Designing for Turbine Housing Weight Reduction Using Thermal Fatigue Crack Propagation Prediction Technology 2019-01-0533

Turbine housings in car engine turbochargers, which use costly stainless steel castings, account for nearly 50% of the parts cost of a turbocharger. They are also the component which controls the competitiveness of the turbocharger, in terms of both function and cost. In this research, focusing on thermal fatigue resistance which is one of the main functions demanded of a turbine housing, achieving reduction in wall thickness while securing sufficient thermal fatigue resistance, it is possible to reduce the amount of material used in the turbine housing and aimed for cost reduction. Therefore, we built a method to quantitatively predict, using 3D FEM, the lifespan from the initiation of thermal fatigue cracking to the formation of a penetrating crack which leads to gas leakage. This prediction method uses the Abaqus general-purpose nonlinear analysis software from Dassault Systèmes, and produced a low-cycle fatigue analysis by the direct cyclic algorithm, by identifying the parameters for analysis from the results of RIG tests, which applied hot-cold cycle loads. In addition, we reduced the analysis time by using submodel analysis with only the model near the evaluation part cut out. By combining the crack propagation prediction technology using CAE, which was built in this research, with existing shape optimization software, we were able to produce designs which reduced turbine housing mass by 10% or more, while maintaining thermal fatigue resistance.