Methodology Development for Topology Optimization of Power Transfer Unit Housing Structures

University essay from KTH/Skolan för industriell teknik och management (ITM)

Abstract: Simulation driven design is a method and process that has been developed over many years, and with today’s advanced software, the possibility to embed simulation into the design process has become a reality. The advantages of using simulation driven design in the product development process is well known and compared to a more traditional design process, the simulation driven design process can give the user the possibility to explore, optimize and design products with reduced lead time.  One of the methods that is applied in simulation driven design is the use of topology optimization (structural optimization). Topology optimization is something that GKN uses in the design process. Due to the complexity of the products GKN design and manufacture, the output from the topology optimization lacks good design interpretability and the design process requires a lot of time and effort.  The purpose of the thesis is to explore different simulation tools used for topology optimization and improve the methodology and process with higher design interpretability for a static topology optimization. This requires a good understanding of the component and the product development process. It is imperative that the topology result must have high design interpretability, and the visualization of the result must show the formation of clear rib structures.  The software’s used for performing topology optimization in this thesis are Inspire, SimLab, HyperMesh, and OptiStruct (HyperWorks suite). Static topology optimization is conducted, and manufacturing constraints for the casting process are considered. The methodology developed is robust for similar gearbox housing structures, and the process is set up to be efficient. The proposed method is verified by implementing it on a housing structure.  The resulting concept from the topology optimization is deemed to have higher design interpretability which improves knowledge transfer in the design process when compared to the current topology results. The weight of the product is reduced, and a more optimum design is reached with a lesser number of iterations.

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