Speaker
Description
Winds and temperature inversions in the lower atmosphere can create waveguides for acoustic waves. These waveguides are similar to acoustic ducts, such that the sound field can be represented as a superposition of a finite set of propagating atmospheric modes. These modes are obtained by solving a cubic eigenvalue problem derived from the linearized Euler equations. This approach enables the simulation of long-range acoustic propagation in vertically stratified atmospheres, as demonstrated through benchmark cases. We present numerical examples illustrating how this modal decomposition facilitates efficient hybrid simulations of long-range acoustic wave propagation. While the resulting computations are efficient, a limiting factor in terms of computational cost is the solution of the cubic eigenvalue problem. Therefore, we discuss the scalability of the approach using distributed eigenvalue solvers. In the future, more efficient eigenvalue solvers could further extend the applicability of the modal decomposition method toward real-time predictive modeling.