Bies, Jeffrey2023-11-282023-11-282023https://hdl.handle.net/11299/258683University of Minnesota Ph.D. dissertation. 2023. Major: Mechanical Engineering. Advisor: William Durfee. 1 computer file (PDF); vii, 199 pages.This dissertation focuses on the application of thermal-fluid-structure topology optimization to small-scale hydraulic systems for robotic exoskeletons. The primary goal was to develop optimization capabilities that can simultaneously consider fluid flow, heat transfer, and structural integrity under external loads while optimizing the design of these systems. The optimization methodology is based on the continuous adjoint method and the method of moving asymptotes and was implemented using the open-source computational fluid dynamics software OpenFOAM. The optimization approach was demonstrated through a series of two-dimensional case studies as well as a three-dimensional hydraulic system in a medical robotic exoskeleton focused on the knee-to-ankle region. The results show that topology optimization leads to significant improvements in the performance and efficiency of small-scale hydraulic systems. By optimizing for fluid flow, heat transfer, and structural integrity, the optimized designs are able to achieve a balance between thermal dissipation, structural strength, and pressure drop, resulting in designs that outperform traditional designs in terms of performance and efficiency. This work demonstrates how topology optimization can revolutionize the design and optimization of small-scale hydraulic systems.encontinuous adjoint methodhydraulicmulti-objective optimizationmulti-physicsOpenFOAMtopology optimizationThesis or Dissertation