Abstract:A difficult challenge in geometrical acoustic modeling is computing propagation paths from sound sources to receivers fast enough for interactive applications. This paper describes a beam tracing method that enables interactive updates of propagation paths from a stationary source to a moving receiver in large building interiors. During a precomputation phase, convex polyhedral beams traced from the location of each sound source are stored in a "beam tree" representing the regions of space reachable by potenti… Show more
“…Most present-day room acoustics software packages use geometric methods [19]. Recent work such as AD-FRUSTA [20], edgediffraction [21], beam tracing [22,23], are able to accelerate these methods using ray and volume tracing. There has also been work on accelerating geometric techniques on the GPU [24,25] …”
Section: Geometric Methods For the Wave Equationmentioning
An efficient algorithm for time-domain solution of the acoustic wave equation for the purpose of room acoustics is presented. It is based on adaptive rectangular decomposition of the scene and uses analytical solutions within the partitions that rely on spatially invariant speed of sound. This technique is suitable for auralizations and sound field visualizations, even on coarse meshes approaching the Nyquist limit. It is demonstrated that by carefully mapping all components of the algorithm to match the parallel processing capabilities of graphics processors (GPUs), significant improvement in performance is gained compared to the corresponding CPU-based solver, while maintaining the numerical accuracy. Substantial performance gain over a high-order finite-difference time-domain method is observed. Using this technique, a 1 second long simulation can be performed on scenes of air volume 7500 m 3 till 1650 Hz within 18 minutes compared to the corresponding CPU-based solver that takes around 5 hours and a high-order finite-difference time-domain solver that could take up to three weeks on a desktop computer. To the best of the authors' knowledge, this is the fastest time-domain solver for modeling the room acoustics of large, complex-shaped 3D scenes that generates accurate results for both auralization and visualization.
“…Most present-day room acoustics software packages use geometric methods [19]. Recent work such as AD-FRUSTA [20], edgediffraction [21], beam tracing [22,23], are able to accelerate these methods using ray and volume tracing. There has also been work on accelerating geometric techniques on the GPU [24,25] …”
Section: Geometric Methods For the Wave Equationmentioning
An efficient algorithm for time-domain solution of the acoustic wave equation for the purpose of room acoustics is presented. It is based on adaptive rectangular decomposition of the scene and uses analytical solutions within the partitions that rely on spatially invariant speed of sound. This technique is suitable for auralizations and sound field visualizations, even on coarse meshes approaching the Nyquist limit. It is demonstrated that by carefully mapping all components of the algorithm to match the parallel processing capabilities of graphics processors (GPUs), significant improvement in performance is gained compared to the corresponding CPU-based solver, while maintaining the numerical accuracy. Substantial performance gain over a high-order finite-difference time-domain method is observed. Using this technique, a 1 second long simulation can be performed on scenes of air volume 7500 m 3 till 1650 Hz within 18 minutes compared to the corresponding CPU-based solver that takes around 5 hours and a high-order finite-difference time-domain solver that could take up to three weeks on a desktop computer. To the best of the authors' knowledge, this is the fastest time-domain solver for modeling the room acoustics of large, complex-shaped 3D scenes that generates accurate results for both auralization and visualization.
“…Similar to the ray tracing technique are the the beam tracing methods [12,13,20] obstructed by several surfaces [19]. As for ray tracing, diffraction contri bution modelling is a problem for beam tracing methods [20].…”
Section: R Ay Trace Techniquesmentioning
confidence: 99%
“…Moreover, im portant propagation paths may be missed by all samples. In order to minimise the likelihood of large errors, ray tracing systems often generate a large number of samples, which requires a large amount of com putation [19].…”
“…The main reason is the fact that sound in the full audio range must be simulated for frequencies and wavelengths covering three orders of magnitude (from 20 Hz to 20 kHz). This might be the reason for the delayed implementation of physically based 3D audio real-time rendering engines for virtual environments (Savioja et al 1999;Funkhouser et al 2004;Lentz et al 2007;Schröder et al 2010;Schröder 2011).…”
Over the last decades, powerful prediction models have been developed in architectural acoustics, which are used for the calculation of sound propagation in indoor and/or outdoor scenarios. Sound insulation is predicted rather precisely by using direct and flanking transmission models of sound and vibration propagation. These prediction tools are already in use in architectural design and consulting. For the extension towards virtual reality (VR) systems, it is required to accelerate the prediction and simulation tools significantly and to allow an adaptive and interactive data processing during the simulation and 3D audio stimulus presentation. This article gives an overview on the current state-of-the-art of acoustic VR and discusses all relevant components in terms of accuracy, implementation and computational effort. With the progress in processing power, it is already possible to apply such VR concepts for architectural acoustics and to start perceptual studies in integrated architectural design processes.
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