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  1. Home
  3. Fibre Phantom Generation Using Fibresimulator: An Open-source Python Tool.
  1. Home
  3. Fibre Phantom Generation Using Fibresimulator: An Open-source Python Tool.

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Fibre phantom generation using FibreSimulator: an open-source Python tool.

Mary Chris Roperos Go1, Daniël M Pelt1, Anirudh Kohli2

  • 1Leiden Institute of Advanced Computer Science, Universiteit Leiden, Leiden, The Netherlands.

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|March 25, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

FibreSimulator generates realistic synthetic data for fibre-reinforced composites, enabling quantitative analysis of computed tomography scan parameters. This open-source tool aids in optimizing imaging for material science research.

Keywords:
FibreSimulatorcomputational modellingcomputed tomographyradiography

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Area of Science:

  • Materials Science
  • Computational Imaging
  • Polymer Composites

Background:

  • Fibre-reinforced polymers (FRPs) are crucial engineering materials, requiring internal structure visualization for mechanical property assessment.
  • Computed tomography (CT) is a key non-destructive imaging technique for FRPs, but machine learning methods need extensive, realistic datasets.
  • Acquiring experimental CT datasets for composites is difficult due to high costs and lack of ground truth data.

Purpose of the Study:

  • To develop an open-source Python tool, FibreSimulator, for generating labelled 3D synthetic phantoms of unidirectional fibre-reinforced polymers.
  • To enable simulation of tomographic scans with customizable material properties, fibre orientations, and geometrical features.
  • To facilitate systematic and quantitative investigation of how CT acquisition parameters influence reconstruction and segmentation.

Main Methods:

  • Developed FibreSimulator, an open-source Python tool for creating 3D synthetic phantoms of FRPs.
  • Integrated FibreSimulator with the ASTRA toolbox to simulate realistic CT scans of the generated phantoms.
  • Conducted simulated experiments to evaluate the impact of varying X-ray projections and beam intensity on reconstruction and segmentation.

Main Results:

  • Simulated CT scans showed that reduced projections and lower beam intensity blur fibre boundaries, overestimate diameters, and decrease fibre detection.
  • FibreSimulator enabled quantitative analysis of artefacts like undersampling and fibre overlap, revealing nonlinear trends in detection accuracy.
  • The tool demonstrated the ability to systematically study the effects of acquisition parameters and composite properties under controlled, ground-truth conditions.

Conclusions:

  • FibreSimulator provides a valuable, controllable platform for generating synthetic data crucial for advancing CT-based analysis of fibre-reinforced polymers.
  • The tool aids in optimizing CT parameters and guiding experimental design, overcoming limitations of purely experimental approaches.
  • Enables quantitative investigation of imaging artefacts and their impact on material characterization, crucial for materials science research.