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Parallel Ray Tracing for Underwater Acoustic Predictions

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Computational Science and Its Applications – ICCSA 2017 (ICCSA 2017)

Abstract

Different applications of underwater acoustics frequently rely on the calculation of transmissions loss (TL), which is obtained from predictions of acoustic pressure provided by an underwater acoustic model. Such predictions are computationally intensive when dealing with three-dimensional environments. Parallel processing can be used to mitigate the computational burden and improve the performance of calculations, by splitting the computational workload into several tasks, which can be allocated on multiple processors to run concurrently. This paper addresses an Open MPI based parallel implementation of a three-dimensional ray tracing model for predictions of acoustic pressure. Data from a tank scale experiment, providing waveguide parameters and TL measurements, are used to test the accuracy of the ray model and the performance of the proposed parallel implementation. The corresponding speedup and efficiency are also discussed. In order to provide a complete reference runtimes and TL predictions from two additional underwater acoustic models are also considered.

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Notes

  1. 1.

    For horizontal measurements of cross-slope propagation.

  2. 2.

    KRAKEN and BELLHOP3D are part of the Acoustic Toolbox, which is available at the Ocean Acoustic Library [21].

  3. 3.

    This is believed to happen because the wedge is too step for the adiabatic approximation used by KRAKEN to be valid.

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Acknowledgments

This work received support from the Foreign Courses Program of CNPq and the Brazilian Navy. Thanks are due to the SiPLAB research team, LARSyS, FCT, University of Algarve. The authors are also deeply thankful to LMA-CNRS for allowing the use of the experimental tank data discussed in this work.

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Correspondence to Rogério M. Calazan .

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Calazan, R.M., Rodríguez, O.C., Nedjah, N. (2017). Parallel Ray Tracing for Underwater Acoustic Predictions. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10404. Springer, Cham. https://doi.org/10.1007/978-3-319-62392-4_4

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  • DOI: https://doi.org/10.1007/978-3-319-62392-4_4

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