Literature DB >> 20236853

Surrogate articular contact models for computationally efficient multibody dynamic simulations.

Yi-Chung Lin1, Raphael T Haftka, Nestor V Queipo, Benjamin J Fregly.   

Abstract

Contact occurs in a wide variety of multibody dynamic systems, including the human musculoskeletal system. However, sensitivity and optimization studies of such systems have been limited by the high computational cost of repeated contact analyses. This study presents a novel surrogate modeling approach for performing computationally efficient three-dimensional elastic contact analyses within multibody dynamic simulations. The approach fits a computationally cheap surrogate contact model to data points sampled from a computationally expensive elastic contact model (e.g., a finite element or elastic foundation model) and resolves several unique challenges involved in applying surrogate modeling techniques to elastic contact problems. As an example application, we performed multibody dynamic simulations of a Stanmore wear simulator machine using surrogate and elastic foundation (EF) contact models of a total knee replacement. Accuracy was assessed by performing eleven dynamic simulations with both types of contact models utilizing large variations in motion and load inputs to the machine. Wear volumes predicted with the surrogate contact models were within 1.5% of those predicted with the EF contact models. Computational speed was assessed by performing five Monte Carlo analyses (over 1000 dynamic simulations each) with surrogate contact models utilizing realistic variations in motion and load inputs. Computation time was reduced from an estimated 284 h per analysis with the EF contact models to 1.4 h with the surrogate contact models (i.e., 17 min vs. 5 s per simulation), with higher wear sensitivity observed for motion variations than for load variations. The proposed surrogate modeling approach can significantly improve the computational speed of multibody dynamic simulations incorporating three-dimensional elastic contact models with general surface geometry. Copyright 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20236853     DOI: 10.1016/j.medengphy.2010.02.008

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  5 in total

1.  Grand challenge competition to predict in vivo knee loads.

Authors:  Benjamin J Fregly; Thor F Besier; David G Lloyd; Scott L Delp; Scott A Banks; Marcus G Pandy; Darryl D D'Lima
Journal:  J Orthop Res       Date:  2011-12-12       Impact factor: 3.494

2.  A methodology to accurately quantify patellofemoral cartilage contact kinematics by combining 3D image shape registration and cine-PC MRI velocity data.

Authors:  Bhushan S Borotikar; William H Sipprell; Emily E Wible; Frances T Sheehan
Journal:  J Biomech       Date:  2012-01-28       Impact factor: 2.712

3.  An Open-Source Toolbox for Surrogate Modeling of Joint Contact Mechanics.

Authors:  Ilan Eskinazi; Benjamin J Fregly
Journal:  IEEE Trans Biomed Eng       Date:  2015-07-13       Impact factor: 4.538

4.  Surrogate modeling of deformable joint contact using artificial neural networks.

Authors:  Ilan Eskinazi; Benjamin J Fregly
Journal:  Med Eng Phys       Date:  2015-07-26       Impact factor: 2.242

Review 5.  Articular Contact Mechanics from an Asymptotic Modeling Perspective: A Review.

Authors:  Ivan Argatov; Gennady Mishuris
Journal:  Front Bioeng Biotechnol       Date:  2016-11-01
  5 in total

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