Data for Event-Triggered Satellite Conjunction Management with Response-Surface Benchmarking

Description

This dataset supports the manuscript “Event-Triggered Satellite Conjunction Management with Response-Surface Benchmarking.” It contains the AnyLogic .alp model, response-surface inputs, scenario parameters, MATLAB two-body and J2 benchmark scripts, six-direction RTN benchmarking outputs, calibrated radial-inward response-surface data, held-out validation outputs, 1000-sample calibrated surrogate Monte Carlo outputs, uncertainty-scale sensitivity outputs, random-seed information, figures, software-version notes, reproduction steps, and SHA-256 manifest checksums. The data relate to a synthetic encounter and surrogate decision model and do not include operational conjunction data, covariance products, or flight ephemerides.

Steps to reproduce

1. Download and extract the dataset package. 2. Open the README file and review the package structure, software-version notes, manifest, and reproduction instructions. 3. To inspect the AnyLogic implementation, open the supplied Satellite_CAM_Clean.alp model in AnyLogic 8.9.9 or a compatible version. The model contains the event-triggered conjunction-screening architecture, protected-satellite and resident-space-object agents, statechart logic, approval-delay scheduling, response-surface functions, secondary-screening lookup, and Monte Carlo/parameter-sweep configuration notes. 4. To reproduce the MATLAB benchmark and calibration results, open MATLAB and run the scripts in the matlab/scripts directory. The scripts reproduce the two-body and J2 benchmark cases, six-direction radial-transverse-normal maneuver comparison, radial-inward calibration assessment, held-out validation outputs, calibrated threshold estimates, calibrated delay sensitivity, and calibrated 1000-sample surrogate Monte Carlo outputs. 5. Compare the generated CSV files with the processed outputs supplied in the dataset package. Key outputs include benchmark error metrics, calibrated response knots, held-out validation results, required-delta-v estimates, calibrated Monte Carlo summaries, and uncertainty-scale sensitivity results. 6. Recreate the figures using the supplied MATLAB plotting routines and the processed CSV outputs. The figures correspond to the response-surface, benchmark, calibration, Monte Carlo, and uncertainty-sensitivity results reported in the manuscript. 7. Verify file integrity using the SHA-256 checksums listed in MANIFEST.csv. The dataset relates to a synthetic conjunction-management decision-support model. It does not contain operational conjunction data, CDMs, flight ephemerides, or operational covariance products.

Institutions

• Purdue University West Lafayette

  Indiana, West Lafayette

Categories

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