Comparison of two methods for probabilistic finite element analysis of total knee replacement
Comparison of two methods for probabilistic finite element analysis of total knee replacement
Probabilistic Finite Element (FE) models have recently been developed to assess the impact of experimental variability present in knee wear simulator on predicted Total Knee Replacement (TKR) mechanics by determining the performance envelope of joint kinematics and contact mechanics. The gold standard for this type of analysis is currently the Monte Carlo method, however, this requires a larger number of trials and is therefore computationally expensive. Alternatively, probabilistic methods exist, such as response surface methods that can offer considerable savings in computational cost. The aim of the current study was to compare the performance envelopes obtained for three metrics (Anterior-Posterior (AP) translation, Internal-External (IE) rotation and peak Contact Pressure (CP)) for a FE model of TKR mechanics using two different probabilistic methods: the Monte Carlo technique and the Response Surface Method (RSM), implemented with PamCrash FE solver and PamOpt optimization/probabilistic software. The influence of implant alignment was considered, based on a study from the literature. The results of a 1000 trial Monte Carlo analysis were compared to predictions from 25, 50 and 100 trial response surface calculations. Overall, the Response Surface Method (RSM) was capable of predicting similar results to the Monte Carlo method, but with a substantially reduced computational cost (RSM-50 4 hours as compared to 4 days with the Monte Carlo method)
Arsene, C.T.C.
82a43866-2104-4cbf-bde3-2789cdbb7818
Strickland, M.A.
605405d5-e9e9-434e-a092-5a4565a34e9b
Laz, P.J.
68340f4f-ddf3-4801-9668-fb6d9b957e83
Taylor, M
e368bda3-6ca5-4178-80e9-41a689badeeb
2008
Arsene, C.T.C.
82a43866-2104-4cbf-bde3-2789cdbb7818
Strickland, M.A.
605405d5-e9e9-434e-a092-5a4565a34e9b
Laz, P.J.
68340f4f-ddf3-4801-9668-fb6d9b957e83
Taylor, M
e368bda3-6ca5-4178-80e9-41a689badeeb
Arsene, C.T.C., Strickland, M.A., Laz, P.J. and Taylor, M
(2008)
Comparison of two methods for probabilistic finite element analysis of total knee replacement.
8th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, Porto, Portugal.
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Conference or Workshop Item
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Abstract
Probabilistic Finite Element (FE) models have recently been developed to assess the impact of experimental variability present in knee wear simulator on predicted Total Knee Replacement (TKR) mechanics by determining the performance envelope of joint kinematics and contact mechanics. The gold standard for this type of analysis is currently the Monte Carlo method, however, this requires a larger number of trials and is therefore computationally expensive. Alternatively, probabilistic methods exist, such as response surface methods that can offer considerable savings in computational cost. The aim of the current study was to compare the performance envelopes obtained for three metrics (Anterior-Posterior (AP) translation, Internal-External (IE) rotation and peak Contact Pressure (CP)) for a FE model of TKR mechanics using two different probabilistic methods: the Monte Carlo technique and the Response Surface Method (RSM), implemented with PamCrash FE solver and PamOpt optimization/probabilistic software. The influence of implant alignment was considered, based on a study from the literature. The results of a 1000 trial Monte Carlo analysis were compared to predictions from 25, 50 and 100 trial response surface calculations. Overall, the Response Surface Method (RSM) was capable of predicting similar results to the Monte Carlo method, but with a substantially reduced computational cost (RSM-50 4 hours as compared to 4 days with the Monte Carlo method)
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Published date: 2008
Venue - Dates:
8th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering, Porto, Portugal, 2008-01-01
Organisations:
Bioengineering Group
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Local EPrints ID: 202737
URI: http://eprints.soton.ac.uk/id/eprint/202737
PURE UUID: d4077556-6b80-4ee8-b610-64028fc9180f
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Date deposited: 09 Nov 2011 14:00
Last modified: 14 Mar 2024 04:25
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Author:
C.T.C. Arsene
Author:
M.A. Strickland
Author:
P.J. Laz
Author:
M Taylor
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