Computational-Fluid-Dynamics-Based Kriging Optimization Tool for Aeronautical Combustion Chambers
Florent Duchaine, Thierry Morel, Laurent Y. M. Gicquel · AIAA Journal · 2009
Current state-of-the-art in Computational Fluid Dynamics (CFD) provides rea-sonable reacting flow predictions and is already used in industry to evaluate new concepts of gas turbine engines. In parallel, optimization techniques have reached maturity and several industrial activities benefit from enhanced search algorithms. However, coupling a physical model with an optimization algorithm to yield a deci-sion making tool, needs to be undertaken with care to take advantage of the current computing power while satisfying the gas turbine industrial constraints. Among the many delicate issues for such tools to contribute efficiently to the gas turbine indus-try, combustion is probably the most challenging and optimization algorithms are not easily applicable to such problems. In our study, a fully encapsulated algorithm addresses the issue by making use of a new multi-objective optimization strategy based on an iteratively enhanced meta-model (Kriging) coupled to a Design of Ex-periments (DoE) method and a fully parallel three dimensional (3D) CFD solver to model turbulent reacting flows. With this approach, the computer cost needed for thousands of CFD computations is greatly reduced while ensuring an automatic error reduction of the approximated response function. Preliminary assessments of the search algorithm against simple analytical test functions prove the strategy to be efficient and robust. Application to a 3D industrial aeronautical combustion chamber demonstrates the approach to be feasible with currently available com-puting power. One result of the optimization is that possible design changes can improve performance and durability of the studied engine. With the advent of