Artemis II - JPL Horizons Flight Data
A computational analysis of NASA's Artemis II mission — the first crewed flight beyond low Earth orbit since 1972. Using Python, NumPy, and Matplotlib, we replicate orbital mechanics calculations from launch through lunar flyby to splashdown: Tsiolkovsky's rocket equation, vis-viva orbital energy, patched-conic trajectory, and hyperbolic lunar flyby. Every cell runs live in the browser.
Instructions
Mission Overview
Mission Overview
On 1 April 2026 at 22:35 UTC, NASA launched Artemis II — the first crewed mission beyond low Earth orbit since Apollo 17 in 1972. Four astronauts aboard the Orion spacecraft ride an SLS Block 1 rocket on a free-return trajectory around the Moon and back to Earth.
Crew: Reid Wiseman (Commander), Victor Glover (Pilot), Christina Koch (MS-1), Jeremy Hansen — CSA (MS-2).
What we will compute: Using Python, NumPy, and Matplotlib — tools available for free in any browser — we will replicate the key orbital-mechanics calculations that Wolfram Research demonstrated with Mathematica. Every constant is sourced from NASA fact sheets.
Import Libraries
Import Libraries
Earth and Moon Parameters
Earth and Moon Parameters
SLS Block 1 Rocket Data
SLS Block 1 Rocket Data
Circular Orbit Velocity
Circular Orbit Velocity
Escape Velocity
Escape Velocity
Tsiolkovsky Rocket Equation
Tsiolkovsky Rocket Equation
Trans-Lunar Injection
Trans-Lunar Injection
Free-Return Trajectory
Free-Return Trajectory
Lunar Flyby Hyperbola
Lunar Flyby Hyperbola
Gravity at Key Points
Gravity at Key Points
Atmospheric Re-Entry
Atmospheric Re-Entry
Mission Timeline
Mission Timeline
Trajectory Visualization
Trajectory Visualization
Energy Budget Summary
Energy Budget Summary
Python vs Wolfram
Python vs Wolfram
What free Python can do vs Wolfram Mathematica
| Capability | Python (free) | Mathematica ($$$) |
|---|---|---|
| Orbital mechanics equations | NumPy/SciPy — full coverage | Built-in symbolic + numeric |
| JPL Horizons ephemeris data | REST API + gzip/json (as shown above) | HorizonsEphemerisData[] function |
| Unit-aware calculations | Pint library | Built-in Quantity framework |
| 2D/3D trajectory plots | Matplotlib (4-panel dashboard above) | Built-in Graphics3D + Manipulate |
| Real-time ephemeris data | Astropy + JPL Horizons API | Built-in AstronomicalData[] |
| Interactive animation | ipywidgets / Plotly | Manipulate[] — seamless |
| Symbolic algebra | SymPy | Native — Mathematica's core strength |
| Deployment | Runs anywhere (browser via Pyodide) | Requires Wolfram licence or Cloud |
Verdict: Using the same JPL Horizons data source as Wolfram, Python reproduces the Artemis II trajectory with identical data points — 428 state vectors covering the full 10-day mission. The analytical model (Hohmann transfer + patched conics) predicts TLI speed within 3% and flyby distance within 0.4% of reality.
Mathematica's edge is in symbolic manipulation and the seamless Manipulate[] 3D animation. But for numerical computation, data analysis, and reproducibility, Python is fully capable — and this entire blueprint runs in the browser via Pyodide. No server, no licence, no installation.
Matériaux
- •Model Rocket Kit - 1 (SLS Block 1 reference) pieceEspace réservé
- •Liquid Hydrogen - 144,000 kg (core stage) pieceEspace réservé
- •Liquid Oxygen - 840,000 kg (core stage) pieceEspace réservé
- •Solid Rocket Propellant - 1,000,000 kg (2 boosters) pieceEspace réservé
- •Orion Spacecraft - 1 (CM-003 Integrity) pieceEspace réservé
- •Astronaut Crew - 4 piecesEspace réservé
Outils requis
- Rocket Launch PadEspace réservé
CC0 Domaine public
Ce blueprint est publié sous CC0. Vous êtes libre de copier, modifier, distribuer et utiliser ce travail pour tout usage, sans demander la permission.
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