Noisyduck: An open-source python tool for computing eigenmode decompositions of duct flows

Paper in proceeding, 2019

Wave propagation in ducts is a rich topic that is important to consider in the design of turbomachinery components for aero-engine applications. In order to describe how the waves propagate inside a duct, an eigenmode decomposition of the equations modeling the fluid problem can be performed. The resulting eigenmodes may be used to construct nonreflecting boundary conditions, to investigate flow physics, or for post-processing numerical simulations to track the evolution of modal content through a computational domain. In the present work, an open-source Python tool, called noisyduck, was developed to compute eigenmode decompositions of the linearized Euler equations that model linear wave propagation in a duct with constant cross-section. The numerical method is verified against analytical solutions and reported results from the literature for uniform axial flow and swirling flow in an annulus. The noisyduck tool is made available as a public resource with the intent of reducing duplicated research efforts, and clarifying equation sets and formulations with respect to the literature in the area of eigenmode decompositions for problems in duct acoustics.