pyTSFoil

A Python interface for TSFOIL2, an inviscid transonic small-disturbance (TSD) solver for flow past lifting airfoils.

Overview

TSFOIL2 is a CFD solver known for its rapid solution time, ease of use, and open-source architecture. It solves the transonically-scaled perturbation potential and similarity variables to compute the following quantities:

• Pressure coefficient distribution (Cp) along airfoil surfaces
• Lift and drag coefficients through surface integration
• Transonic flow field analysis

Reference: Murman, E.M., Bailey, F.R., and Johnson, M.L., "TSFOIL - A Computer Code for Two-Dimensional Transonic Calculations, Including Wind-Tunnel Wall Effects and Wave Drag Evaluation," NASA SP-347, March 1975.

Original TSFOIL2: http://www.dept.aoe.vt.edu/~mason/Mason_f/MRsoft.html#TSFOIL2

Features

• Fast CFD Analysis: Direct Python interface to modernized Fortran TSFOIL2 solver
• Flexible Input: Support for airfoil coordinate files or numpy arrays
• Comprehensive Output: Pressure distributions, flow fields, lift/drag coefficients
• Visualization: Built-in plotting capabilities for results analysis
• Example Cases: Includes RAE2822 airfoil test cases and demonstrations

Installation

Prerequisites

• Python 3.8 or higher
• NumPy, SciPy, Matplotlib
• Fortran compiler for f2py, meson compilation (gfortran is recommended)
• Linux is recommended (for easier usage of meson)
• cst-modeling3d is recommended (for airfoil geometric modelling)

Install Package

sudo apt update
sudo apt install gfortran

# Install from source
git clone https://github.com/swayli94/pyTSFoil.git
cd pyTSFoil
pip install -e .

# Or install from PyPI
pip install pytsfoil>=0.2.1

# Test installation
python -c "import pytsfoil; print('✓ pytsfoil installed successfully')" || echo "pytsfoil failed to import"

# Optional: Install cst-modeling3d
pip install cst-modeling3d

Quick Start

from pytsfoil import PyTSFoil

# Load airfoil coordinates (or provide as numpy array)
pytsfoil = PyTSFoil(
    airfoil_coordinates=airfoil_coordinates,  # coordinates of the airfoil (x, y) [n_points, 2]
    airfoil_file='path/to/airfoil.dat',       # file containing the airfoil geometry (provide either airfoil_coordinates or airfoil_file)
    work_dir='output_directory',              # output directory for Fortran output files (smry.out, tsfoil2.out)
    output_dir='output_directory',            # output directory for Python output files (cpxs.dat, field.dat)
)

# Configure flow conditions
pytsfoil.set_config(
    ALPHA=0.5,      # Angle of attack (degrees)
    EMACH=0.75,     # Mach number
    MAXIT=9999,     # Maximum iterations
    n_point_x=200,  # Grid points in x-direction
    n_point_y=80,   # Grid points in y-direction
    EPS=0.2,        # Grid stretching parameter
    CVERGE=1e-6,    # Convergence criteria
    flag_output=True,           # write solver process to tsfoil2.out
    flag_output_summary=True,   # write summary to smry.out
    flag_output_shock=True,     # write shock data to cpxs.dat
    flag_output_field=True,     # write field data to field.dat
    flag_print_info=True,       # print information to console
)

# Run analysis
pytsfoil.run()

# Plot results
pytsfoil.plot_all_results()

# Access results
cp_upper = pytsfoil.data_summary['cp_upper']
cp_lower = pytsfoil.data_summary['cp_lower']
cl = pytsfoil.data_summary['cl']
cd = pytsfoil.data_summary['cd']

Package Structure

pyTSFoil/
├── pytsfoil.py           # Main PyTSFoil class and CFD interface
├── tsfoil_fortran.*      # Compiled Fortran module
├── compile_f2py.py       # Fortran compilation script
├── __init__.py           # Package initialization
└── example/              # Example cases
    ├── rae2822/          # Basic PyTSFoil usage example
    └── rae2822_mp/       # Multi-process PyTSFoil usage example

Important Notes

Data Security Warning: All PyTSFoil instances in the same Python process share underlying Fortran module data. For thread safety:

• Use only one PyTSFoil instance per Python process
• For parallel analyses, use multiprocessing.Pool
• Each subprocess gets isolated Fortran data

Safe parallel usage:

import multiprocessing as mp

def run_analysis(params):
    pytsfoil = PyTSFoil()  # Each process gets its own data
    # ... run analysis
    return results

with mp.Pool() as pool:
    results = pool.map(run_analysis, case_list)