porkchop: Visualize Interplanetary Trajectory Constraints

A porkchop plot generator for interplanetary mission design. Given a range of departure and arrival dates, it solves Lambert's problem across a grid of transfer trajectories and visualizes the results as a contour plot of characteristic energies ($C_3$) derived from spacecraft excess velocities ($V_\infty{}$). The brute-force Lambert solver is written in Rust for speed, with Python handling visualization.

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Example: 2026 Earth–Mars Transfer Window

The plots below compare Porkchop's output against the reference contour plot from Burke et al. (2010) for the same transfer opportunity — a strong validation of the solver's accuracy.

Burke, L. M. Interplanetary Mission Design Handbook: Earth-to-Mars Mission Opportunities 2026 to 2045. NASA Technical Reports Server, ntrs.nasa.gov/citations/20100037210.

Example: 2003 Mars Opportunity Rover & 2020 Mars Perseverance Rover Transfer

The green contours represent the spacecraft's outbound launch asymptote declination, another constraint used in preliminary trajectory design.

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Core Features

• Departure/Launch C3 Energy ($\frac{\text{km}^2}{\text{s}^2}$) Contour Plot
• Arrival C3 Energy ($\frac{\text{km}^2}{\text{s}^2}$) Contour Plot
• Declination of Launch Asymptote Plot (deg)
• Right Ascension of Launch Asymptote Plot (deg)
• Lines of Constant Time of Flight (days)
• Manual levels adjustment

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How It Works

1. Rust solver — iterates over a grid of departure date and time-of-flight pairs and solves Lambert's problem for each, computing the launch and arrival $V_\infty{}$ before computing characteristic energy $C_3$.
2. Python plotter — reads the solver's output and renders contour plots with labeled $C_3$ curves.
3. run.sh — allows for manual adjustment of the solver's search parameters and general plotting functions.

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Limitations

1. Lambert's problem assumes ideal two-body (Keplarian) motion, and errors in small perturbations, planetary oblateness, atmospheric drag, solar radiation pressure are not accounted for. (Possible "fix" for this could be applying mid-course corrections).
2. The Rust crate satkit only provides JPL ephemeris for the main 8 planets and Pluto, so small body data is not currently implemented.
3. Ballistic-only trajectories: we are assuming that the calculated delta-v is delivered instantaneously
4. No gravity assists: it's a little silly to plot a porkchop plot from Earth to the Jovian Planets (for example, Europa Clipper used a Mars gravity assist on it's way to Europa)

Prerequisites

• Rust ≥ 1.86: rust-lang.org/tools/install
• Python ≥ 3.9: python.org/downloads

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Installation

# 1. Clone the repository
git clone https://github.com/mihirb-6/porkchop.git
cd porkchop

# 2. Set up the Python virtual environment
cd plotter-python
python -m venv .venv
source .venv/bin/activate       # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
cd ..

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Usage

# Make the runner executable (first time only)
chmod +x run.sh

# Run the full pipeline: Rust solver → Python plotter
./run.sh

The plot will be saved to docs/porkchop_plot.png.

Running steps individually

# Build and run only the Rust solver (outputs raw trajectory data)
cargo build --release
./target/release/porkchop

# Then plot manually (from inside the plotter-python directory, with venv active)
python plot.py

Tip: Use cargo build --release for significantly faster solve times compared to the debug build.

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Project Structure

porkchop/
├── solver-rust/        # Lambert solver (Rust) [main.rs, trajectory.rs, elements.rs]
├── plotter-python/     # Contour plot generator (Python) [plot.py]
├── docs/               # Output images and reference plots
├── run.sh              # End-to-end pipeline script
├── config.toml         # TOML to configure search/plot parameters from both Python and Rust
└── README.md

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License

MIT — see LICENSE.