Large-distance sound propagation with high-frequency noise sources, multiple obstacles/geometry with varying acoustic impedance is common in real-life applications. To resolve the acoustic governing equations directly is often computationally costly, especially in three-dimensional space. Methods based on geometric acoustics can be more rapid. However, efforts are still being made to improve the efficiency, robustness, and the capability for complex configurations of such methods. In this paper, an efficient implementation of the rectilinear Gaussian beam tracing method is conducted, which combines rectilinear ray tracing with a proposed efficiency-matched dynamic ray tracing algorithm. A continuous medium stratification method is employed to improve the robustness. Also, a ray compression algorithm is proposed to save computation time. Numerical tests show that computation acceleration up to tenfold is achieved, benefiting rapid estimation of large-distance sound propagation. A standard octree data structure is employed in the code, which accelerates ray tracing in the testing cases with complex geometries. The efficiency and capability of the solver are demonstrated by studying several benchmark problems with varying complexity.

中文翻译：

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用于非湍流介质中声音传播建模的高效直线高斯光束跟踪方法

在现实生活中，具有高频噪声源的大距离声音传播，具有不同声阻抗的多个障碍物/几何形状是常见的。直接求解声学控制方程通常在计算上是昂贵的，尤其是在三维空间中。基于几何声学的方法可以更快。但是，仍在努力提高这种方法的复杂配置的效率，鲁棒性和能力。本文对直线高斯光束跟踪方法进行了有效的实现，将直线射线跟踪与提出的效率匹配动态射线跟踪算法相结合。采用连续介质分层方法来提高鲁棒性。另外，提出了一种射线压缩算法以节省计算时间。数值测试表明，可以实现高达十倍的计算加速，从而有利于快速估计远距离声音的传播。该代码中使用了标准的八叉树数据结构，可在几何形状复杂的测试案例中加速光线跟踪。通过研究具有不同复杂度的几个基准问题来证明求解器的效率和功能。