A multiscale predictor/corrector scheme for efficient elastoplastic voxel finite element analysis, with application to CT-based bone strength prediction

Lam H. Nguyen, Dominik Schillinger

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Voxel finite elements combined with plasticity have been shown to accurately predict the evolution of bone failure, but involve a prohibitive computational cost when applied to high-resolution CT scans of a complete bone. We present a simple multiscale predictor/corrector scheme that uses elasticity and the finite cell method on a coarse-scale mesh, complemented by plasticity and fine-scale voxel finite elements in regions where failure occurs. The core components of our method are top-down displacement and bottom-up stress projectors for the exchange of information between coarse and fine scales. Our choice of projectors eliminates communication of fine-scale voxel elements beyond boundaries of coarse-scale cells, which enables the solution in terms of a series of small uncoupled systems at a fraction of the computing power and memory required by the fully coupled fine-scale system. At the same time, we illustrate that the multiscale approach yields the same accuracy as the full-resolution voxel finite element method, if we appropriately balance the approximation power of coarse-scale and fine-scale meshes. We demonstrate the advantages of our method for the load capacity analysis of a patient-specific vertebra.

Original languageEnglish (US)
Pages (from-to)598-628
Number of pages31
JournalComputer Methods in Applied Mechanics and Engineering
Volume330
DOIs
StatePublished - Mar 1 2018

Bibliographical note

Funding Information:
L.H. Nguyen is supported by a Doctoral Dissertation Fellowship awarded by the University of Minnesota for the academic year 2017–2018, which is gratefully acknowledged. D. Schillinger gratefully acknowledges support from the National Science Foundationvia the NSF grant CISE-1565997 and the NSF CAREER Award No. 1651577 . The authors also acknowledge the Minnesota Supercomputing Institute (MSI) of the University of Minnesota for providing computing resources that have contributed to the research results reported within this paper ( https://www.msi.umn.edu/ ). The authors are grateful to Thomas Baum and Jan S. Kirschke (Dept. of Neuroradiology, Technische Universität München, Germany) for providing access to the medical imaging data of the vertebra.

Funding Information:
L.H. Nguyen is supported by a Doctoral Dissertation Fellowship awarded by the University of Minnesota for the academic year 2017–2018, which is gratefully acknowledged. D. Schillinger gratefully acknowledges support from the National Science Foundationvia the NSF grant CISE-1565997 and the NSF CAREER Award No. 1651577. The authors also acknowledge the Minnesota Supercomputing Institute (MSI) of the University of Minnesota for providing computing resources that have contributed to the research results reported within this paper (https://www.msi.umn.edu/). The authors are grateful to Thomas Baum and Jan S. Kirschke (Dept. of Neuroradiology, Technische Universität München, Germany) for providing access to the medical imaging data of the vertebra.

Publisher Copyright:
© 2017 Elsevier B.V.

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

Keywords

  • Bone strength prediction
  • Finite cell method
  • Multiscale predictor/corrector scheme
  • Parallel computing
  • Plasticity
  • Voxel finite element method

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