Computational-Fluid-Dynamics-Based Kriging Optimization Tool for Aeronautical Combustion Chambers

The current state of the art in computational fluid dynamics provides reasonable 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 computational fluid dynamics model with an optimization algorithm to yield a decision-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 industry, 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 multiobjective optimization strategy based on an iteratively enhanced metamodel (kriging) coupled to a design-of-experiments method and a fully parallel three-dimensional computational fluid dynamics solver to model turbulent reacting flows. With this approach, the computer cost needed for thousands of computational fluid dynamics 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 three-dimensional industrial aeronautical combustion chamber demonstrates the approach to be feasible with currently available computing power. One result of the optimization is that possible design changes can improve performance and durability of the studied engine. With the advent of massively parallel architectures, the intersection between these two advanced techniques seems a logical path to yield fully automated decision-making tools for the design of gas turbine engines.