fix invalid image caused by alt-text

posts/2018-09-12-how-to-export-fusion-360-files-to-other-file-types/index.qmd

@@ -9,7 +9,7 @@ categories:
   - Notes
 creative_commons: CC BY
 image: banner.png
-image-alt: A slide titled "EXPORTING FROM FUSION 360". The slide features the Fusion 360 logo on the left and a cloud icon on the right, with double arrows between them indicating data transfer in both directions.
+image-alt: A slide showing the Fusion 360 logo on the left and a cloud icon on the right, with double arrows between them indicating data transfer in both directions.
 ---
 
 

posts/2021-04-14-iss-eclipse-determination/index.qmd

@@ -14,7 +14,7 @@ categories:
   - Math
 creative_commons: CC BY
 image: preview.png
-image-alt: A diagram illustrating the umbra and penumbra regions cast by a celestial body. A circular body is shown with light rays from a spacecraft creating a conical shadow region labeled "Umbra". The lighter, partially shaded regions surrounding the umbra are labeled "Penumbra".
+image-alt: A diagram illustrating the umbra and penumbra regions cast by a celestial body.
 format:
   html:
     code-tools: true

posts/2022-02-07-space-debris-characterization/index.qmd

@@ -36,7 +36,7 @@ author:
 abstract: >
     Orbital debris is a form of pollution that is growing at an exponential pace and puts current and future space infrastructure at risk. Satellites are critical to military, commercial, and civil operations. Unfortunately, the space they occupy is increasingly becoming more crowded and dangerous, potentially leading to a cascade event that could turn orbit around the Earth into an unusable wasteland for decades proper mitigation is not introduced. Unfortunately, existing models employed by NASA rely on a dataset created from 2D images and are missing many crucial features required for correctly modeling the space debris environment. Our approach uses high-resolution 3D scanning to fully capture the geometry of a piece of debris and allow a more advanced analysis of each piece. This approach, coupled with machine learning methods, will allow advances to the current cutting edge. Physical and photograph-based measurements are time-consuming, hard to replicate, and lack precision. 3D scanning allows much more advanced and accurate analysis of each debris sample, focusing on properties such as moment of inertia, cross-section, and drag. With these additional properties, we stand to substantially increase our understanding of the space debris environment through advanced characterization of each piece of debris. Once the characteristics of space debris are more thoroughly understood, we can begin mitigating the creation and danger of future space debris by implementing improved satellite construction methods and more advanced debris avoidance measures. 
 description: |
-    The growing threat of orbital debris poses a significant risk to space infrastructure. Current NASA models, based on 2D images, lack crucial features for accurate modeling. This research utilizes high-resolution 3D scanning and machine learning to analyze debris geometry, enabling a more comprehensive understanding of the debris environment. This improved characterization will inform mitigation strategies, including better satellite construction and debris avoidance measures.
+    Research proposal detailing the growing threat of orbital debris and its significant risk to space infrastructure.
 description-meta: |
     Researching orbital debris using 3D scanning and machine learning to improve current models and inform mitigation strategies. Learn how this approach enhances our understanding of space debris and its impact on space infrastructure.
 funding: "This work was funded by ERAU URI Ignite Award"