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

Abstract

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.