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A multiscale modelling of bone ultrastructure elastic proprieties using finite elements simulation and neural network

Abdelwahed Barkaoui1, Brahim Tlili1, Ana Vercher-Martínez2

  • 1Université de Tunis El Manar, Ecole Nationale d'Ingénieurs de Tunis, LR-11-ES19 Laboratoire de Mécanique Appliquée et Ingénierie (LR-MAI), 1002 Tunis, Tunisie; Université de Tunis El Manar, Institut Préparatoire aux Etudes d'Ingénieurs d'El Manar, B.P 244, 2092 Tunis, Tunisie.

Computer Methods and Programs in Biomedicine
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Summary

This study estimates bone

Keywords:
Bone ultrastructureElastics propertiesFinite element methodMultiscale modellingNeural network computation

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Area of Science:

  • Biomaterials Science
  • Computational Mechanics
  • Nanotechnology

Background:

  • Bone's hierarchical structure provides exceptional mechanical properties.
  • Understanding multiscale elastic properties is crucial for bone research.
  • Limited studies correlate elastic properties across bone's three nanoscale levels.

Purpose of the Study:

  • To estimate bone's elastic properties using a multiscale approach.
  • To analyze the sensitivity of elastic behavior at each length scale.
  • To develop a novel hybrid multiscale modeling technique.

Main Methods:

  • Hybrid multiscale modeling combining neural network (NN) computations and finite element method (FEM) analysis.
  • NN simulations trained with FEM database results.
  • Parametric analysis of elastic constants and constituent properties.

Main Results:

  • Averaged elastic constants were provided for each length scale.
  • The influence of constituent elastic constants on overall behavior was determined.
  • Parametric analysis revealed key factors affecting bone's elastic properties.

Conclusions:

  • The hybrid multiscale model accurately estimates bone's multiscale elastic properties.
  • Intelligent numerical methods are effective for complex bone tissue modeling.
  • Results align with existing literature values for specific scale levels.