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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Accompanying data for the paper "Modeling of nonlinear viscoelasticity and stress softening in soft tissues"

Authors: Caro, Anne-Sophie; Chrysochoos, Andre; Iaquinta, Sarah; Chagnon, Grégory;

Accompanying data for the paper "Modeling of nonlinear viscoelasticity and stress softening in soft tissues"

Abstract

Caro et al. (2025) – Supplementary Material This repository contains the Jupyter notebook used for the analyses presented in the paper: Caro et al. (2025), Modeling of nonlinear viscoelasticity and stress softening in soft tissues https://dx.doi.org/10.2139/ssrn.5274578. The dataset is identically stored on Zenodo and on Renkulab. 📓 Notebook - Caro_et_al_2025.ipynb: Contains all code used for data processing, analysis, and figure generation related to the study. 🚀 Getting Started You can run this notebook directly in Renkulab or in a local environment. Run in Renkulab Click the link below to launch the notebook in a pre-configured Renkulab session: https://renkulab.io/p/sarah.iaquinta/supplementary-material-for-caro-et-al-2025 📂 Repository Contents ├── Caro_et_al_2025.ipynb # Main analysis notebook ├── data/ # Input data files └── README.md # Readme file 📈 Outputs All figures and tables used in the manuscript are generated when running the notebook. 🔁 Reproducibility The analysis is designed to be fully reproducible. 👩‍💻 Authors - [Anne-Sophie Caro] – [anne-sophie.caro@mines-ales.fr] - LMGC, IMT Mines Alès, Univ Montpellier, CNRS, Alès, France - [Andre Chrysochoos] – [andre.chrysochoos@umontpellier.fr] - LMGC, Univ Montpellier, CNRS, Montpellier, France - [Sarah Iaquinta] – [sarah.iaquinta@mines-ales.fr] - LMGC, IMT Mines Alès, Univ Montpellier, CNRS, Alès, France - [Grégory Chagnon] – [gregory.chagnon@univ-grenoble-alpes.fr] - Univ. Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France. - Based on work by Caro et al. (2025) 📄 License Creative Commons Attribution 4.0. 📄 Detailed description This paper deals with the mechanical behavior of soft living tissues under load-unload and relaxation cyclic strains. It proposes a thermodynamic model formulated within the Generalized Standard Materials framework that incorporates both Mullins’ effect and viscoelasticity, integrating the history dependent behavior of the material under finite strain. A key innovation lies in the use of a common softening function to modulate both the hyperelastic and viscous components, capturing history-dependent behavior more accurately. Viscous parameters are adjusted based on the loading history via the maximum strain invariant. Numerical implementation is validated against uniaxial tensile tests on porcine perineal tissues and a global Sobol sensitivity analysis confirms that elastic, viscous, and Mullins-related parameters are identifiable from different phases of the loading protocol. This model provides a unified, thermodynamical consistent tool for simulating soft tissue mechanics. Keywords: Soft tissue, Finite strain, Visco-hyperelasticity, Mullins effect, Incompressibility

Keywords

finite strain, visco-hyperelasticity, mullins effect, incompressibility, soft tissue

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average