Finite element-based probabilistic analysis tool for orthopaedic applications

Sarah K. Easley, Saikat Pal, Paul R. Tomaszewski, Anthony J. Petrella, Paul J. Rullkoetter, Peter J. Laz

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

Orthopaedic implants, as well as other physical systems, contain inherent variability in geometry, material properties, component alignment, and loading conditions. While complex, deterministic finite element (FE) models do not account for the potential impact of variability on performance, probabilistic studies have typically predicted behavior from simplified FE models to achieve practical solution times. The objective of this research was to develop an efficient and versatile probabilistic FE tool to quantify the effect of uncertainty in the design variables on the performance of orthopaedic components under relevant conditions. Key aspects of the computational tool developed include parametric and automated FE model creation for changes in dimensional variables, efficient solution using the advanced mean-value (AMV) reliability method, and identification of the most significant design variables. Two orthopaedic applications are presented to demonstrate the ability of the computational tool to efficiently and accurately represent component performance.

Original languageEnglish (US)
Pages (from-to)32-40
Number of pages9
JournalComputer Methods and Programs in Biomedicine
Volume85
Issue number1
DOIs
StatePublished - Jan 2007
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Health Informatics

Keywords

  • Finite element modeling
  • Orthopaedic implants
  • Probabilistic modeling
  • Reliability
  • Sensitivity
  • Variability

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