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桡骨段弹塑性行为预测:基于损伤的非线性细观有限元模拟与 Pistoia 准则比较。

Prediction of the Inelastic Behaviour of Radius Segments: Damage-based Nonlinear Micro Finite Element Simulation vs Pistoia Criterion.

机构信息

Institute of Lightweight Design and Structural Biomechanics, TU Wien, Austria.

ARTORG Center for Biomedical Engineering Research, University of Bern, Switzerland.

出版信息

J Biomech. 2021 Feb 12;116:110205. doi: 10.1016/j.jbiomech.2020.110205. Epub 2021 Jan 2.

DOI:10.1016/j.jbiomech.2020.110205
PMID:33476984
Abstract

The Pistoia criterion (PC) is widely used to estimate the failure load of distal radius segments based on linear micro Finite Element (μFE) analyses. The advantage of the PC is that a simple strain-threshold and a tissue volume fraction can be used to predict failure properties. In this study, the PC is compared to materially nonlinear μFE analyses, where the bone tissue is modelled as an elastic, damageable material. The goal was to investigate for which outcomes the PC is sufficient and when a nonlinear (NL) simulation is required. Three types of simulation results were compared: (1) prediction of the failure load, (2) load sharing of cortical and trabecular regions, and (3) distribution of local damaged/overstrained tissue at the maximum sustainable load. The failure load obtained experimentally could be predicted well with both the PC and the NL simulations using linear regression. Although the PC strongly overestimated the failure load, it was sufficient to predict adequately normalized apparent results. An optimised PC (oPC) was proposed which uses experimental data to calibrate the individual volume of overstrained tissue. The main areas of local over-straining predicted by the oPC were the same as estimated by the NL simulation, although the oPC predicted more diffuse regions. However, the oPC relied on an individual calibration requiring the experimental failure load while the NL simulation required no a priori knowledge of the experimental failure load.

摘要

Pistoia 标准(PC)广泛用于根据线性微有限元(μFE)分析来估计桡骨远端段的失效载荷。PC 的优点在于可以使用简单的应变阈值和组织体积分数来预测失效特性。在这项研究中,PC 与材料非线性 μFE 分析进行了比较,其中骨组织被建模为弹性、可损坏的材料。目的是研究 PC 在哪些情况下足够,以及何时需要非线性(NL)模拟。比较了三种类型的模拟结果:(1)失效载荷的预测,(2)皮质和小梁区域的载荷分配,以及(3)最大可持续载荷下局部受损/过度应变组织的分布。使用线性回归,实验获得的失效载荷可以很好地用 PC 和 NL 模拟来预测。尽管 PC 严重高估了失效载荷,但足以充分预测归一化的表观结果。提出了一种优化的 PC(oPC),它使用实验数据来校准个体过度应变组织的体积。oPC 预测的局部过度应变的主要区域与 NL 模拟相同,尽管 oPC 预测了更弥散的区域。然而,oPC 依赖于需要实验失效载荷的个体校准,而 NL 模拟则不需要实验失效载荷的先验知识。

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