Summary: A pure-Julia package for propeller/rotor blade noise prediction with acoustic analogies.

What's an acoustic analogy?

• TL;DR answer:

  An acoustic analogy is a noise prediction approach that takes information from one area of the fluid domain (e.g., a propeller blade surface, or a fictitious surface surrounding a complicated flow) and calculates the acoustics radiated by the flow. The particular acoustic analogy implemented in AcousticAnalogies.jl is especially well-suited for predicting tonal propeller/rotor noise, and has features that ease its inclusion in gradient-based optimizations.

• Mathy answer:

  An acoustic analogy is a clever rearrangement of the Navier-Stokes equations, the governing equations of fluid flow, into a form that looks like the classical inhomogeneous wave equation. The inhomogeneous term represents sources of sound in the flow. The wave equation can be solved using the appropriate Green's function, which requires the evaluation of two surface integrals and a volume integral (usually neglected). If the integration surface is taken to be a solid surface in the fluid domain (e.g., a propeller blade), we can use the acoustic analogy solution to predict the acoustics caused by the motion of and loading on the integration surface.

Features:

• Implementation of L. Lopes' compact form of Farassat's formulation 1A (see http://dx.doi.org/10.2514/6.2015-2673 or http://dx.doi.org/10.2514/1.C034048 for details).
• Implementation of Brooks & Burley's rotor broadband noise prediction method http://dx.doi.org/10.2514/6.2001-2210.
• Support for stationary or constant-velocity moving observers, with an explict calculation for the latter from D. Casalino http://dx.doi.org/10.1016/S0022-460X(02)00986-0.
• Thoroughly tested: unit tests for everything, and multiple comparisons of the entire calculation to equivalent methods in NASA's ANOPP2 code.
• Convenient, fast coordinate system transformations through KinematicCoordinateTransformations.jl.
• Written in pure Julia, and compatible with automatic differentiation (AD) tools like ForwardDiff.jl.
• Comprehensive docs (TODO).
• Fast!

Installation

] add AcousticAnalogies

Usage

See the docs.

• This repository contains extensive tests run by GitHub Actions.
• This repository only allows signed commits to be merged into the main branch.