:09 -0700 Subject: [PATCH 3/4] fix image scaling --- .../air-propulsion-simulation.Rmd | 3 +-- .../air-propulsion-simulation.html | 9 ++++----- .../figure-html5/unnamed-chunk-6-J1.png | Bin 22805 -> 16307 bytes .../figure-html5/unnamed-chunk-7-J1.png | Bin 49257 -> 29624 bytes docs/index.xml | 9 ++++----- .../figure-html5/unnamed-chunk-6-J1.png | Bin 22805 -> 16307 bytes .../figure-html5/unnamed-chunk-7-J1.png | Bin 49257 -> 29624 bytes .../index.html | 17 ++++++++--------- docs/posts/posts.json | 8 ++++---- docs/sitemap.xml | 2 +- 10 files changed, 22 insertions(+), 26 deletions(-) diff --git a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd index 083db74..0fe416e 100644 --- a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd +++ b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.Rmd @@ -126,7 +126,6 @@ plot(df.Time .|> ustrip, thrust_values, fillalpha=.2,label="Thrust", xlabel="Time (s)", ylabel="Thrust (N)", - size = (1200, 800), ) ``` @@ -139,7 +138,7 @@ f15 = CSV.read("Estes_F15.csv", DataFrame); g8 = CSV.read("AeroTech_G8ST.csv", DataFrame); -plot(air.Time, air.Thrust, label="Air Propulsion", fillalpha=.1, legend=:topleft, size = (1200, 800)); +plot(air.Time, air.Thrust, label="Air Propulsion", legend=:topleft); for (d, l) in [(f10, "F10"), (f15, "F15"), (g8, "G8ST")] plot!(d[!,"Time (s)"], d[!, "Thrust (N)"], label=l); diff --git a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html index 526223f..cccfbc2 100644 --- a/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html +++ b/_posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation.html @@ -1576,11 +1576,10 @@ Show code fillalpha=.2,label="Thrust", xlabel="Time (s)", ylabel="Thrust (N)", - size = (1200, 800), - )
+ )
-Air Proplsion Simulation +Air Proplsion Simulation

Figure 1: Air Proplsion Simulation

@@ -1598,7 +1597,7 @@ Show code g8 = CSV.read("AeroTech_G8ST.csv", DataFrame); -plot(air.Time, air.Thrust, label="Air Propulsion", fillalpha=.1, legend=:topleft, size = (1200, 800)); +plot(air.Time, air.Thrust, label="Air Propulsion", legend=:topleft); for (d, l) in [(f10, "F10"), (f15, "F15"), (g8, "G8ST")] plot!(d[!,"Time (s)"], d[!, "Thrust (N)"], label=l); @@ -1609,7 +1608,7 @@ Show code ylabel!("Thrust (N)")
-Rocket Motor Data: [@thrustcurve] +Rocket Motor Data: [@thrustcurve]

Figure 2: Rocket Motor Data: (Coker, n.d.)

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Show code fillalpha=.2,label="Thrust", xlabel="Time (s)", ylabel="Thrust (N)", - size = (1200, 800), - )

+ )
-Air Proplsion Simulation +Air Proplsion Simulation

Figure 1: Air Proplsion Simulation

@@ -2240,7 +2239,7 @@ Show code g8 = CSV.read("AeroTech_G8ST.csv", DataFrame); -plot(air.Time, air.Thrust, label="Air Propulsion", fillalpha=.1, legend=:topleft, size = (1200, 800)); +plot(air.Time, air.Thrust, label="Air Propulsion", legend=:topleft); for (d, l) in [(f10, "F10"), (f15, "F15"), (g8, "G8ST")] plot!(d[!,"Time (s)"], d[!, "Thrust (N)"], label=l); @@ -2251,7 +2250,7 @@ Show code ylabel!("Thrust (N)")
-Rocket Motor Data: [@thrustcurve] +Rocket Motor Data: [@thrustcurve]

Figure 2: Rocket Motor Data: (Coker, n.d.)

diff --git a/docs/posts/posts.json b/docs/posts/posts.json index 1b2ba66..163786e 100644 --- a/docs/posts/posts.json +++ b/docs/posts/posts.json @@ -36,11 +36,11 @@ "Julia", "Capstone" ], - "contents": "\nFor Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just napkin math to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.\n\n\nShow code\nusing Plots\ntheme(:ggplot2); # In true R spirit\n\nusing Unitful\nusing DataFrames\nusing Measurements\nusing Measurements: value, uncertainty\nusing CSV\n\nThe Simulation\nI chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.\n\n# Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/\nV = (85 ± 5)u\"inch^3\"\nP0 = (4200.0 ± 300)u\"psi\"\nWtank = (2.3 ± 0.2)u\"lb\"\nPmax = (250 ± 50)u\"psi\" # Max Pressure that can come out the nozzle\n\nThe nozzle diameter was changed until the air prop system had a burn time similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.\n\n# Params\nd_nozzle = ((1 // 18) ± 0.001)u\"inch\"\na_nozzle = (pi / 4) * d_nozzle^2\n\nThese are just universal values for what a typical day would look like during the summer in Northern Arizona. (Çengel and Boles 2015)\n\n# Universal Stuff\nP_amb = (1 ± 0.2)u\"atm\"\nγ = 1.4 ± 0.05\nR = 287.05u\"J/(kg * K)\"\nT = (300 ± 20)u\"K\"\n\nThe actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate \\(\\dot{m}\\), which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by \\(\\dot{m}\\) and recalculate pressure using the new mass then repeat the whole process.\nThe bulk of the equations in the simulation came from (Çengel and Boles 2015), while the Thrust and \\(v_e\\) equations came from (Sutton and Biblarz 2001, eq: 2-14).\n\\[ T = \\dot{m} \\cdot v_\\text{Exit} + A_\\text{Nozzle} \\cdot (P - P_\\text{Ambient}) \\]\nThe initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and burn time vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.\n\ndf = let\nt = 0.0u\"s\"\nP = P0 |> u\"Pa\"\nM = V * (P / (R * T)) |> u\"kg\"\nts = 1u\"ms\"\ndf = DataFrame(Thrust=(0 ± 0)u\"N\", Pressure=P0, Time=0.0u\"s\", Mass=M)\n while M > 0.005u\"kg\"\n # Calculate what is leaving tank\n P = minimum([P, Pmax])\n ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |> u\"m/s\"\n ρ = P / (R * T) |> u\"kg/m^3\"\n ṁ = ρ * a_nozzle * ve |> u\"kg/s\"\n \n Thrust = ṁ * ve + a_nozzle * (P - P_amb) |> u\"N\"\n \n # Calculate what is still in the tank\n M = M - ṁ * ts |> u\"kg\"\n P = (M * R * T) / V |> u\"Pa\"\n t = t + ts\n \n df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M)\n append!(df, df_step)\n end\n df\nend\n\nAnalysis\nBelow in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.\n\n\nShow code\n\nthrust_values = df.Thrust .|> ustrip .|> value;\nthrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;\n\nair = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|> u\"s\" .|> ustrip);\n\n\nplot(df.Time .|> ustrip, thrust_values, \n title=\"Thrust Over Time\", \n ribbon=(thrust_uncertainties, thrust_uncertainties), \n fillalpha=.2,label=\"Thrust\",\n xlabel=\"Time (s)\", \n ylabel=\"Thrust (N)\",\n size = (1200, 800),\n )\n\n\nFigure 1: Air Proplsion Simulation\n\n\n\nIn Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.\n\n\nShow code\n\nf10 = CSV.read(\"AeroTech_F10.csv\", DataFrame);\nf15 = CSV.read(\"Estes_F15.csv\", DataFrame);\ng8 = CSV.read(\"AeroTech_G8ST.csv\", DataFrame);\n\n\nplot(air.Time, air.Thrust, label=\"Air Propulsion\", fillalpha=.1, legend=:topleft, size = (1200, 800));\n\nfor (d, l) in [(f10, \"F10\"), (f15, \"F15\"), (g8, \"G8ST\")]\n plot!(d[!,\"Time (s)\"], d[!, \"Thrust (N)\"], label=l);\nend\n\ntitle!(\"Propulsion Comparison\");\nxlabel!(\"Time (s)\");\nylabel!(\"Thrust (N)\")\n\n\nFigure 2: Rocket Motor Data: (Coker, n.d.)\n\n\n\nIn the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.\nFuture Work\nAfter determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.\n\n\n\nCoker, John. n.d. “Rocket Motor Data.” https://www.thrustcurve.org/.\n\n\nÇengel, Yunus A., and Michael A. Boles. 2015. Thermodynamics: An Engineering Approach. Eighth edition. New York: McGraw-Hill Education.\n\n\nSutton, George P., and Oscar Biblarz. 2001. Rocket Propulsion Elements. 7th ed. New York: John Wiley & Sons.\n\n\n\n\n", + "contents": "\nFor Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just napkin math to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.\n\n\nShow code\nusing Plots\ntheme(:ggplot2); # In true R spirit\n\nusing Unitful\nusing DataFrames\nusing Measurements\nusing Measurements: value, uncertainty\nusing CSV\n\nThe Simulation\nI chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.\n\n# Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/\nV = (85 ± 5)u\"inch^3\"\nP0 = (4200.0 ± 300)u\"psi\"\nWtank = (2.3 ± 0.2)u\"lb\"\nPmax = (250 ± 50)u\"psi\" # Max Pressure that can come out the nozzle\n\nThe nozzle diameter was changed until the air prop system had a burn time similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.\n\n# Params\nd_nozzle = ((1 // 18) ± 0.001)u\"inch\"\na_nozzle = (pi / 4) * d_nozzle^2\n\nThese are just universal values for what a typical day would look like during the summer in Northern Arizona. (Çengel and Boles 2015)\n\n# Universal Stuff\nP_amb = (1 ± 0.2)u\"atm\"\nγ = 1.4 ± 0.05\nR = 287.05u\"J/(kg * K)\"\nT = (300 ± 20)u\"K\"\n\nThe actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate \\(\\dot{m}\\), which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by \\(\\dot{m}\\) and recalculate pressure using the new mass then repeat the whole process.\nThe bulk of the equations in the simulation came from (Çengel and Boles 2015), while the Thrust and \\(v_e\\) equations came from (Sutton and Biblarz 2001, eq: 2-14).\n\\[ T = \\dot{m} \\cdot v_\\text{Exit} + A_\\text{Nozzle} \\cdot (P - P_\\text{Ambient}) \\]\nThe initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and burn time vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.\n\ndf = let\nt = 0.0u\"s\"\nP = P0 |> u\"Pa\"\nM = V * (P / (R * T)) |> u\"kg\"\nts = 1u\"ms\"\ndf = DataFrame(Thrust=(0 ± 0)u\"N\", Pressure=P0, Time=0.0u\"s\", Mass=M)\n while M > 0.005u\"kg\"\n # Calculate what is leaving tank\n P = minimum([P, Pmax])\n ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |> u\"m/s\"\n ρ = P / (R * T) |> u\"kg/m^3\"\n ṁ = ρ * a_nozzle * ve |> u\"kg/s\"\n \n Thrust = ṁ * ve + a_nozzle * (P - P_amb) |> u\"N\"\n \n # Calculate what is still in the tank\n M = M - ṁ * ts |> u\"kg\"\n P = (M * R * T) / V |> u\"Pa\"\n t = t + ts\n \n df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M)\n append!(df, df_step)\n end\n df\nend\n\nAnalysis\nBelow in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.\n\n\nShow code\n\nthrust_values = df.Thrust .|> ustrip .|> value;\nthrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;\n\nair = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|> u\"s\" .|> ustrip);\n\n\nplot(df.Time .|> ustrip, thrust_values, \n title=\"Thrust Over Time\", \n ribbon=(thrust_uncertainties, thrust_uncertainties), \n fillalpha=.2,label=\"Thrust\",\n xlabel=\"Time (s)\", \n ylabel=\"Thrust (N)\",\n )\n\n\nFigure 1: Air Proplsion Simulation\n\n\n\nIn Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.\n\n\nShow code\n\nf10 = CSV.read(\"AeroTech_F10.csv\", DataFrame);\nf15 = CSV.read(\"Estes_F15.csv\", DataFrame);\ng8 = CSV.read(\"AeroTech_G8ST.csv\", DataFrame);\n\n\nplot(air.Time, air.Thrust, label=\"Air Propulsion\", legend=:topleft);\n\nfor (d, l) in [(f10, \"F10\"), (f15, \"F15\"), (g8, \"G8ST\")]\n plot!(d[!,\"Time (s)\"], d[!, \"Thrust (N)\"], label=l);\nend\n\ntitle!(\"Propulsion Comparison\");\nxlabel!(\"Time (s)\");\nylabel!(\"Thrust (N)\")\n\n\nFigure 2: Rocket Motor Data: (Coker, n.d.)\n\n\n\nIn the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.\nFuture Work\nAfter determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.\n\n\n\nCoker, John. n.d. “Rocket Motor Data.” https://www.thrustcurve.org/.\n\n\nÇengel, Yunus A., and Michael A. Boles. 2015. Thermodynamics: An Engineering Approach. Eighth edition. New York: McGraw-Hill Education.\n\n\nSutton, George P., and Oscar Biblarz. 2001. Rocket Propulsion Elements. 7th ed. New York: John Wiley & Sons.\n\n\n\n\n", "preview": "posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-7-J1.png", - "last_modified": "2021-05-03T21:36:23-07:00", + "last_modified": "2021-05-03T21:53:15-07:00", "input_file": "air-propulsion-simulation.utf8.md", - "preview_width": 1200, - "preview_height": 800 + "preview_width": 600, + "preview_height": 400 } ] diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 899b56f..78fea4a 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -14,6 +14,6 @@ https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation/ - 2021-05-03T21:36:23-07:00 + 2021-05-03T21:53:15-07:00 From 66efb062d4e56c619e773610a577b3640d06f0ed Mon Sep 17 00:00:00 2001 From: Anson Biggs Date: Fri, 7 May 2021 09:54:03 -0700 Subject: [PATCH 4/4] finished eclipse det --- .../citations.bib | 32 ++--- .../iss-eclipse-determination.Rmd | 42 +++---- .../iss-eclipse-determination.html | 43 +++---- .../figure-html5/sunlight-plot-J1.png | Bin 0 -> 22194 bytes docs/index.xml | 119 +----------------- .../citations.bib | 32 ++--- .../index.html | 43 +++---- .../figure-html5/sunlight-plot-J1.png | Bin 0 -> 22194 bytes docs/posts/posts.json | 8 +- docs/search.json | 4 +- docs/sitemap.xml | 4 +- 11 files changed, 96 insertions(+), 231 deletions(-) create mode 100644 _posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination_files/figure-html5/sunlight-plot-J1.png create mode 100644 docs/posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination_files/figure-html5/sunlight-plot-J1.png diff --git a/_posts/2021-04-14-iss-eclipse-determination/citations.bib b/_posts/2021-04-14-iss-eclipse-determination/citations.bib index db9cc12..6578764 100644 --- a/_posts/2021-04-14-iss-eclipse-determination/citations.bib +++ b/_posts/2021-04-14-iss-eclipse-determination/citations.bib @@ -1,24 +1,3 @@ - -@book{shackelford_introduction_2015, - address = {Boston}, - edition = {Eighth edition}, - title = {Introduction to materials science for engineers}, - isbn = {9780133826654}, - publisher = {Pearson}, - author = {Shackelford, James F.}, - year = {2015}, - keywords = {Materials}, -} - -@book{curtis_orbital_2021, - title = {Orbital mechanics for engineering students}, - isbn = {9780128240250 9780323853453 9780081021330}, - language = {English}, - author = {Curtis, Howard D}, - year = {2021}, - note = {OCLC: 1235349370}, -} - @misc{ariss, title = {{ARISS} {TLE}}, shorttitle = {{ARISS}}, @@ -27,3 +6,14 @@ journal = {Amateur Radio on the International Space Station}, note = {publisher: ARISS}, } + +@book{vallado, + address = {Dordrecht}, + title = {Fundamentals of {Astrodynamics} and {Applications}, 2nd. ed.}, + isbn = {0-07-066829-9}, + publisher = {Microcosm, Inc}, + author = {Vallado, David A.}, + editor = {Larson, Wiley}, + collaborator = {McClain, Wayne}, + year = {1997}, +} \ No newline at end of file diff --git a/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.Rmd b/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.Rmd index ff56c80..b72c549 100644 --- a/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.Rmd +++ b/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.Rmd @@ -6,7 +6,6 @@ draft: false author: - name: Anson Biggs url: https://ansonbiggs.com -repository_url: https://gitlab.com/lander-team/air-prop-simulation date: 05-01-2021 fig_width: 6 fig_align: "center" @@ -21,7 +20,7 @@ creative_commons: CC BY preview: preview.png --- -Determining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space with no solar radiation to power the solar panels and keep the spacecraft from freezing. +Determining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space where it will receive no solar radiation to power the solar panels and keep the spacecraft from freezing. ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE, results = 'hide') @@ -33,15 +32,15 @@ julia_setup(JULIA_HOME = "/opt/julia-1.6.0/bin/") ![Geometry of an Eclipse](geometry.svg) -The above image is a simple representation of what an eclipse is. You'll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn't much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra. +The above image is a simple representation of what an eclipse is. First, you'll notice the Umbra is complete darkness, then the Penumbra, which is a shadow of varying darkness, and then the rest of the orbit is in full sunlight. For this example, I will be using the ISS, which has a very low orbit, so the Penumbra isn't much of a problem. However, you can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra. ![Body Radius's and Position Vectors](vectors_radiuss.svg) -Here is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius's that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS's orbit. Rsun and Rbody are the radius's of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate [Ephemerides](https://ssd.jpl.nasa.gov/?ephemerides) in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft. +Here is a more detailed view of the eclipse that will make it easier to explain what is going on. There are 2 Position vectors, and 2 radius that need to be known for simple eclipse determination. More advanced cases where the atmosphere of the body your orbiting can significantly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun. However, we will keep it simple for this example since they have minimal effect on the ISS’s orbit. Rsun and Rbody are the radius of the Sun and Body (In this case Earth), respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination it is important to calculate the ephemeris at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate [Ephemerides](https://ssd.jpl.nasa.gov/?ephemerides) in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbited, to the center of our spacecraft. ## The Code -```{julia, code_folding=TRUE} +```{julia imports, code_folding=TRUE} using Unitful using LinearAlgebra using SatelliteToolbox @@ -50,9 +49,9 @@ using Colors theme(:ggplot2) ``` -In order to get the orbit for the ISS I used a [Two-Line Element](https://en.wikipedia.org/wiki/Two-line_element_set) which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible [@ariss]. The Julia Package [SatelliteToolbox.jl](https://github.com/JuliaSpace/SatelliteToolbox.jl) makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the `tle` string macro like below and now we have access to the information to start making our ISS orbit. +To get the orbit for the ISS, I used a [Two-Line Element](https://en.wikipedia.org/wiki/Two-line_element_set) which is a data format for explaining orbits. The US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible [@ariss]. The Julia Package [SatelliteToolbox.jl](https://github.com/JuliaSpace/SatelliteToolbox.jl) makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the `tle` string macro like below, we now have access to the information to start making our ISS orbit. -```{julia, results='show'} +```{julia ISS, results='show'} ISS = tle""" ISS (ZARYA) 1 25544U 98067A 21103.84943184 .00000176 00000-0 11381-4 0 9990 @@ -60,23 +59,21 @@ ISS (ZARYA) """ ``` -Now that we have the TLE we can pass that into SatelliteToolbox's orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector. +Now that we have the TLE, we can pass that into SatelliteToolbox's orbit propagator. Before propagating the orbit, we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day, so using that, we can calculate the amount of time required for one orbit, which is all that we're worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector. -```{juliam result='show'} +```{julia mean-motion, result='show'} ISS[1].n ``` -```{julia} +```{julia orbit-propagation} orbit = init_orbit_propagator(Val(:twobody), ISS[1]); time = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day. o, r, v = propagate!(orbit, time); ``` -Now we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math. +We just need to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of trigonometry and vector math that I won't bore anyone with. However, using the diagrams above and following the code in the sunlight function, you should follow what's happening. For a rigorous discussion, check out [@vallado]. -`add more discussion about the math` - -```{julia} +```{julia sunlight-function} function sunlight(Rbody, r_sun_body, r_body_sc) Rsun = 695_700u"km" @@ -110,9 +107,9 @@ S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u" ## Plotting the Results -The `sunlight` function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant. +The `sunlight` function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spent in the penumbra is almost insignificant. -```{julia, code_folding=TRUE, results='show',layout="l-body-outset",fig.cap= "ISS Sunlight", preview=TRUE } +```{julia sunlight-plot, code_folding=TRUE, results='show',layout="l-body-outset",fig.cap= "ISS Sunlight", preview=TRUE } # Get fancy with the line color. light_range = range(colorant"black", stop = colorant"orange", length = 101); light_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S]; @@ -130,21 +127,24 @@ ylabel!("Sunlight (%)"); title!("ISS Sunlight Over a Day") ``` -Looking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region. +Looking at the plot, the vertical transition from 0% to 100% makes it pretty clear that the time in the penumbra is limited. Still, almost counterintuitively, it also looks like the ISS gets more sunlight than it does darkness. So, using the raw sunlight data, we can calculate precisely how much time is spent in each region. Time in Sun: -```{julia, results='show'} + +```{julia sun-time, results='show'} sun = length(S[S.==1])/length(S) * 100 ``` Time in Darkness: -```{julia, results='show'} + +```{julia dark-time, results='show'} umbra = length(S[S.==0])/length(S) * 100 ``` Time in Penumbra: -```{julia, results='show'} + +```{julia penum-time, results='show'} penumbra = 100 - umbra - sun ``` -The ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes. +This means that even with the ISS's low orbit, it still gets sunlight ~62% of the time and spends almost no time in the penumbra. This would vary a few percent depending on the time of year, but in a circular orbit like the ISS, the amount of sunlight would remain pretty constant. There are other orbits like a polar orbit, lunar orbit, or highly elliptic earth orbits that can have their time in the sunlight vary widely by the time of year. diff --git a/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.html b/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.html index 7f92793..39d14cf 100644 --- a/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.html +++ b/_posts/2021-04-14-iss-eclipse-determination/iss-eclipse-determination.html @@ -111,15 +111,16 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */ + @@ -1485,16 +1486,16 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */
-

Determining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space with no solar radiation to power the solar panels and keep the spacecraft from freezing.

+

Determining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space where it will receive no solar radiation to power the solar panels and keep the spacecraft from freezing.

What is an Eclipse

Geometry of an Eclipse
-

The above image is a simple representation of what an eclipse is. You’ll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn’t much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.

+

The above image is a simple representation of what an eclipse is. First, you’ll notice the Umbra is complete darkness, then the Penumbra, which is a shadow of varying darkness, and then the rest of the orbit is in full sunlight. For this example, I will be using the ISS, which has a very low orbit, so the Penumbra isn’t much of a problem. However, you can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.

Body Radius’s and Position Vectors
-

Here is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius’s that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS’s orbit. Rsun and Rbody are the radius’s of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft.

+

Here is a more detailed view of the eclipse that will make it easier to explain what is going on. There are 2 Position vectors, and 2 radius that need to be known for simple eclipse determination. More advanced cases where the atmosphere of the body your orbiting can significantly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun. However, we will keep it simple for this example since they have minimal effect on the ISS’s orbit. Rsun and Rbody are the radius of the Sun and Body (In this case Earth), respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination it is important to calculate the ephemeris at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbited, to the center of our spacecraft.

The Code

@@ -1509,7 +1510,7 @@ Show code theme(:ggplot2)
-

In order to get the orbit for the ISS I used a Two-Line Element which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below and now we have access to the information to start making our ISS orbit.

+

To get the orbit for the ISS, I used a Two-Line Element which is a data format for explaining orbits. The US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below, we now have access to the information to start making our ISS orbit.

ISS = tle"""
 ISS (ZARYA)
@@ -1519,17 +1520,16 @@ Show code
 
1-element Vector{TLE}:
  TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)
-

Now that we have the TLE we can pass that into SatelliteToolbox’s orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.

+

Now that we have the TLE, we can pass that into SatelliteToolbox’s orbit propagator. Before propagating the orbit, we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day, so using that, we can calculate the amount of time required for one orbit, which is all that we’re worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.

-
ISS[1].n
+
ISS[1].n
orbit = init_orbit_propagator(Val(:twobody), ISS[1]);
 time = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.
 o, r, v = propagate!(orbit, time);
-

Now we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math.

-

add more discussion about the math

+

We just need to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of trigonometry and vector math that I won’t bore anyone with. However, using the diagrams above and following the code in the sunlight function, you should follow what’s happening. For a rigorous discussion, check out (Vallado 1997).

function sunlight(Rbody, r_sun_body, r_body_sc)
     Rsun = 695_700u"km"
@@ -1560,7 +1560,7 @@ Show code
 
S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u"m");

Plotting the Results

-

The sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant.

+

The sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spent in the penumbra is almost insignificant.

@@ -1582,35 +1582,38 @@ Show code ylabel!("Sunlight (%)"); title!("ISS Sunlight Over a Day")
-
-ISS Sunlight +
+ISS Sunlight

Figure 1: ISS Sunlight

-

Looking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region.

-Time in Sun: +

Looking at the plot, the vertical transition from 0% to 100% makes it pretty clear that the time in the penumbra is limited. Still, almost counterintuitively, it also looks like the ISS gets more sunlight than it does darkness. So, using the raw sunlight data, we can calculate precisely how much time is spent in each region.

+

Time in Sun:

sun = length(S[S.==1])/length(S) * 100
62.03323593209401
-Time in Darkness: +

Time in Darkness:

umbra = length(S[S.==0])/length(S) * 100
37.64408511553699
-Time in Penumbra: +

Time in Penumbra:

penumbra = 100 - umbra - sun
0.322678952369003
-

The ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes.

+

This means that even with the ISS’s low orbit, it still gets sunlight ~62% of the time and spends almost no time in the penumbra. This would vary a few percent depending on the time of year, but in a circular orbit like the ISS, the amount of sunlight would remain pretty constant. There are other orbits like a polar orbit, lunar orbit, or highly elliptic earth orbits that can have their time in the sunlight vary widely by the time of year.

“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/.
+
+Vallado, David A. 1997. Fundamentals of Astrodynamics and Applications, 2nd. Ed. Edited by Wiley Larson. Dordrecht: Microcosm, Inc. +
@@ -1626,10 +1629,8 @@ Time in Penumbra:

References

-

Corrections

-

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

-

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://gitlab.com/lander-team/air-prop-simulation, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

+

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

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The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just <em>napkin math</em> to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.</p> -<pre class="julia"><code>using Plots -theme(:ggplot2); # In true R spirit - -using Unitful -using DataFrames -using Measurements -using Measurements: value, uncertainty -using CSV</code></pre> -<h2 id="the-simulation">The Simulation</h2> -<p>I chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.</p> -<pre class="julia"><code># Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/ -V = (85 ± 5)u&quot;inch^3&quot; -P0 = (4200.0 ± 300)u&quot;psi&quot; -Wtank = (2.3 ± 0.2)u&quot;lb&quot; -Pmax = (250 ± 50)u&quot;psi&quot; # Max Pressure that can come out the nozzle</code></pre> -<p>The nozzle diameter was changed until the air prop system had a <em>burn time</em> similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.</p> -<pre class="julia"><code># Params -d_nozzle = ((1 // 18) ± 0.001)u&quot;inch&quot; -a_nozzle = (pi / 4) * d_nozzle^2</code></pre> -<p>These are just universal values for what a typical day would look like during the summer in Northern Arizona. <span class="citation">(Çengel and Boles 2015)</span></p> -<pre class="julia"><code># Universal Stuff -P_amb = (1 ± 0.2)u&quot;atm&quot; -γ = 1.4 ± 0.05 -R = 287.05u&quot;J/(kg * K)&quot; -T = (300 ± 20)u&quot;K&quot;</code></pre> -<p>The actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate <span class="math inline">\(\dot{m}\)</span>, which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by <span class="math inline">\(\dot{m}\)</span> and recalculate pressure using the new mass then repeat the whole process.</p> -<p>The bulk of the equations in the simulation came from <span class="citation">(Çengel and Boles 2015)</span>, while the Thrust and <span class="math inline">\(v_e\)</span> equations came from <span class="citation">(Sutton and Biblarz 2001, eq: 2-14)</span>.</p> -<p><span class="math display">\[ T = \dot{m} \cdot v_\text{Exit} + A_\text{Nozzle} \cdot (P - P_\text{Ambient}) \]</span></p> -<p>The initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and <em>burn time</em> vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.</p> -<pre class="julia"><code>df = let -t = 0.0u&quot;s&quot; -P = P0 |&gt; u&quot;Pa&quot; -M = V * (P / (R * T)) |&gt; u&quot;kg&quot; -ts = 1u&quot;ms&quot; -df = DataFrame(Thrust=(0 ± 0)u&quot;N&quot;, Pressure=P0, Time=0.0u&quot;s&quot;, Mass=M) - while M &gt; 0.005u&quot;kg&quot; - # Calculate what is leaving tank - P = minimum([P, Pmax]) - ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |&gt; u&quot;m/s&quot; - ρ = P / (R * T) |&gt; u&quot;kg/m^3&quot; - ṁ = ρ * a_nozzle * ve |&gt; u&quot;kg/s&quot; - - Thrust = ṁ * ve + a_nozzle * (P - P_amb) |&gt; u&quot;N&quot; - - # Calculate what is still in the tank - M = M - ṁ * ts |&gt; u&quot;kg&quot; - P = (M * R * T) / V |&gt; u&quot;Pa&quot; - t = t + ts - - df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M) - append!(df, df_step) - end - df -end</code></pre> -<h2 id="analysis">Analysis</h2> -<p>Below in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.</p> -<pre class="julia"><code> -thrust_values = df.Thrust .|&gt; ustrip .|&gt; value; -thrust_uncertainties = df.Thrust .|&gt; ustrip .|&gt; uncertainty; - -air = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|&gt; u&quot;s&quot; .|&gt; ustrip); - - -plot(df.Time .|&gt; ustrip, thrust_values, - title=&quot;Thrust Over Time&quot;, - ribbon=(thrust_uncertainties, thrust_uncertainties), - fillalpha=.2,label=&quot;Thrust&quot;, - xlabel=&quot;Time (s)&quot;, - ylabel=&quot;Thrust (N)&quot;, - )</code></pre> -<div class="figure"> -<img src="file622ef5a388f_files/figure-html/unnamed-chunk-6-J1.png" alt="Air Proplsion Simulation" width="300" /> -<p class="caption"> -(#fig:unnamed-chunk-6)Air Proplsion Simulation -</p> -</div> -<p>In Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.</p> -<pre class="julia"><code> -f10 = CSV.read(&quot;AeroTech_F10.csv&quot;, DataFrame); -f15 = CSV.read(&quot;Estes_F15.csv&quot;, DataFrame); -g8 = CSV.read(&quot;AeroTech_G8ST.csv&quot;, DataFrame); - - -plot(air.Time, air.Thrust, label=&quot;Air Propulsion&quot;, legend=:topleft); - -for (d, l) in [(f10, &quot;F10&quot;), (f15, &quot;F15&quot;), (g8, &quot;G8ST&quot;)] - plot!(d[!,&quot;Time (s)&quot;], d[!, &quot;Thrust (N)&quot;], label=l); -end - -title!(&quot;Propulsion Comparison&quot;); -xlabel!(&quot;Time (s)&quot;); -ylabel!(&quot;Thrust (N)&quot;)</code></pre> -<div class="figure"> -<img src="file622ef5a388f_files/figure-html/unnamed-chunk-7-J1.png" alt="Rocket Motor Data: [@thrustcurve]" width="300" data-distill-preview=1 /> -<p class="caption"> -(#fig:unnamed-chunk-7)Rocket Motor Data: <span class="citation">(Coker, n.d.)</span> -</p> -</div> -<p>In the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.</p> -<h2 id="future-work">Future Work</h2> -<p>After determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.</p> -<pre class="r distill-force-highlighting-css"><code></code></pre> -<div id="refs" class="references csl-bib-body hanging-indent"> -<div id="ref-thrustcurve" class="csl-entry"> -Coker, John. n.d. <span>“Rocket <span>Motor</span> <span>Data</span>.”</span> <a href="https://www.thrustcurve.org/">https://www.thrustcurve.org/</a>. -</div> -<div id="ref-cengel_thermodynamics" class="csl-entry"> -Çengel, Yunus A., and Michael A. Boles. 2015. <em>Thermodynamics: An Engineering Approach</em>. Eighth edition. New York: McGraw-Hill Education. -</div> -<div id="ref-sutton_rocket_2001" class="csl-entry"> -Sutton, George P., and Oscar Biblarz. 2001. <em>Rocket Propulsion Elements</em>. 7th ed. New York: John Wiley &amp; Sons. -</div> -</div> - dbf2ace5c1414ee7c72e89cac1535434 + Simulating the performance of an air propulsion system as an alternative to solid rocket motors. Julia Capstone https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation diff --git a/docs/posts/2021-04-14-iss-eclipse-determination/citations.bib b/docs/posts/2021-04-14-iss-eclipse-determination/citations.bib index db9cc12..6578764 100644 --- a/docs/posts/2021-04-14-iss-eclipse-determination/citations.bib +++ b/docs/posts/2021-04-14-iss-eclipse-determination/citations.bib @@ -1,24 +1,3 @@ - -@book{shackelford_introduction_2015, - address = {Boston}, - edition = {Eighth edition}, - title = {Introduction to materials science for engineers}, - isbn = {9780133826654}, - publisher = {Pearson}, - author = {Shackelford, James F.}, - year = {2015}, - keywords = {Materials}, -} - -@book{curtis_orbital_2021, - title = {Orbital mechanics for engineering students}, - isbn = {9780128240250 9780323853453 9780081021330}, - language = {English}, - author = {Curtis, Howard D}, - year = {2021}, - note = {OCLC: 1235349370}, -} - @misc{ariss, title = {{ARISS} {TLE}}, shorttitle = {{ARISS}}, @@ -27,3 +6,14 @@ journal = {Amateur Radio on the International Space Station}, note = {publisher: ARISS}, } + +@book{vallado, + address = {Dordrecht}, + title = {Fundamentals of {Astrodynamics} and {Applications}, 2nd. ed.}, + isbn = {0-07-066829-9}, + publisher = {Microcosm, Inc}, + author = {Vallado, David A.}, + editor = {Larson, Wiley}, + collaborator = {McClain, Wayne}, + year = {1997}, +} \ No newline at end of file diff --git a/docs/posts/2021-04-14-iss-eclipse-determination/index.html b/docs/posts/2021-04-14-iss-eclipse-determination/index.html index adbd0ee..2a478ce 100644 --- a/docs/posts/2021-04-14-iss-eclipse-determination/index.html +++ b/docs/posts/2021-04-14-iss-eclipse-determination/index.html @@ -128,15 +128,16 @@ code span.wa { color: #5e5e5e; font-style: italic; } /* Warning */ + @@ -2127,16 +2128,16 @@ document.addEventListener('DOMContentLoaded', function() {

-

Determining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space with no solar radiation to power the solar panels and keep the spacecraft from freezing.

+

Determining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space where it will receive no solar radiation to power the solar panels and keep the spacecraft from freezing.

What is an Eclipse

Geometry of an Eclipse
-

The above image is a simple representation of what an eclipse is. You’ll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn’t much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.

+

The above image is a simple representation of what an eclipse is. First, you’ll notice the Umbra is complete darkness, then the Penumbra, which is a shadow of varying darkness, and then the rest of the orbit is in full sunlight. For this example, I will be using the ISS, which has a very low orbit, so the Penumbra isn’t much of a problem. However, you can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.

Body Radius’s and Position Vectors
-

Here is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius’s that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS’s orbit. Rsun and Rbody are the radius’s of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft.

+

Here is a more detailed view of the eclipse that will make it easier to explain what is going on. There are 2 Position vectors, and 2 radius that need to be known for simple eclipse determination. More advanced cases where the atmosphere of the body your orbiting can significantly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun. However, we will keep it simple for this example since they have minimal effect on the ISS’s orbit. Rsun and Rbody are the radius of the Sun and Body (In this case Earth), respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination it is important to calculate the ephemeris at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbited, to the center of our spacecraft.

The Code

@@ -2151,7 +2152,7 @@ Show code theme(:ggplot2)
-

In order to get the orbit for the ISS I used a Two-Line Element which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below and now we have access to the information to start making our ISS orbit.

+

To get the orbit for the ISS, I used a Two-Line Element which is a data format for explaining orbits. The US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below, we now have access to the information to start making our ISS orbit.

ISS = tle"""
 ISS (ZARYA)
@@ -2161,17 +2162,16 @@ Show code
 
1-element Vector{TLE}:
  TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)
-

Now that we have the TLE we can pass that into SatelliteToolbox’s orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.

+

Now that we have the TLE, we can pass that into SatelliteToolbox’s orbit propagator. Before propagating the orbit, we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day, so using that, we can calculate the amount of time required for one orbit, which is all that we’re worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.

-
ISS[1].n
+
ISS[1].n
orbit = init_orbit_propagator(Val(:twobody), ISS[1]);
 time = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.
 o, r, v = propagate!(orbit, time);
-

Now we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math.

-

add more discussion about the math

+

We just need to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of trigonometry and vector math that I won’t bore anyone with. However, using the diagrams above and following the code in the sunlight function, you should follow what’s happening. For a rigorous discussion, check out (Vallado 1997).

function sunlight(Rbody, r_sun_body, r_body_sc)
     Rsun = 695_700u"km"
@@ -2202,7 +2202,7 @@ Show code
 
S = r .|> R -> sunlight(6371u"km", [0.5370, 1.2606, 0.5466] .* 1e8u"km", R .* u"m");

Plotting the Results

-

The sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant.

+

The sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spent in the penumbra is almost insignificant.

@@ -2224,35 +2224,38 @@ Show code ylabel!("Sunlight (%)"); title!("ISS Sunlight Over a Day")
-
-ISS Sunlight +
+ISS Sunlight

Figure 1: ISS Sunlight

-

Looking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region.

-Time in Sun: +

Looking at the plot, the vertical transition from 0% to 100% makes it pretty clear that the time in the penumbra is limited. Still, almost counterintuitively, it also looks like the ISS gets more sunlight than it does darkness. So, using the raw sunlight data, we can calculate precisely how much time is spent in each region.

+

Time in Sun:

sun = length(S[S.==1])/length(S) * 100
62.03323593209401
-Time in Darkness: +

Time in Darkness:

umbra = length(S[S.==0])/length(S) * 100
37.64408511553699
-Time in Penumbra: +

Time in Penumbra:

penumbra = 100 - umbra - sun
0.322678952369003
-

The ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes.

+

This means that even with the ISS’s low orbit, it still gets sunlight ~62% of the time and spends almost no time in the penumbra. This would vary a few percent depending on the time of year, but in a circular orbit like the ISS, the amount of sunlight would remain pretty constant. There are other orbits like a polar orbit, lunar orbit, or highly elliptic earth orbits that can have their time in the sunlight vary widely by the time of year.

“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/.
+
+Vallado, David A. 1997. Fundamentals of Astrodynamics and Applications, 2nd. Ed. Edited by Wiley Larson. Dordrecht: Microcosm, Inc. +
@@ -2281,10 +2284,8 @@ Time in Penumbra:

References

-

Corrections

-

If you see mistakes or want to suggest changes, please create an issue on the source repository.

Reuse

-

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. Source code is available at https://gitlab.com/lander-team/air-prop-simulation, unless otherwise noted. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

+

Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".

Citation

For attribution, please cite this work as

Biggs (2021, May 1). Anson's Projects: ISS Eclipse Determination. Retrieved from https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination/
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Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space with no solar radiation to power the solar panels and keep the spacecraft from freezing.\nWhat is an Eclipse\nGeometry of an EclipseThe above image is a simple representation of what an eclipse is. You’ll notice there is the Umbra which is complete darkness, then the Penumbra which is a shadow of varying darkness, and then the rest of the orbit is in complete sunlight. For this example I will be using the ISS which has a very low orbit so the Penumbra isn’t much of a problem. You can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.\nBody Radius’s and Position VectorsHere is a more detailed view of the eclipse that will make it easier to explain the code. There are 2 Position vectors and 2 radius’s that need to be known for simple eclipse determination. There are more advanced cases where the atmosphere of the body your orbiting can greatly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun, but for this example we will keep it simple since those have very little affect for the ISS’s orbit. Rsun and Rbody are the radius’s of the Sun and Body (In this case Earth) respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination its important to calculate this at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbitted, to the center of our spacecraft.\nThe Code\n\n\nShow code\nusing Unitful\nusing LinearAlgebra\nusing SatelliteToolbox\nusing Plots\nusing Colors\ntheme(:ggplot2)\n\nIn order to get the orbit for the ISS I used a Two-Line Element which is a data format for explaining orbits. the US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below and now we have access to the information to start making our ISS orbit.\n\nISS = tle\"\"\"\nISS (ZARYA)\n1 25544U 98067A 21103.84943184 .00000176 00000-0 11381-4 0 9990\n2 25544 51.6434 300.9481 0002858 223.8443 263.8789 15.48881793278621\n\"\"\"\n1-element Vector{TLE}:\n TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)\n\nNow that we have the TLE we can pass that into SatelliteToolbox’s orbit propagator. Before we can propagate the orbit we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day so using that we can calculate the amount of time required for one orbit which is all that were worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.\n\nISS[1].n\n\n\norbit = init_orbit_propagator(Val(:twobody), ISS[1]);\ntime = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.\no, r, v = propagate!(orbit, time);\n\nNow we just need way to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of pretty basic trigonometry and vector math.\nadd more discussion about the math\n\nfunction sunlight(Rbody, r_sun_body, r_body_sc)\n Rsun = 695_700u\"km\"\n \n hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)\n \n θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))\n\n θu = atan(Rbody / hu)\n du = hu * sin(θu) / sin(θe + θu)\n\n θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))\n dp = Rbody * sin(θp) / cos(θe - θp)\n\n S = 1\n if (θe < π / 2) && (norm(r_body_sc) < du)\n S = 0\n end\n if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))\n S = (norm(r_body_sc .|> u\"km\") - du) / (dp - du) |> ustrip\n end\n\n return S\nend\n\nThen we can pass all the values we’ve gathered into the function we just made.\n\nS = r .|> R -> sunlight(6371u\"km\", [0.5370, 1.2606, 0.5466] .* 1e8u\"km\", R .* u\"m\");\n\nPlotting the Results\nThe sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spend in the penumbra is almost insignificant.\n\n\nShow code\n# Get fancy with the line color. \nlight_range = range(colorant\"black\", stop = colorant\"orange\", length = 101);\nlight_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];\n\nplot(\n LinRange(0, 24, length(S)),\n S .* 100,\n linewidth = 5,\n legend = false,\n color = light_colors,\n);\n\nxlabel!(\"Time (hr)\");\nylabel!(\"Sunlight (%)\");\ntitle!(\"ISS Sunlight Over a Day\")\n\n\nFigure 1: ISS Sunlight\n\n\n\nLooking at the plot its pretty easy to see by the vertical transition from 0% to 100% that the time in the penumbra is limited, but almost counterintutively it also looks like the ISS gets more sunlight than it does darkness. Using the raw sunlight data we can actually calculate almost exactly how much time is spent in each region.\nTime in Sun:\n\nsun = length(S[S.==1])/length(S) * 100\n62.03323593209401\n\nTime in Darkness:\n\numbra = length(S[S.==0])/length(S) * 100\n37.64408511553699\n\nTime in Penumbra:\n\npenumbra = 100 - umbra - sun\n0.322678952369003\n\nThe ISS spends about 62% of its time in the sun, this is because if you go back and reference the diagram at the beginning of this post you can see that the umbra is actually a cone. This is mainly due to the fact that the Sun is massive compared to the Earth, but this effect is also stronger with orbits of higher altitudes.\n\n\n\n“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/.\n\n\n\n\n", + "contents": "\nDetermining the eclipses a satellite will encounter is a major driving factor when designing a mission in space. Thermal and power budgets have to be made with the fact that a satellite will periodically be in the complete darkness of space where it will receive no solar radiation to power the solar panels and keep the spacecraft from freezing.\nWhat is an Eclipse\nGeometry of an EclipseThe above image is a simple representation of what an eclipse is. First, you’ll notice the Umbra is complete darkness, then the Penumbra, which is a shadow of varying darkness, and then the rest of the orbit is in full sunlight. For this example, I will be using the ISS, which has a very low orbit, so the Penumbra isn’t much of a problem. However, you can tell by looking at the diagram that higher altitude orbits would spend more time in the Penumbra.\nBody Radius’s and Position VectorsHere is a more detailed view of the eclipse that will make it easier to explain what is going on. There are 2 Position vectors, and 2 radius that need to be known for simple eclipse determination. More advanced cases where the atmosphere of the body your orbiting can significantly affect the Umbra and Penumbra, and other bodies could also potentially block the Sun. However, we will keep it simple for this example since they have minimal effect on the ISS’s orbit. Rsun and Rbody are the radius of the Sun and Body (In this case Earth), respectively. r_sun_body is a vector from the center of the Sun to the center of the target body. For this example I will only be using one vector, but for more rigorous eclipse determination it is important to calculate the ephemeris at least once a day since it does significantly change over the course of a year. The reason that I am ignoring it at the moment is because there is currently no good way to calculate Ephemerides in Julia but the package is being worked on so I may revisit this and do a more rigorous analysis in the future. r_body_sc is a position vector from the center of the body being orbited, to the center of our spacecraft.\nThe Code\n\n\nShow code\nusing Unitful\nusing LinearAlgebra\nusing SatelliteToolbox\nusing Plots\nusing Colors\ntheme(:ggplot2)\n\nTo get the orbit for the ISS, I used a Two-Line Element which is a data format for explaining orbits. The US Joint Space Operations Center makes these widely available, but https://live.ariss.org/tle/ makes the TLE for the ISS way more accessible (“ARISS TLE,” n.d.). The Julia Package SatelliteToolbox.jl makes it super easy to turn a TLE into an orbit that can be propagated. Simply putting the TLE in a string and using the tle string macro like below, we now have access to the information to start making our ISS orbit.\n\nISS = tle\"\"\"\nISS (ZARYA)\n1 25544U 98067A 21103.84943184 .00000176 00000-0 11381-4 0 9990\n2 25544 51.6434 300.9481 0002858 223.8443 263.8789 15.48881793278621\n\"\"\"\n1-element Vector{TLE}:\n TLE: ISS (ZARYA) (Epoch = 2021-04-13T20:23:10.911)\n\nNow that we have the TLE, we can pass that into SatelliteToolbox’s orbit propagator. Before propagating the orbit, we need to have a range of time steps to pass into the propagator. The TLE gives the mean motion, n, which is the revolutions per day, so using that, we can calculate the amount of time required for one orbit, which is all that we’re worried about for this analysis. The propagator returns a tuple containing the Orbital elements, a position vector with units meters, and a velocity vector with units meters per second. For this analysis were only worried about the position vector.\n\nISS[1].n\n\n\norbit = init_orbit_propagator(Val(:twobody), ISS[1]);\ntime = 0:0.1:((24 / ISS[1].n) .* 60 * 60); # ISS[1].n gives the mean motion, or orbits per day.\no, r, v = propagate!(orbit, time);\n\nWe just need to use the radii and vectors discussed earlier to determine if the ISS is in the penumbra or umbra. This is a lot of trigonometry and vector math that I won’t bore anyone with. However, using the diagrams above and following the code in the sunlight function, you should follow what’s happening. For a rigorous discussion, check out (Vallado 1997).\n\nfunction sunlight(Rbody, r_sun_body, r_body_sc)\n Rsun = 695_700u\"km\"\n \n hu = Rbody * norm(r_sun_body) / (Rsun - Rbody)\n \n θe = acos((r_sun_body ⋅ r_body_sc) / (norm(r_sun_body) * norm(r_body_sc)))\n\n θu = atan(Rbody / hu)\n du = hu * sin(θu) / sin(θe + θu)\n\n θp = π - atan(norm(r_sun_body) / (Rsun + Rbody))\n dp = Rbody * sin(θp) / cos(θe - θp)\n\n S = 1\n if (θe < π / 2) && (norm(r_body_sc) < du)\n S = 0\n end\n if (θe < π / 2) && ((du < norm(r_body_sc)) && (norm(r_body_sc) < dp))\n S = (norm(r_body_sc .|> u\"km\") - du) / (dp - du) |> ustrip\n end\n\n return S\nend\n\nThen we can pass all the values we’ve gathered into the function we just made.\n\nS = r .|> R -> sunlight(6371u\"km\", [0.5370, 1.2606, 0.5466] .* 1e8u\"km\", R .* u\"m\");\n\nPlotting the Results\nThe sunlight function returns values from 0 to 1, 0 being complete darkness, 1 being complete sunlight, and anything between being the fraction of light being received. Again since the ISS has a very low orbit, the amount of time spent in the penumbra is almost insignificant.\n\n\nShow code\n# Get fancy with the line color. \nlight_range = range(colorant\"black\", stop = colorant\"orange\", length = 101);\nlight_colors = [light_range[unique(round(Int, 1 + s * 100))][1] for s in S];\n\nplot(\n LinRange(0, 24, length(S)),\n S .* 100,\n linewidth = 5,\n legend = false,\n color = light_colors,\n);\n\nxlabel!(\"Time (hr)\");\nylabel!(\"Sunlight (%)\");\ntitle!(\"ISS Sunlight Over a Day\")\n\n\nFigure 1: ISS Sunlight\n\n\n\nLooking at the plot, the vertical transition from 0% to 100% makes it pretty clear that the time in the penumbra is limited. Still, almost counterintuitively, it also looks like the ISS gets more sunlight than it does darkness. So, using the raw sunlight data, we can calculate precisely how much time is spent in each region.\nTime in Sun:\n\nsun = length(S[S.==1])/length(S) * 100\n62.03323593209401\n\nTime in Darkness:\n\numbra = length(S[S.==0])/length(S) * 100\n37.64408511553699\n\nTime in Penumbra:\n\npenumbra = 100 - umbra - sun\n0.322678952369003\n\nThis means that even with the ISS’s low orbit, it still gets sunlight ~62% of the time and spends almost no time in the penumbra. This would vary a few percent depending on the time of year, but in a circular orbit like the ISS, the amount of sunlight would remain pretty constant. There are other orbits like a polar orbit, lunar orbit, or highly elliptic earth orbits that can have their time in the sunlight vary widely by the time of year.\n\n\n\n“ARISS TLE.” n.d. Amateur Radio on the International Space Station. https://live.ariss.org/tle/.\n\n\nVallado, David A. 1997. Fundamentals of Astrodynamics and Applications, 2nd. Ed. Edited by Wiley Larson. Dordrecht: Microcosm, Inc.\n\n\n\n\n", "preview": "posts/2021-04-14-iss-eclipse-determination/preview.png", - "last_modified": "2021-05-03T21:23:45-07:00", + "last_modified": "2021-05-07T09:51:55-07:00", "input_file": {}, "preview_width": 1292, "preview_height": 703 @@ -38,8 +38,8 @@ ], "contents": "\nFor Capstone my team was tasked with designing a system capable of moving mining equipment and materials around the surface of the Moon using a propulsive landing. The system had to be tested on Earth with something feasible for our team to build in 2 semesters. One of the first considerations my capstone advisor wanted was to test the feasibility of an air propulsion system instead of the obvious solution that of using solid rocket motors. This document is just napkin math to determine if the system is even feasibly and is not meant to be a rigorous study of an air propulsion system that would easily keep a capstone team busy by itself.\n\n\nShow code\nusing Plots\ntheme(:ggplot2); # In true R spirit\n\nusing Unitful\nusing DataFrames\nusing Measurements\nusing Measurements: value, uncertainty\nusing CSV\n\nThe Simulation\nI chose an off-the-shelf paintball gun tank for the pressure vessel. The primary consideration was the incredible pressure to weight ratio, and the fact that it is designed to be bumped around would be necessary for proving the safety of the system further into the project.\n\n# Tank https://www.amazon.com/Empire-Paintball-BASICS-Pressure-Compressed/dp/B07B6M48SR/\nV = (85 ± 5)u\"inch^3\"\nP0 = (4200.0 ± 300)u\"psi\"\nWtank = (2.3 ± 0.2)u\"lb\"\nPmax = (250 ± 50)u\"psi\" # Max Pressure that can come out the nozzle\n\nThe nozzle diameter was changed until the air prop system had a burn time similar to a G18ST rocket motor. The propulsion system’s total impulse is not dependant on the nozzle diameter, so this was just done to make it plot nicely with the rest of the rocket motors since, at this time, it is unknown what the optimal thrust profile is.\n\n# Params\nd_nozzle = ((1 // 18) ± 0.001)u\"inch\"\na_nozzle = (pi / 4) * d_nozzle^2\n\nThese are just universal values for what a typical day would look like during the summer in Northern Arizona. (Çengel and Boles 2015)\n\n# Universal Stuff\nP_amb = (1 ± 0.2)u\"atm\"\nγ = 1.4 ± 0.05\nR = 287.05u\"J/(kg * K)\"\nT = (300 ± 20)u\"K\"\n\nThe actual simulation is quite simple. The basic idea is that using the current pressure, you can calculate \\(\\dot{m}\\), which allows calculating the Thrust, and then you can subtract the current mass of air in the tank by \\(\\dot{m}\\) and recalculate pressure using the new mass then repeat the whole process.\nThe bulk of the equations in the simulation came from (Çengel and Boles 2015), while the Thrust and \\(v_e\\) equations came from (Sutton and Biblarz 2001, eq: 2-14).\n\\[ T = \\dot{m} \\cdot v_\\text{Exit} + A_\\text{Nozzle} \\cdot (P - P_\\text{Ambient}) \\]\nThe initial pressure difference is 4190.0 ± 300.0 psi, which is massive, so the area of the nozzle significantly alters the thrust profile. The paintball tanks come with pressure regulators, in our case, 800 psi which is still a huge number compared to atmospheric pressure. While the total impulse of the system doesn’t change with different nozzle areas, the peak thrust and burn time vary greatly. One of the benefits of doing air propulsion and the reason it was even considered so seriously is that it should be possible to change the nozzle diameter in flight, allowing thrust to be throttled, making controlled landing easier to control.\n\ndf = let\nt = 0.0u\"s\"\nP = P0 |> u\"Pa\"\nM = V * (P / (R * T)) |> u\"kg\"\nts = 1u\"ms\"\ndf = DataFrame(Thrust=(0 ± 0)u\"N\", Pressure=P0, Time=0.0u\"s\", Mass=M)\n while M > 0.005u\"kg\"\n # Calculate what is leaving tank\n P = minimum([P, Pmax])\n ve = sqrt((2 * γ / (γ - 1)) * R * T * (1 - P_amb / P)^((γ - 1) / γ)) |> u\"m/s\"\n ρ = P / (R * T) |> u\"kg/m^3\"\n ṁ = ρ * a_nozzle * ve |> u\"kg/s\"\n \n Thrust = ṁ * ve + a_nozzle * (P - P_amb) |> u\"N\"\n \n # Calculate what is still in the tank\n M = M - ṁ * ts |> u\"kg\"\n P = (M * R * T) / V |> u\"Pa\"\n t = t + ts\n \n df_step = DataFrame(Thrust=Thrust, Pressure=P, Time=t, Mass=M)\n append!(df, df_step)\n end\n df\nend\n\nAnalysis\nBelow in figure 1, the result of the simulation is plotted. Notice the massive error once the tank starts running low. This is because the calculation for pressure has a lot of very uncertain variables. This is primarily due to air being a compressible fluid, making this simulation challenging to do accurately. The thrust being below 0 N might not make intuitive sense, but it’s technically possible for the pressure to compress, leaving the inside of the rocket nozzle with a pressure that’s actually below atmospheric pressure. The effect would likely last a fraction of a second, but the point stands that this simulation is wildly inaccurate and only meant to get an idea of what an air propulsion system is capable of.\n\n\nShow code\n\nthrust_values = df.Thrust .|> ustrip .|> value;\nthrust_uncertainties = df.Thrust .|> ustrip .|> uncertainty;\n\nair = DataFrame(Thrust=thrust_values, Uncertainty=thrust_uncertainties, Time=df.Time .|> u\"s\" .|> ustrip);\n\n\nplot(df.Time .|> ustrip, thrust_values, \n title=\"Thrust Over Time\", \n ribbon=(thrust_uncertainties, thrust_uncertainties), \n fillalpha=.2,label=\"Thrust\",\n xlabel=\"Time (s)\", \n ylabel=\"Thrust (N)\",\n )\n\n\nFigure 1: Air Proplsion Simulation\n\n\n\nIn Figure 2, the air propulsion simulation is compared to commercially available rocket motors. This early in the project, we have no idea whether short burns or longer burns are ideal for a propulsive landing, so the air propulsion system was compared to a variety of different motors with unique profiles.\n\n\nShow code\n\nf10 = CSV.read(\"AeroTech_F10.csv\", DataFrame);\nf15 = CSV.read(\"Estes_F15.csv\", DataFrame);\ng8 = CSV.read(\"AeroTech_G8ST.csv\", DataFrame);\n\n\nplot(air.Time, air.Thrust, label=\"Air Propulsion\", legend=:topleft);\n\nfor (d, l) in [(f10, \"F10\"), (f15, \"F15\"), (g8, \"G8ST\")]\n plot!(d[!,\"Time (s)\"], d[!, \"Thrust (N)\"], label=l);\nend\n\ntitle!(\"Propulsion Comparison\");\nxlabel!(\"Time (s)\");\nylabel!(\"Thrust (N)\")\n\n\nFigure 2: Rocket Motor Data: (Coker, n.d.)\n\n\n\nIn the end, the air propulsion system’s performance has a very impressive total impulse and, with more time and resources, could be a serious option for a propulsive landing on Earth. One of the largest abstractions from the Moon mission that the mission here on Earth will have to deal with is the lack of Throttling engines since any propulsion system outside of model rocket motors is well beyond the scope of this Capstone.\nFuture Work\nAfter determining that solid model rocket motors are the best option for the current mission scope, the next step is determining what motor to use. There are many great options, and deciding what thrust profile is ideal may have to wait until a Simulink simulation of the landing can be built so that the metrics of each motor can be constrained more. Instead of throttling motors, the current working idea is that thrust vector control may be a way to squeeze a little more control out of a solid rocket motor. Thrust Vector Control will undoubtedly be challenging to control, so another essential piece that needs exploring is whether an LQR controller is feasible or if a PID controller is accurate enough to control our system.\n\n\n\nCoker, John. n.d. “Rocket Motor Data.” https://www.thrustcurve.org/.\n\n\nÇengel, Yunus A., and Michael A. Boles. 2015. Thermodynamics: An Engineering Approach. Eighth edition. New York: McGraw-Hill Education.\n\n\nSutton, George P., and Oscar Biblarz. 2001. Rocket Propulsion Elements. 7th ed. New York: John Wiley & Sons.\n\n\n\n\n", "preview": "posts/2021-04-01-air-propulsion-simulation/air-propulsion-simulation_files/figure-html5/unnamed-chunk-7-J1.png", - "last_modified": "2021-05-03T21:53:15-07:00", - "input_file": "air-propulsion-simulation.utf8.md", + "last_modified": "2021-05-07T08:51:19-07:00", + "input_file": {}, "preview_width": 600, "preview_height": 400 } diff --git a/docs/search.json b/docs/search.json index a9cc35d..4ec592a 100644 --- a/docs/search.json +++ b/docs/search.json @@ -6,14 +6,14 @@ "description": "I'm an Astronautical Engineer studying at Embry-Riddle Prescott.", "author": [], "contents": "\nI mostly write code, but sometimes I make 3D Models. This website is where I plan on breaking down some of my more interesting findings and sharing them with the World Wide Web. If you think I could be a could fit at your company then take a look at my Resume, otherwise you can reach me on Telegram or by Email.\n\n\n\n", - "last_modified": "2021-05-03T21:28:01-07:00" + "last_modified": "2021-05-07T09:53:25-07:00" }, { "path": "index.html", "title": "Anson's Projects", "author": [], "contents": "\n\n\n\n", - "last_modified": "2021-05-03T21:28:01-07:00" + "last_modified": "2021-05-07T09:53:25-07:00" } ], "collections": ["posts/posts.json"] diff --git a/docs/sitemap.xml b/docs/sitemap.xml index 78fea4a..31a521b 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -10,10 +10,10 @@ https://projects.ansonbiggs.com/posts/2021-04-14-iss-eclipse-determination/ - 2021-05-03T21:23:45-07:00 + 2021-05-07T09:51:55-07:00 https://projects.ansonbiggs.com/posts/2021-04-01-air-propulsion-simulation/ - 2021-05-03T21:53:15-07:00 + 2021-05-07T08:51:19-07:00