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• W3107890991 endingPage "105870" @default.
• W3107890991 startingPage "105870" @default.
• W3107890991 abstract "Finite element models built from micro-computed tomography scans have become a powerful tool to investigate the mechanical properties of trabecular bone. There are two types of solving algorithms in the finite element method: implicit and explicit. Both of these methods have been utilized to study the trabecular bone. However, an investigation comparing the results obtained using the implicit and explicit solvers is lacking. Thus, in this paper, we contrast implicit and explicit procedures by analyzing trabecular bone samples as a case study. Micro-computed tomography-based finite element analysis of trabecular bone under a direct quasi-static compression was done using implicit and explicit methods. The differences in the predictions of mechanical properties and computational time of the two methods were studied using high-performance computing. Our findings indicate that the results using implicit and explicit solvers are well comparable, given that similar problem set up is carefully utilized. Also, the parallel scalability of the two methods was similar, while the explicit solver performed about five times faster than the implicit method. Along with faster performance, the explicit method utilized significantly less memory for the analysis, which shows another benefit of using an explicit solver for this case study. The comparison of the implicit and explicit methods for the simulation of trabecular bone samples should be highly valuable to the bone modeling community and researchers studying complex cellular and architectured materials." @default.
• W3107890991 created "2020-12-07" @default.
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• W3107890991 date "2021-03-01" @default.
• W3107890991 modified "2023-10-16" @default.
• W3107890991 title "High-Performance Computing Comparison of Implicit and Explicit Nonlinear Finite Element Simulations of Trabecular Bone" @default.
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• W3107890991 doi "https://doi.org/10.1016/j.cmpb.2020.105870" @default.
• W3107890991 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33280935" @default.
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