A High Performance Computing and Sensitivity Analysis Algorithm for Stochastic Many-Particle Wave Scattering

We present a high performance computing framework for quantifying uncertainties in the propagation of acoustic waves through a stochastic media comprising a large number of three-dimensional particles. We subsequently describe an efficient postprocessing approach using our framework to statistically quantify the sensitivity of the uncertainties with respect to input parameters that govern the stochasticity in the model. The stochasticity arises through the random positions and orientations of the component particles in the media. Simulation even for a single deterministic three-dimensional configuration is inherently difficult because of the large number of particles; the stochasticity leads to a larger dimensional model involving three spatial variables and additional stochastic variables, and accounting for uncertainty in key parameters of the input probability distributions leads to prohibitive computational complexity. In the first part of our paper we describe a high performance computing framework f...