Date of Award

Fall 11-21-2025

Document Type

Masters Thesis

Degree Name

M.S. in Mechanical Engineering

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Mechanical and Materials Engineering

First Advisor

Peter J. Laz

Second Advisor

Casey Myers

Third Advisor

Martin Rhodes

Copyright Statement / License for Reuse

All Rights Reserved
All Rights Reserved.

Keywords

Computational modeling of the knee, Finite element modeling (FEM), Knee kinematics, Model credibility, Model reproducibility

Abstract

Computational modeling of knee joint biomechanics can provide valuable insights into joint function, injury mechanisms, and patient outcomes, and can support surgical planning and informed clinical decision-making. However, achieving consistent and repeatable results, or reproducibility, is a significant challenge that affects the credibility of these models. This thesis addresses reproducibility through two studies related to the KneeHub Project, which is a multi-institutional collaboration designed to investigate reproducibility in finite-element modeling of the knee.

The first study involved model benchmarking, where predicted results of the calibrated models were compared with the experimental data to evaluate model reproducibility. While all models replicated key experimental trends in joint kinematics and kinetics, discrepancies arose from differences in ligament representation, coordinate system definitions, and calibration strategies. Errors of up to 6.6 ± 2.4 mm in anteriorposterior (AP) translation to 13.5 ± 12.9˚ in internal-external (IE) rotation were observed. Variability in the approaches used highlights the subjectivity inherent in modeling, even when using the same data and goals.

The second study implemented a consensus workflow that was developed by the KneeHub community in an effort to improve reproducibility and credibility in the modeling process. This workflow was developed to study ACL injury, repair, and potential post-injury outcomes, highlighting the importance of having a clear context of use. The model developed by following the steps in the consensus workflow successfully captured physiological behaviors, like posterior femoral rollback during deep flexion. Simulations of anterior-posterior laxity and passive flexion showed numerical stability, confirming model robustness. A sensitivity analysis indicated that precise calibration of ligament slack-length and a high-quality geometric representation of the cartilage anatomy are more critical for accurate predictions on knee kinematics than variations in stiffness or mesh density.

Overall, this work supports the notion that a community-based consensus workflow can enhance reproducibility and predictive capability in knee joint modeling, contributing to credible computational biomechanics and supporting future studies, model calibration, and clinical applications.

Copyright Date

11-2025

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Maryam Nazem

Provenance

Received from ProQuest

File Format

application/pdf

Language

English (eng)

Extent

202 pgs

File Size

6.8 MB

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