Surrogate articular contact models for computationally efficient multibody dynamic simulations

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

doi:10.1016/j.medengphy.2010.02.008

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Volume 32, Issue 6 , Pages 584-594, July 2010

Surrogate articular contact models for computationally efficient multibody dynamic simulations

Yi-Chung Lin
- Department of Mechanical & Aerospace Engineering, University of Florida, Gainesville, FL, USA
Raphael T. Haftka
- Department of Mechanical & Aerospace Engineering, University of Florida, Gainesville, FL, USA
Nestor V. Queipo
- Applied Computing Institute, University of Zulia, Maracaibo, Venezuela
Benjamin J. Fregly
- Department of Mechanical & Aerospace Engineering, University of Florida, Gainesville, FL, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
- Department of Orthopaedics and Rehabilitation, University of Florida, Gainesville, FL, USA
- Corresponding author at: Department of Mechanical & Aerospace Engineering, 231 MAE-A Building, PO Box 116250, University of Florida, Gainesville, FL 32611-6250, USA. Tel.: +1 352 392 8157; fax: +1 352 392 7303.

Received 16 July 2009; received in revised form 8 February 2010; accepted 10 February 2010. published online 17 March 2010.

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 284h per analysis with the EF contact models to 1.4h with the surrogate contact models (i.e., 17min vs. 5s 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.