Abstract The present chapter aims at providing first guidelines for the application of uncertainty quantification method to robust design in industrial problems exhibiting complex physics. The first part of this chapter is dedicated to the exploitation of UQ-based techniques to predict the risk of occurrence of combustion instabilities in aeronautic engines. Combustion is by nature a multiphysics problem including fluid mechanics, chemistry and heat transfer. Including UQ in such complex applications requires to reduce the problem solve to reduced order models accounting for the main phenomena implying a limited number of parameters. Within the project, reduced order models have been developed at CERFACS for combustion–acoustic interactions, allowing the introduction of UQ in the field of combustion instabilities. This chapter therefore focuses on this specific application and paves the way towards the use of UQ techniques for combustor robust design. A second part is dedicated to efficient UQ and RDO for aero-engine acoustic liners. Preliminary designing of acoustic liners is by nature a multiobjective problem due to different flight conditions prescribed by certification authorities. The number of uncertainties was limited to the geometrical variables that most influence the acoustic impedance according to the proprietary semi-empiric model exploited in the mathematical representation of the nacelle modelled into finite element code MSC Actran, which is used to conduct computational aero-acoustic simulations. The Adaptive Sparse Polynomial Chaos method has been used for an efficient UQ, allowing the reduction of the terms, rather than the reduction of the variables, retaining accuracy by avoiding overfitting. A single-objective reliability-based formulation is successfully applied with SIMPLEX and MOGAII algorithm for efficient RDO.


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