Design Optimization Methods for Improving HPT Vane Pressure Side Cooling Properties Using Genetic Algorithms and Efficient CFD

Abstract

Typical modern-day high pressure turbine (HPT) durability design methods in industry utilize dated correlations and spreadsheet methods based on “rules of thumb”. Of the over 2,700 film cooling references in existence, no known efforts have been made towards an optimized overall film cooling design for a realistic HPT vane geometry in proper flow conditions. Nor has there been a major attempt in open literature to improve component cooling design methods in general. This work invests greater effort in the design and optimization of a HPT vane film cooling array by way of considering numerous configurations, variables, and variable value ranges within the design space. Cooling hole surface location, size, injection orientation, and row patterns are varied in the design space. Optimization occurs by way of Latin hypercube sampling (LHS) and multi-objective genetic algorithms (GAs) to maximize the cooling effectiveness and minimize area-averaged heat transfer over the pressure surface (PS) of a baseline nozzle guide vane currently being tested experimentally within a full-scale blowdown facility. Full-map PS heat transfer predictions from 3-D computational fluid dynamics (CFD) simulations that efficiently approximate the cooling hole physics are used with prescribed fitness functions to arrive at a much improved PS cooling array design. 1,300 cooling designs were evaluated within design-space exploration that allows an extremely high number (0.32 x 10 552 ) of cooling array possibilities.