Welcome to DeepFlame’s Documentation

DeepFlame is a computational fluid dynamics suite for single or multiphase, laminar or turbulent reacting flows at all speeds with machine learning capabilities. It aims to provide an open-source platform bringing together the individual strengths of OpenFOAM, Cantera and Torch libraries for deep learning assisted reacting flow simulations. It is also has the scope to incorporate next-generation heterogenous supercomputing and AI acceleration infrustructures such as GPU and FPGAs.

Note

This project is under active development.

Installation

• 1. Install OpenFOAM-7 (if not already installed)
• 2. Source your OpenFOAM
• 3. Clone the DeepFlame repository
• 4. Install dependencies and DeepFlame based on your need
  • 4.1. No Torch version
  • 4.2. LibTorch version
  • 4.3. PyTorch version

Quick Start

• Quick Examples for Each Integrator
  • 1. CVODE Solver
  • 2. Libtorch Solver
  • 3. PyTorch Solver

Solvers

• 1. df0DFoam
  • 1.1. Zero-Dimensional ignition reactor
• 2. dfLowMachFoam
  • 2.1. One-Dimensional Planar Flame
  • 2.2. Two-Dimensional Jet Flame
  • 2.3. Three-Dimensional reactive Taylor-Green Vortex
• 3. dfHighSpeedFoam
  • 3.1. One-Dimensional Reactive Shock Tube
  • 3.2. One-Dimensional H2/Air Detonation
  • 3.3. Two-Dimensional H2/Air Detonation
• 4. dfSprayFoam
  • 4.1. aachenBomb

Utility

• 1. Reaction Mechanism Convertion
• 2. Flame Speed

Project Details

• 1. Development Team
• 2. How to Cite

Contributing to DeepFlame

• Submitting a Pull Request