Concert Hall Geometry Optimization with Parametric Modeling Tools and Wave-Based Acoustic Simulations

Abstract

Advances in computational capacity made available through graphics processing unit (GPU) processing and developments in parametrically driven design tools are creating new possibilities for acoustic design and analysis. In particular, wave-based numerical simulations are becoming more tractable, and geometry manipulations, which were once cumbersome manual work, can now be automated. A case study of concert hall section profile optimization is presented. Using RHINOCEROS software with the GRASSHOPPER parametric modeling plugin, geometries were automatically generated based on a few parameters, then evaluated using Finite Difference Time Domain (FDTD) numerical simulations using GPU processing in MATLAB. The results from each iteration are used to inform a global optimization algorithm that conducts an intelligent search of the parameter space to find a solution in as few iterations as possible. The optimization is based on a stochastic model of the multidimensional objective function. The objective function is iteratively sampled and a simplified Bayesian approach is used for finding the set of parameters which is most likely to improve the current estimate of the global minimum at each iteration. With this method, curved and linear iterations of the sidewalls and under-balcony surfaces of a concert hall section were investigated. The objective was to deliver the most early energy, in the most uniform distribution, from multiple sources to multiple receiver positions.