| bin | ||
| detection.mcdplib | ||
| dome.mcdplib | ||
| hask | ||
| images | ||
| out-mcdp_plot | ||
| present | ||
| py | ||
| py-mcdp | ||
| redirection.mcdplib | ||
| sensors.mcdplib | ||
| .gitattributes | ||
| .gitignore | ||
| .pre-commit-config.yaml | ||
| _typos.toml | ||
| flake.lock | ||
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| LICENSE | ||
| README.md | ||
Blue Dome
MIT 1.144 ACT4ED Project, Fall 2025
About
Applied category theory offers new opportunities to approach complex design problems in a mathematically rigorous and computationally tractable way. Properties such as compositionality and functorality of the solution map allow for design problems to be split into smaller problems, solved, and recombined into a provably optimal solution.
Blue Dome is our Fall 2025 ACT4ED project using category theory to investigate orbital defense. Specifically, we investigate sensor selection and interception methods to prevent near earth objects (NEOs) from causing harm to Earth.
Structure
Presentations
Presentations on our work can be found here.
Sensor Modeling
Sensor modeling for ground-based and space-based sensors can be found here.
Sensor Selection (Python)
Python code on determining sensor choices can be found in py-mcdp.
Sensor Selection (MCDPL)
MCDPL code on determining sensor choices can be found in dome.mcdplib.
STK Simulations
ANSYS Satellite Toolbox is used for visualization of orbits and sensors. Tools to convert JPL Horizons Ephemeris into ANSYS STK Ephemeris to create orbits of NEOs can be found in horizons_to_stk.md.
Proximal Motion Equations
Initial work was done on determining orbital changes based on kinetic intercepts. Equations are from Optimal Impact Strategies for Asteroid Deflection by Massimiliano Vasile and Camilla Colombo.