Publication Date
Summer 2019
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mechanical Engineering
Advisor
Winncy Y. Du
Keywords
articular cartilage, computational elbow joint model, elbow joint motion, fluid-structure interaction, human elbow joint, synovial fluid
Subject Areas
Mechanical engineering; Biomedical engineering; Biomechanics
Abstract
While significant advances have been made in the development of computational elbow joint models, fluid-structure interaction (FSI) in the elbow joint has not yet been explored. The objective of this study is to develop a computational elbow joint model to simulate the effects of synovial fluid on articular cartilage during flexion, extension, pronation, and supination. The model was developed with anatomically accurate 3D bone geometries; articular cartilage geometries that were derived from the 3D bone geometries; ligaments defined as linear springs; muscles embedded as joint non-linear stiffness; and a fluid domain that encompassed the joint articulations with a homogenous, incompressible, Newtonian synovial fluid. Two FSI simulations with varying joint velocities were conducted for elbow flexion, extension, pronation, and supination each. Peak von Mises stress of 0.0073 MPa on proximal ulna articular cartilage and peak von Mises stress of 0.0085 MPa on proximal radius articular cartilage were recorded during flexion-extension and pronation-supination, respectively. Synovial fluid flow was found to be predominantly laminar for the slower joint velocity and turbulent for the faster joint velocity for all elbow joint motions. This model not only establishes a validated approach to developing FSI simulations in the elbow joint, but also presents information on crucial in vivo parameters such as articular cartilage stresses and synovial fluid flow patterns during joint motion.
Recommended Citation
Yellapragada, Abhishek, "Development of a Computational Elbow Joint Model to Analyze the Effects of Synovial Fluid on Articular Cartilage during Joint Motion" (2019). Master's Theses. 5052.
DOI: https://doi.org/10.31979/etd.xtd3-epyv
https://scholarworks.sjsu.edu/etd_theses/5052