  We demonstrate an adaptive sampling approach for computing the probability of
a rare event for a set of three-dimensional airplane geometries under various
flight conditions. We develop a fully automated method to generate
parameterized airplanes geometries and create volumetric mesh for viscous CFD
solution. With the automatic geometry and meshing, we perform the adaptive
sampling procedure to compute the probability of the rare event. We show that
the computational cost of our adaptive sampling approach is hundreds of times
lower than a brute-force Monte Carlo method.
