Proof-first aerocapture + Entry/Descent/Landing (EDL) deceleration architecture for reproducible trade studies.
This repository is built around one idea: if you can’t rerun it from a single config and audit what happened, it doesn’t count.
So instead of starting with marketing claims or “magic braking,” this repo starts with constraints, baselines, telemetry, and verification — then layers models only after scope is locked.
Maintainer: Bryce Lovell
License: Apache-2.0
Status: Active development (README intentionally lean; details live in /docs)
Braking/capture problems die in review for predictable reasons:
- unclear assumptions,
- hidden constants,
- no baselines,
- no reproducibility,
- “trust me” outputs with no proof trail.
This repo targets the opposite:
- Corridor / heating / q / g constraints are first-class
- results are replayable
- verification is range-based early (no fake precision)
- every run produces audit-grade artifacts (config echo + JSONL telemetry + result bundle)
This is intended to be useful to:
- Mission design (aerocapture trades, capture energy vs propulsive ΔV)
- EDL/GNC (corridor shaping under constraints)
- TPS/structures (heating proxy + q gates + margin reporting)
- Tooling/verification folks (repeatability + regression harness)
- An architecture + workflow for aerocapture/EDL deceleration studies
- A simulation harness scaffold (config → run → telemetry → result)
- A verification scaffold (golden cases + range checks)
- A telemetry/proof scaffold for reviewable evidence artifacts
- A claim of reactionless braking
- A warp/negative-energy dependency
- A finished physics toolchain (models are intentionally stubbed until scope is locked)
- Architecture Map:
docs/architecture/ARCH_MAP.md - Decision Log:
docs/decision-log/DECISION_LOG.md - Requirements:
docs/requirements/METRICS.md(what we measure)CONSTRAINTS.md(hard gates)BASELINES.md(what “better” means)
Repo guardrails:
CLAIMS_POLICY.mdSCOPE.md
docs/— architecture, decisions, requirements (this is where the real content lives right now)models/— interfaces/contracts only (physics implementations come later)sim/— run harness (config IO + JSONL telemetry + result bundle)verification/— golden-case scaffolding + range checkertelemetry/— proof bundle tools + schema + basic validators
python -m sim.run sim/example_configs/minimal_run.json
This creates:
sim_output/<timestamp>_<hash>/config.echo.json
sim_output/<timestamp>_<hash>/telemetry.jsonl
sim_output/<timestamp>_<hash>/result.json
Note: models are not executed yet (by design). This validates the run pipeline and proof trail.
2) Run the minimal verification case
python verification/run_case.py verification/cases/case_000_minimal
3) Validate telemetry format (basic)
python -m telemetry.validate_basic sim_output/<run_id>/telemetry.jsonl
Evidence levels (how this repo stays credible)
This repo uses explicit evidence tags:
E0 concept
E1 toy model
E2 implemented model
E3 cross-checked
E4 measured
E5 flight relevant
If a claim is stronger than E1, it must link to the model producing it and its assumptions.
Roadmap (near-term, realistic)
Lock mission focus (aerocapture-to-orbit vs landing EDL vs both) via Decision Log
Implement a first E1/E2 atmosphere + aero proxy + heating proxy (explicit assumptions)
Add initial golden cases with published-range cross-check targets (E3 path)
Expand verification to include constraint violations and degrade modes
Improve proof bundles (packaging + stronger schema checks)
Contributing
See CONTRIBUTING.md.
Key rule while architecture is evolving: do not churn the README — add substance to /docs, cases, and checks.
Disclaimer
This is an independent engineering repo and is not affiliated with NASA, SpaceX, or any other organization.