contributor author | Townsend, Molly T. | |
contributor author | Mills, Matthew | |
contributor author | Sarigul-Klijn, Nesrin | |
date accessioned | 2024-04-24T22:36:00Z | |
date available | 2024-04-24T22:36:00Z | |
date copyright | 10/3/2023 12:00:00 AM | |
date issued | 2023 | |
identifier issn | 2572-7958 | |
identifier other | jesmdt_007_02_021002.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4295515 | |
description abstract | An approach is presented for calculation verification of geometry-based and voxel-based finite element modeling techniques used for biological hard tissue. The purpose of this study is to offer a controlled comparison of geometry- and voxel-based finite element modeling in terms of the convergence (i.e., discretization based on mesh size and/or element order), accuracy, and computational speed in modeling biological hard tissues. All of the geometry-based numerical test models have hp-converged at an acceptable mesh seed length of 0.6 mm, while not all voxel-based models exhibited convergence and no voxel models p-converged. Converged geometry-based meshes were found to offer accurate solutions of the deformed model shape and equivalent vertebral stiffness, while voxel-based models were 6.35% ± 0.84% less stiff (p < 0.0001) and deformed 6.79% ± 0.96% more (p < 0.0001). Based on the controlled verification study results, the voxel-based models must be confirmed with local values and validation of quantities of interest to ensure accurate finite element model predictions. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Verification Process for Finite Element Modeling Techniques Used in Biological Hard Tissue | |
type | Journal Paper | |
journal volume | 7 | |
journal issue | 2 | |
journal title | Journal of Engineering and Science in Medical Diagnostics and Therapy | |
identifier doi | 10.1115/1.4063302 | |
journal fristpage | 21002-1 | |
journal lastpage | 21002-11 | |
page | 11 | |
tree | Journal of Engineering and Science in Medical Diagnostics and Therapy:;2023:;volume( 007 ):;issue: 002 | |
contenttype | Fulltext | |