WrinkleFE

An open-source Python finite element package for predicting strength and stiffness knockdown in composite laminates containing fiber waviness defects.

Screenshots

Wrinkle Profile & Fiber Misalignment — Convex dual-wrinkle morphology showing upper/lower ply profiles, interface gap, and through-thickness fiber angle distribution.

3D Finite Element Mesh — Graded morphology with 8,640 hexahedral elements, color-coded by ply ID. Wrinkle amplitude decays from midplane to surface.

Stress Analysis & Retention — Through-thickness interlaminar stress (sigma_33) contour with strength and modulus retention bar chart. 58.3% strength retention, 97.9% modulus retention.

Features

• Compression model: CLT-weighted Budiansky-Fleck kink-band with layup-dependent confinement
• Tension model: Three-mechanism (fiber cos^2 theta, Hashin matrix, curved-beam sigma_33 delamination) with thick-ply in-situ correction
• 3D finite element: Structured hexahedral mesh with LaRC04/05 failure criteria
• Five morphologies: Stack, convex, concave, uniform, graded (with configurable decay floor)
• Graded averaging: Through-thickness ply-averaged knockdown for graded wrinkles
• PyQt6 GUI: Interactive analysis with real-time stress visualization
• 4 built-in materials: AS4/3501-6, IM7/8552, T300/914, T700/2510
• 414 tests covering all modules

Installation

From source (recommended)

git clone https://github.com/elhajjar1/WrinkleFE.git
cd WrinkleFE
pip install -e ".[all]"

Dependencies only

pip install numpy scipy matplotlib PyQt6 pyvista pyvistaqt

Verify installation

python -c "import wrinklefe; print('WrinkleFE installed successfully')"

Run tests

pytest

Quick Start

GUI

wrinklefe-gui

Command line

wrinklefe --help

Python API

from wrinklefe.analysis import AnalysisConfig, WrinkleAnalysis

config = AnalysisConfig(
    amplitude=0.366, wavelength=16.0, width=12.0,
    morphology="stack", loading="compression",
)
result = WrinkleAnalysis(config).run()
print(result.summary())

Tension analysis

config = AnalysisConfig(
    amplitude=0.366, wavelength=16.0, width=12.0,
    morphology="stack", loading="tension",
    angles=[0, 45, 90, -45, 0, 45, -45, 0, 0, -45, 45, 0, -45, 90, 45, 0],
    ply_thickness=0.152,
)
result = WrinkleAnalysis(config).run()
print(result.summary())

Graded morphology (embedded wrinkle)

config = AnalysisConfig(
    amplitude=0.5, wavelength=15.0, width=11.0,
    morphology="graded", decay_floor=0.0,
    loading="compression",
)
result = WrinkleAnalysis(config).run()
print(result.analytical_knockdown)

Validation

Validated against 31 experimental data points from three independent datasets:

Dataset	Loading	Cases	Pass	MAE
Elhajjar (2025)	Compression	13	11/13	9.9%
Elhajjar (2025)	Tension	7	7/7	6.2%
Mukhopadhyay (2015)	Compression	3	3/3	17.4%
Mukhopadhyay (2015)	Tension	3	3/3	12.1%
Li et al. (2026)	Compression	5	4/5	8.6%
Total		31	28/31	9.5%

To regenerate validation figures: python joss/generate_fig_elhajjar.py

How It Works

Compression

CLT-weighted Budiansky-Fleck:

KD_lam = f_0 / (1 + theta / gamma_Y_eff) + (1 - f_0)
gamma_Y_eff = 0.032 + 0.050 * f_confined

Tension

Three-mechanism minimum, CLT-weighted:

KD_lam = f_0 * min(cos^2(theta), KD_matrix, KD_oop) + (1 - f_0)

For graded morphology, the BF knockdown is averaged over the wrinkle profile in both the longitudinal (x) and through-thickness (z) directions, with Gaussian decay (scale = amplitude A) confining the effect to the wrinkle zone.

References

• Elhajjar, R. (2025). Scientific Reports, 15:25977.
• Li, Y. et al. (2026). Composites Part A, 205:109719.
• Budiansky, B. & Fleck, N.A. (1993). J. Mech. Phys. Solids, 41(1), 183-211.
• Pinho, S.T. et al. (2005). NASA-TM-2005-213530.
• Camanho, P.P. et al. (2006). Composites Part A, 37(2), 165-176.
• Jin, L. et al. (2026). Thin-Walled Structures, 219:114237.

License

MIT - see LICENSE

Contributing

See CONTRIBUTING.md

Citation

If you use WrinkleFE in your research, please cite:

Elhajjar, R. (2025). WrinkleFE: An open-source finite element package for strength prediction of wrinkled composite laminates (Version 1.0.0) [Computer software]. University of Wisconsin-Milwaukee. https://github.com/elhajjar1/WrinkleFE

@software{elhajjar2025wrinklefe,
  author = {Elhajjar, Rani},
  title = {{WrinkleFE}: An Open-Source Finite Element Package for Strength
           Prediction of Wrinkled Composite Laminates},
  year = {2025},
  version = {1.0.0},
  publisher = {GitHub},
  url = {https://github.com/elhajjar1/WrinkleFE},
  note = {University of Wisconsin-Milwaukee}
}

Please also cite the underlying experimental validation data:

Elhajjar, R. (2025). Fat-tailed failure strength distributions and manufacturing defects in advanced composites. Scientific Reports, 15, 25977. https://doi.org/10.1038/s41598-025-25977-3