SoundSim360


SoundSim360 is a high-fidelity acoustic simulation tool developed by RHOWS, based on more than 25 years of research in advanced numerical methods for wave-dominated partial differential equations.


Unlike traditional noise modeling software that relies on simplified ray-tracing or parabolic equation (PE) methods, SoundSim360 uses state-of-the-art physics-based algorithms (SBP–SAT finite difference methods) combined with GPU acceleration to deliver both accuracy and speed.


🔹 What it does

  • Predicts sound propagation over long distances, where low-frequency noise dominates.

  • Handles complex 3D environments including cities, buildings, and natural terrains.

  • Simulates transmission and reflection of sound against facades, terrain, and ground surfaces.

  • Models indoor sound propagation, including frequency-dependent transmission through walls and ceilings.

  • Incorporates realistic physics: atmospheric effects (wind, temperature, humidity), diffraction, scattering, and interference.


🔹 Applications

  • Urban planning: generating reliable noise maps for traffic, railways, air traffic, and construction.

  • Environmental protection: ensuring quiet zones in parks and recreation areas.

  • Wind farm noise: accurate low-frequency and infrasound propagation predictions.

  • Building acoustics: studying how sound penetrates and propagates indoors.

  • Marine/industrial noise: propagation in specialized environments.


🔹 Why it’s different

  • Accurate at low frequencies (<200 Hz), where existing models fail.

  • Robust for irregular terrain and complex geometries.

  • Can handle broadband and transient sources.

  • Validated against measurements in real environments.


In short: SoundSim360 is a next-generation, GPU-accelerated acoustic simulation platform that delivers accurate, physics-based predictions of sound propagation in realistic 3D environments.


Learn more about SoundSim360 and infrasound in this 2024 presentation by Professor Ken Mattsson (in swedish).

Relevant publications


  • Ken Mattsson, Gustav Eriksson, Leif Persson, José Chilo, & Kourosh Tatar (2026). Efficient finite difference modeling of infrasound propagation in realistic 3D domains: Validation with wind turbine measurements. Applied Acoustics, 243, 111156. https://authors.elsevier.com/sd/article/S0003-682X(25)00628-0

  • Gustav Eriksson, & Vidar Stiernström (2024). Acoustic shape optimization using energy stable curvilinear finite differences. Journal of Computational Physics, 517, 113347. https://doi.org/10.1016/j.jcp.2024.113347

  • Martin Almquist, Ilkka Karasalo, & Ken Mattsson (2014). Atmospheric Sound Propagation Over Large-Scale Irregular Terrain. Journal of Scientific Computing, 61(2), 369-397. https://doi.org/10.1007/s10915-014-9830-4


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