Massively parallel structural acoustics for forward and inverse problems

Abstract

Three-dimensional structural acoustic simulations on highly complex structural models that are immersed in infinite and semi-infinite acoustic domains typically lead to large numbers of degrees of freedom that cannot be solved with commercial software packages. Typical applications include underwater acoustic simulation of submerged structures, and reverberation testing of aerospace structures. Many of these applications of interest involve large acoustic domains and complex 3D structures, thus making a finite element solution an attractive option. In addition, unknown parameters in the models can be mitigated with the solution of inverse problems. In this talk, we will discuss recent research efforts in Sierra-SD in the area of structural acoustics and will also present a partial differential equation (PDE) constrained optimization approach for solving inverse problems in structural acoustics that uses Sierra-SD for solving the forward and adjoint problems. Inverse problems are commonly encountered in structural acoustics, where accelerometer and/or microphone pressures are measured experimentally, and it is desired to characterize the acoustic sources, material parameters, and/or boundary conditions that produced the measurements. With a PDE-constrained optimization approach, the scalability of Sierra-SD can be leveraged for solving inverse problems. We will present results on the application of Sierra-SD on several large-scale structural acoustic applications examples of interest.