Application of an interface failure model to predict fatigue crack growth in an implanted metallic femoral stem

Jiye Chen, M. Browne, M. Taylor, P. J. Gregson

Research output: Contribution to journalArticlepeer-review

Abstract

A novel computational modelling technique has been developed for the prediction of crack growth in load bearing orthopaedic alloys subjected to fatigue loading. Elastic/plastic fracture mechanics has been used to define a three-dimensional fracture model, which explicitly models the opening, sliding and tearing process. This model consists of 3D nonlinear spring elements implemented in conjunction with a brittle material failure function, which is defined by the fracture energy for each nonlinear spring element. Thus, the fracture energy criterion is implicit in the brittle material failure function to search for crack initiation and crack development automatically. A degradation function is employed to reduce interfacial fracture properties corresponding to the number of cycles; thus fatigue lifetime can be predicted. Unlike other failure modelling methods, this model predicts the failure load, crack path and residual stiffness directly without assuming any pre-flaw condition.As an example, fatigue of a cobalt based alloy (CoCrMo) femoral stem is simulated. Experimental fatigue data was obtained from four point bending tests. The finite element model simulated a fully embedded implant with a constant point load. Comparison between the model and mechanical test results showed good agreement in fatigue crack growth rate.
Original languageEnglish
Pages (from-to)249-256
Number of pages8
JournalComputer Methods and Programs in Biomedicine
Volume73
Issue number3
Publication statusPublished - Mar 2004

Keywords

  • Interface failure model
  • Degradation function
  • Fatigue crack growth
  • Finite element
  • Hip implant

Fingerprint

Dive into the research topics of 'Application of an interface failure model to predict fatigue crack growth in an implanted metallic femoral stem'. Together they form a unique fingerprint.

Cite this