🚀 Deep Space Mission OS

Professional Aerospace Engineering & Trajectory Design Platform
Astrodynamics · Orbital Mechanics · Digital Twin · Propulsion Diagnostics

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📡 Overview

Deep Space Mission OS is a full-stack, production-grade aerospace engineering platform providing:

• Interactive 3D Orbital Visualization — Plotly.js-powered trajectory rendering with live telemetry HUD
• Mission Planning & Delta-V Budgeting — Tsiolkovsky rocket equation, multi-stage sizing, and propellant fractions
• Interplanetary Porkchop Plots — C₃ launch energy optimization grids for Earth-Mars, Lunar, and asteroid destinations
• Trajectory Optimization — Genetic Algorithm, Particle Swarm, and Differential Evolution solvers
• J₂ Perturbation Propagation — Nodal precession (Ω̇) and apsidal rotation (ω̇) over configurable timelines
• N-Body Perturbations — Lunar and solar third-body gravity integrated via adaptive Dormand-Prince RK5(4) propagator
• Sun-Synchronous Design Tool — Automatic inclination solver + RAAN optimizer from launch calendar date
• Monte Carlo Uncertainty Dispersion — 3σ trajectory envelope visualization across perturbed initial conditions
• Active Station-Keeping Engine — Impulsive ΔV burn simulator with fuel allocation and depletion warnings
• Orbital Transfer Solver — Hohmann, Bi-elliptic, and Low-Thrust Spiral transfer computations
• Digital Twin Diagnostics — EKF state estimation, CCSDS telemetry parsing, AI anomaly forecasting
• Propulsion Simulation — Vacuum chamber pressure decay and ion thruster grid erosion rate (Yamamura-Tawara model)

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🖥️ Dashboard Preview

The platform features a glassmorphism dark-mode UI with:

• 🛸 3D Trajectory Viewer with animated playback controls
• 📊 Porkchop Contour Plots and optimizer convergence charts
• 🎯 Live Orbit Tweaker with real-time vis-viva feedback
• 🔭 5-Tab Diagnostics Panel (EKF · CCSDS · Anomaly · Vacuum · Erosion)

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🏗️ Architecture

Deep Space Mission OS/
│
├── backend/
│   ├── api/
│   │   └── main.py              # FastAPI REST server (1,300+ lines, 35+ endpoints)
│   └── static/
│       ├── index.html           # Single-page dashboard (600+ lines)
│       ├── style.css            # Glassmorphism design system (760+ lines)
│       └── app.js               # Interactive JS logic (2,100+ lines)
│
├── deep-space-ecosystem/
│   ├── deep-space-core/         # Astrodynamics kernel (Keplerian, Lambert, propagators)
│   ├── deep-space-mission-planner/  # Mission engine & optimizer
│   ├── deep-space-digital-twin/ # EKF, CCSDS telemetry, AI anomaly twin
│   ├── deep-space-propulsion-simulator/ # Electric, chemical, nuclear propulsion
│   ├── deep-space-sdk/          # Python SDK & CLI tools
│   ├── deep-space-datasets/     # Validated reference datasets
│   ├── deep-space-docs/         # API documentation
│   └── deep-space-knowledge/    # Mathematics & physics libraries
│
├── simulations/                 # Standalone scenario scripts (Mars, Moon, Asteroid)
├── tests/                       # 175-test verification suite
│   ├── test_tweaker_api.py      # Orbit tweaker + diagnostics endpoint tests
│   ├── test_phase5_ai.py        # AI digital twin tests
│   ├── test_sdk.py              # SDK & CLI integration tests
│   └── unit/                   # Unit tests (algebra, constants, propagators)
│
├── ARCHITECTURE.md              # Deep system design documentation
├── README.md                    # This file
├── LICENSE                      # MIT License
├── requirements.txt             # Python dependencies
└── pytest.ini                   # Test configuration

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🛠️ Setup & Installation

Prerequisites

• Python 3.9+
• pip / virtualenv

1. Clone the Repository

git clone https://github.com/SahilKhutey/Deep-Space-Mission-OS.git
cd Deep-Space-Mission-OS

2. Install Dependencies

pip install -r requirements.txt

3. Launch the Dashboard Server

uvicorn backend.api.main:app --host 127.0.0.1 --port 8000 --reload

Open your browser at http://127.0.0.1:8000

4. API Documentation (Swagger UI)

http://127.0.0.1:8000/docs

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🚀 API Endpoint Reference

Mission Planning

Endpoint	Method	Description
/api/v1/mission/plan	POST	Full interplanetary mission plan with feasibility check
/api/v1/fuel/compute	POST	Tsiolkovsky propellant mass calculation
/api/v1/deltav/budget	POST	Segment-by-segment ΔV budget tracker
/api/v1/staging/size	POST	Multi-stage rocket sizing
/api/v1/presets/mars	GET	Pre-planned Mars mission architecture
/api/v1/presets/moon	GET	Pre-planned Lunar mission architecture

Trajectory & Optimization

Endpoint	Method	Description
/api/v1/porkchop/generate	POST	Porkchop C₃ launch energy grid
/api/v1/optimization/optimize	POST	GA / PSO / DE launch window optimizer
/api/v1/simulations/run	POST	Numerical trajectory propagation (Mars, Moon, Asteroid)

Astrodynamics Toolkit

Endpoint	Method	Description
/api/v1/astrodynamics/vis-viva	POST	Vis-viva velocities + J₂ precession rates
/api/v1/astrodynamics/propagate-perturbed	POST	J₂ + N-body perturbed propagation
/api/v1/astrodynamics/sun-synchronous	POST	Sun-synchronous inclination solver
/api/v1/astrodynamics/sunsync-raan	POST	RAAN optimizer from launch date
/api/v1/astrodynamics/station-keeping	POST	Station-keeping burn + fuel warning
/api/v1/astrodynamics/hohmann	POST	Hohmann transfer ΔV computation
/api/v1/astrodynamics/bielliptic	POST	Bi-elliptic transfer ΔV computation
/api/v1/astrodynamics/low-thrust-spiral	POST	Low-thrust spiral transfer solver
/api/v1/astrodynamics/monte-carlo	POST	Monte Carlo 3σ dispersion envelopes

Digital Twin & Propulsion Diagnostics

Endpoint	Method	Description
/api/v1/digital-twin/ekf-simulate	POST	EKF state estimator on circular orbit with fault injection
/api/v1/digital-twin/ccsds-parse	POST	Decode CCSDS Space Packet from hex
/api/v1/digital-twin/anomaly-predict	POST	AI twin anomaly forecasting from telemetry history
/api/v1/propulsion/vacuum-simulate	POST	Vacuum chamber pressure decay simulation
/api/v1/propulsion/erosion-rate	POST	Ion thruster grid erosion rate (Yamamura-Tawara model)

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🔬 Key Physics Models

Orbital Mechanics

Model	Implementation
Vis-Viva Equation	$v = \sqrt{\mu\left(\tfrac{2}{r} - \tfrac{1}{a}\right)}$
Kepler's Equation	Newton-Raphson with bisection fallback
J₂ Perturbation	Nodal precession $\dot\Omega = -\tfrac{3}{2}nJ_2\left(\tfrac{R}{p}\right)^2\cos i$
Lambert's Problem	Universal Variable Formulation
Hohmann Transfer	Two-impulse coplanar
Bi-elliptic Transfer	Three-impulse with configurable boost apoapsis
Low-Thrust Spiral	Mass-flow integrated Edelbaum-style solver
Monte Carlo Dispersion	Gaussian state perturbations, 3σ envelope

Propagators

Integrator	Order	Usage
Dormand-Prince RK5(4)	5th-order	Adaptive perturbed orbit propagation
Adams-Bashforth-Moulton	4th-order	Long-arc mission propagation
Classical RK4	4th-order	Fixed-step orbit simulation

Propulsion Science

Model	Description
Tsiolkovsky Rocket Equation	Multi-stage mass-ratio and propellant sizing
Yamamura-Tawara (1996)	Ion thruster grid sputter-yield: $Y(E) = Y_{300}\cdot(E/300)^{0.6}\cdot(1-\sqrt{E_{th}/E})^2$
Vacuum Chamber Model	First-order pressure decay: $\dot{p} = Q_{leak}/V - S\cdot p/V$

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🧪 Running Tests

# Run full test suite (175 tests)
python -m pytest tests/ -v

# Run only astrodynamics tests
python -m pytest tests/ -m dashboard -v

# Run only diagnostics tests
python -m pytest tests/ -m diagnostics -v

# Run unit tests only
python -m pytest tests/unit/ -v

Expected output:

====================== 175 passed in ~12s =======================

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📦 Python SDK

A fully-typed Python SDK and CLI are included in deep-space-ecosystem/deep-space-sdk/:

from deep_space_sdk import DeepSpaceClient

client = DeepSpaceClient(base_url="http://127.0.0.1:8000")

# Plan a mission
plan = client.plan_mission(
    destination="Mars",
    spacecraft_mass=2500,
    propulsion_type="Chemical",
    payload_mass=800,
    launch_date="2032-08-15"
)
print(plan)

CLI usage:

python -m deep_space_sdk.cli mission-plan --destination mars --mass 2500
python -m deep_space_sdk.cli cost-estimate --destination mars
python -m deep_space_sdk.cli risk-report
python -m deep_space_sdk.cli digital-twin-check

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🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

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📄 License

This project is licensed under the MIT License — see the LICENSE file for details.

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👨‍🚀 Author

Sahil Khutey
GitHub · Deep Space Mission OS

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Built with ❤️ for the future of space exploration