Optimization Strategy for a Shrouded Turbine Blade Using Variable-Complexity Modeling Methodology

This paper presents the development of a collaborative optimization framework in combination with a variable-complexity modeling technique for the multidisciplinary coupling analysis and design of a shrouded turbine blade. The multidisciplinary optimization design of the shrouded turbine blade involves a high-fidelity detailed computational model and medium-fidelity models, which can become prohibitively expensive. In this investigation, a variable-complexity modeling methodology is introduced, where low-fidelity models and a scaling function are used to approximate the medium-and high-fidelity models through the optimizers in an inner-loop optimization to reduce computational expense. The optimization framework developed includes the collaborative optimization process, parametric modeling of the shrouded turbine blade, fluid-structure interaction solver using arbitrary Lagrangian-Eulerian formulation, an adaptive hexahedral structure mesh generator by establishing virtual blocks and parametric fixed points, and a variable-complexity modeling method combining the multiplicative and additive corrections to manage three levels of fidelity models. On the shrouded turbine-blade design problem, it achieves a feasible optimizer only calling nine high-fidelity analyses. Response surface model variation and cross-validation tests are performed to verify the predictive power of the response surface model in the multidisciplinary design optimization process of the shrouded turbine blade.