Title
Cavity Detection In Biomechanics By An Inverse Evolutionary Point Load Bem Technique
Keywords
Boundary element method (BEM); Cavity detection; Elastostatics; Genetic algorithm
Abstract
An efficient solution of the inverse geometric problem for cavity detection using a point load superposition technique in the elastostatics boundary element method (BEM) is presented in this article. A superposition of point load clusters technique is used to simulate the presence of cavities. This technique offers tremendous advantages in reducing the computational time for the elastostatics field solution as no boundary re-discretization is necessary throughout the inverse problem solution process. The inverse solution is achieved in two steps: (1) fixing the location and strengths of the point loads, (2) locating the cavity geometry. For a current estimated point load distribution, a first objective function measures the difference between BEM-computed and measured deformations at selected points. A genetic algorithm is employed to automatically alter the locations and strengths of the point loads to minimize the objective function. Upon convergence, a second objective function is defined to locate the cavity geometry modelled as traction-free surface. Results of cavity detection simulations using numerical experiments and simulated random measurement errors validate the approach in regular and irregular geometrical configurations.
Publication Date
12-1-2008
Publication Title
Inverse Problems in Science and Engineering
Volume
16
Issue
8
Number of Pages
981-993
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1080/17415970802082914
Copyright Status
Unknown
Socpus ID
55849084668 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/55849084668
STARS Citation
Ojeda, David; Divo, Eduardo; Kassab, Alain; and Cerrolaza, Miguel, "Cavity Detection In Biomechanics By An Inverse Evolutionary Point Load Bem Technique" (2008). Scopus Export 2000s. 9771.
https://stars.library.ucf.edu/scopus2000/9771