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Multiscale Computer Modeling in Biomechanics and Biomedical Engineering pp 3–30Cite as

Application of Neural Network and Finite Element Method for Multiscale Prediction of Bone Fatigue Crack Growth in Cancellous Bone

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Part of the book series: Studies in Mechanobiology, Tissue Engineering and Biomaterials ((SMTEB,volume 14))

Abstract

Fatigue damage in bone in the form of microcracks results from the repetitive loading of daily activities. It is well known that the resistance of bone at the organ level to fatigue fracture is a function of its resistance to the initiation and propagation of local microcracks at a mesoscopic scale which can lead to macrocrack growth at the organ level. Multiscale investigation of the relationship between the effect of the fatigue microcrack growth at microscopic scales and the whole bone behaviour is a subject of great interest in the research field of the biomechanics of human bone. Several finite element models (FE) have been developed in recent years in order to provide better insight and description regarding bone fatigue microcrack growth. Despite the progress in this field, there is still a lack of models integrating multiscale approaches to assess the accumulation of apparent fatigue microcracks in relation with trabecular architecture into practical FE simulations. In this chapter, a trabecular bone multiscale model based on FE simulation and neural network (NN) computation is presented to simulate the accumulation of trabecular bone crack density and crack length at a given trabecular bone site during cyclic loading. The FE calculation is performed at macroscopic level and a trained NN incorporated into a FE code is employed as a numerical device to perform the local mesoscopic computation (the behaviour law needed to compute the outputs at mesoscale is substituted by the trained NN). The input data for the NN are some trabecular morphological and material factors, the applied stress and cycle frequency. The output data are the average crack density and length computed at a given trabecular bone site.

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Acknowledgments

This work was supported by the French National Research Agency (ANR) through TecSan program (Project MoDos, no. ANR-09-TECS-018). The authors are grateful to Dr Loulou H. for providing the micro-CT trabecular bone meshes.

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Authors and Affiliations

  1. Prisme Institute – MMH , 8, Rue Léonard de Vinci, 45072, Orleans Cedex 2, France

    Ridha Hambli

  2. ISTO, UMR 7327 - CNRS/Université d’Orléans, Campus Géosciences,1A, rue de la Férollerie, 45071, Orleans Cedex 2, France

    Nour Hattab

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  1. Ridha Hambli
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  2. Nour Hattab
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Correspondence to Ridha Hambli .

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Editors and Affiliations

  1. Tel Aviv University, Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv, 69978, Israel

    Amit Gefen

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Hambli, R., Hattab, N. (2013). Application of Neural Network and Finite Element Method for Multiscale Prediction of Bone Fatigue Crack Growth in Cancellous Bone. In: Gefen, A. (eds) Multiscale Computer Modeling in Biomechanics and Biomedical Engineering. Studies in Mechanobiology, Tissue Engineering and Biomaterials, vol 14. Springer, Berlin, Heidelberg. https://doi.org/10.1007/8415_2012_146

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  • DOI: https://doi.org/10.1007/8415_2012_146

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