SPH Simulation Project

A collection of Smoothed Particle Hydrodynamics (SPH) simulations implemented in Python for computational physics applications.

🌟 Overview

This project implements SPH methods to simulate fluid dynamics problems, featuring:

• Sod Shock Tube simulations with animated visualizations
• Planetary/Astrophysical fluid dynamics scenarios
• Real-time visualization and animation generation
• Multiple implementation approaches (current and legacy methods)

📁 Project Structure

SPHSimulation/
├── 1/                          # Sod Shock Tube Simulations
│   ├── sodshock.py            # Main SPH shock tube implementation
│   ├── sodshock_leg.py        # Legacy implementation (v1)
│   ├── sodshock_leg2.py       # Legacy implementation (v2)
│   └── sodshock_movie.mp4     # Generated animation output
├── 2/                          # Planetary/Astrophysical Simulations
│   └── planets.py             # SPH simulation for planetary scenarios
├── flake.nix                  # Nix development environment
├── flake.lock                 # Nix lockfile
└── README.md                  # This file

🚀 Features

Sod Shock Tube Simulation

• Simulates the classic Riemann problem in fluid dynamics
• Visualizes the evolution of:
  • Density (ρ)
  • Pressure (p)
  • Velocity (v)
  • Internal Energy (e)
• Generates MP4 animations showing temporal evolution
• Includes legacy implementations for comparison and development history

SPH Implementation

• Particle-based fluid simulation using smoothed particle hydrodynamics
• Adaptive time stepping with RK4 integration
• Kernel-based interpolation for smooth field calculations
• Equation of state: ideal gas law with γ = 1.4

🛠️ Dependencies

This project uses the following Python packages:

• numpy - Numerical computations
• matplotlib - Plotting and visualization
• scipy - Scientific computing and integration
• moviepy / ffmpeg - Animation generation

💻 Setup & Installation

Option 1: Quick Setup (Recommended)

Linux/macOS:

# Clone and navigate to project
git clone <repository-url>
cd SPHSimulation

# Run setup script
./setup.sh

Windows:

# Clone and navigate to project
git clone <repository-url>
cd SPHSimulation

# Run setup script
setup.bat

Option 2: Manual Setup

Using pip:

# Create virtual environment
python -m venv venv

# Activate environment
source venv/bin/activate  # Linux/macOS
# OR
venv\Scripts\activate.bat  # Windows

# Install dependencies
pip install -r requirements.txt

Using conda:

# Create environment from file
conda env create -f environment.yml

# Activate environment
conda activate sph-simulation

Option 3: Nix (Advanced Users)

The project includes a Nix flake for reproducible development environments:

# Enter development shell
nix develop

System Dependencies

• Python 3.9+ (3.12 recommended)
• FFmpeg (for video generation)
  • Ubuntu/Debian: sudo apt install ffmpeg
  • macOS: brew install ffmpeg
  • Windows: Download from ffmpeg.org or use choco install ffmpeg

🎯 Usage

First, activate your environment:

# If using venv
source venv/bin/activate  # Linux/macOS
# OR
venv\Scripts\activate.bat  # Windows

# If using conda
conda activate sph-simulation

# If using Nix
nix develop

Running Sod Shock Simulations

# Navigate to directory 1
cd 1/

# Run main simulation
python sodshock.py

# Run legacy implementations
python sodshock_leg.py
python sodshock_leg2.py

Running Planetary Simulations

# Navigate to directory 2
cd 2/

# Run planetary simulation
python planets.py

📊 Output

• Real-time plots: Display simulation progress
• Animated visualizations: MP4 files showing temporal evolution
• Data analysis: Particle state histories for post-processing

🧮 Physics Background

Smoothed Particle Hydrodynamics (SPH)

SPH is a computational method for simulating fluid flows by representing the fluid as a collection of particles. Each particle carries physical properties (mass, density, pressure, velocity) and interacts with nearby particles through a smoothing kernel.

Sod Shock Tube

A classic test problem in computational fluid dynamics involving:

• Initial discontinuity in density and pressure
• Evolution into shock waves, contact discontinuities, and rarefaction waves
• Exact analytical solutions available for validation

📈 Applications

This simulation framework is suitable for:

• Educational purposes: Understanding SPH methods and fluid dynamics
• Research: Computational physics and astrophysics applications
• Validation: Testing new SPH implementations against known solutions
• Visualization: Creating animations for presentations and publications

📄 License

This project is licensed under the terms specified in the LICENSE file.

🤝 Contributing

For questions or collaboration opportunities, please refer to the repository owner.

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Part of Applied Computational Physics and Machine Learning coursework