Uncertainty quantification (UQ) for multi physics problems like fluid-structure interaction is challenging in terms of the computational cost and efficiency. Sampling algorithms like Monte-Carlo is not feasible for these complex problems due to the constrains in computational time and cost. Random geometry variation arises due to manufacturing tolerances, icing, wear and tear during operation etc. Quantification of these geometric uncertainties is challenging due to the large number of geometric parameters resulting in a high dimensional stochastic problem. A two step UQ using the gradient information obtained by solving the adjoint equation is employed in the current study.     «

Uncertainty quantification (UQ) for multi physics problems like fluid-structure interaction is challenging in terms of the computational cost and efficiency. Sampling algorithms like Monte-Carlo is not feasible for these complex problems due to the constrains in computational time and cost. Random geometry variation arises due to manufacturing tolerances, icing, wear and tear during operation etc. Quantification of these geometric uncertainties is challenging due to the large number of geometric...     »