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Related Experiment Video

Updated: Jun 26, 2025

Generation of a Three-dimensional Full Thickness Skin Equivalent and Automated Wounding
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A computationally efficient gradient-enhanced healing model for soft biological tissues.

Di Zuo1, Mingji Zhu2, Daye Chen2

  • 1Department of Engineering Mechanics, Dalian Jiaotong University, Dalian, 116028, People's Republic of China. zuodi@djtu.edu.cn.

Biomechanics and Modeling in Mechanobiology
|May 11, 2024
PubMed
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A computationally efficient stochastic analysis method for predicting the long-term development of aneurysms.

Computer methods in biomechanics and biomedical engineering·2025

This study introduces an efficient computational model for soft tissue healing. The gradient-enhanced healing model reduces computation time for simulating tissue damage and growth, aiding biomechanical research.

Area of Science:

  • Biomechanics
  • Computational Biology
  • Materials Science

Background:

  • Soft biological tissues exhibit growth and remodeling in response to damage.
  • Computational models are crucial for understanding tissue healing mechanisms.
  • Existing models often suffer from high computational cost and implementation complexity.

Purpose of the Study:

  • To develop a computationally efficient gradient-enhanced healing model for soft biological tissues.
  • To combine gradient-enhanced damage, homeostatic remodeling, and damage-induced growth models.
  • To facilitate finite element simulations of tissue healing and remodeling.

Main Methods:

  • Proposed a gradient-enhanced healing model with explicit solution for healing parameters.
  • Incorporated an adaptive time increment method to reduce computation time.
Keywords:
AneurysmComputational efficiencyGradient-enhancedGrowth and remodelingNumerical simulationSoft biological tissues

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  • Implemented the model in Abaqus using a user subroutine (UMAT).

    • Main Results:

    • The model demonstrated computational efficiency compared to existing methods.
    • Verified model effectiveness through semi-analytical examples and mechanical tests (uniaxial tension, open-hole plate).
    • Investigated the influence of model variables on tissue behavior.

    Conclusions:

    • The proposed model offers an efficient and implementable approach for simulating soft tissue healing and remodeling.
    • The model is suitable for investigating complex biomechanical problems, such as aneurysm development.
    • This work advances computational tools for understanding biological tissue response to damage.