Reduced basis methods with parameterized boundary conditions for room acoustics

Room acoustic simulations can be performed by means of numerical methods, which typically solve the wave equation in an enclosure using discretization techniques. These methods provide high-fidelity solvers that include all the wave phenomena but are computationally costly. This paper presents the potential of a reduced basis method for simulating room acoustics when the boundary properties are changed iteratively, e.g., design changes in rooms where different boundary properties are simulated, which increase the computational cost when using traditional high-fidelity solvers. The presented framework allows reducing the computational burden by applying reduced basis methods and solving the problem in a reduced low-dimensional subspace where the absorption properties of complex boundary conditions are parameterized, e.g., the thickness of a porous material. The potential of the proposed framework is analyzed in terms of computational efficiency, accuracy and storage requirements. We show a computational reduction of two orders of magnitude for a 2D case with an upper frequency of 2 kHz and three orders of magnitude for a 3D simple case with an upper frequency of 1 kHz showing a potential of having an increase in terms of speedup when increasing the size of the domain. The storage requirement for a 2D case with an upper frequency of 8 kHz is 10.8GB while for a 3D case with an upper frequency of 1 kHz is 8GB.