Multidisciplinary uncertainty quantification in aeroelastic analyses of semi-span supersonic transport wing

We present a multidisciplinary uncertainty quantification study through computational static aeroelastic and flutter analyses of the Semi-Span Supersonic Transport (S4T) wing. The aeroelastic solutions of the S4T wing are achieved by using high-fidelity structural and aerodynamic models in a coupled fluid-structure analysis framework. As uncertainty quantification processes require large number of function evaluations due to the variations in random parameters, the computational time requirement rapidly increases if high-fidelity analyses are employed. Thus, utilization of model reduction techniques can be a remedy for the costly uncertainty quantification studies. In this paper, two model reduction techniques such as Polynomial Chaos Expansion and Proper Orthogonal Decomposition are applied to the aeroelastic analyses. These reduced order models are used through Monte Carlo Simulation and Latin Hypercube Sampling techniques. As elasticity modulus, dynamic pressure and angle of attack are chosen to be uncertain design parameters, both structural and aerodynamic uncertainties are propagated in a multidisciplinary analysis framework. Finally, the cumulative distributions of flutter and static aeroelastic output parameters are presented.