Team, Visitors, External Collaborators
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Section: New Results

Application of Uncertainty Quantification studies to fluid-dynamics problems

Multi-fidelity surrogate-based optimization of transonic and supersonic axial turbines profiles

N. Razaaly, G. Persico, P.M. Congedo

This study presents a multifidelity surrogate-based approach for the optimization of the LS89 high pressure axial turbine vane to significantly reduce the computational cost associated to high fidelity CFD simulations while exploiting models of lower fidelity. A cokriging method is used to simultaneously take into account quantities of interest (QoI) coming from models of different fidelities providing a global surrogate model. A classic bayesian global optimization method permits to iteratively propose desing of interest. It relies on the maximization of the so-called Expected Improvement criterion. A geometrical parametrization technique based on B-splines is considered to describe the profile geometry. The mass-flow rate and the outlet angle are constrained. The optimization study reveals significant reduction in computational cost w.r.t. classic optimization frameworks based on a single fidelity, such as, adjoint-based and gradient-free methods, while providing similar improvements in term of fitness functions [23].