Hybrid Large-Eddy Simulation Optimization of a Fundamental Turbine Blade Turbulated Cooling Passage

摘要

An efficient methodology for shape optimization based on computational fluid dynamics is developed and applied to a fundamental turbulated square duct The present study uses a hybrid large-eddy simulation turbulence modeling approach for all computational fluid dynamics evaluation, as it is shown to give much more reh'able results over a range of geometries. Four geometric parameters defining the cross-sectional profile and angle of the turbulators were optimized for two competing performance metrics: heat transfer and pressure drop. An initial database of computational fluid dynamics runs, sampled from the design space using a space-filling design of experiments, is used as a starting point A metamodel is then fitted through the training data in the database. The metamodel provides the means for fast approximation of the objective functions at new design points, allowing the use of a genetic algorithm for this multiobjecti ve optimization. The resulting Pareto front is verified with a second round of computational fluid dynamics evaluations at the end. The optimization demonstrates the potential for improvement in thermal performance when using turbulators with an upstream ramp. Various metamodels are also explored for their ability to deal with design space nonlinearity and noisy data.