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- Parallel ray tracing for underwater acoustic predictionsPublication . Calazan, Rogério; Rodríguez, Orlando; Nedjah, Nadia; Gervasi, O.; Murgante, B.; Misra, S.; Borruso, G.; Torre, C. M.; Rocha, A. M. A. C.; Taniar, D.; Apduhan, B. O.; Stankova, E.; Cuzzocrea, A.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.
- TRACEO3D Ray tracing model for underwater noise predictionsPublication . Calazan, Rogério; Rodríguez, Orlando; Camarinha-Matos, L. M.; Parreira-Rocha, M.; Ramezani, J.Shipping noise is the main source of underwater noise raising concern among environmental protection organizations and the scientific community. Monitoring of noise generated by shipping traffic is a difficult challenge within the context of smart systems and solutions based on acoustic modeling are being progressively adopted to overcome it. A module of sound propagation stands as a key point for the development of a smart monitoring system since it can be used for the calculation of acoustic pressure, which can be combined with estimates of the source pressure level to produce noise predictions. This paper addresses the usage of the TRACEO3D model for application in such systems; the model validity is addressed through comparisons with results from an analytical solution and from a scale tank experiment. The comparisons show that the model is able to predict accurately the reference data, while a full-field model (normal mode-based, but adiabatic) is only accurate till a certain degree. The results show that TRACEO3D is robust enough to be used efficiently for predictions of sound propagation, to be included as a part of a smart system for underwater noise predictions.
- Numerical enhancements and parallel GPU implementation of the TRACEO3D modelPublication . Calazan, Rogério de Moraes; Rodríguez, O. C.Underwater acoustic models provide a fundamental and e cient tool to parametrically investigate hypothesis and physical phenomena through varied environmental conditions of sound propagation underwater. In this sense, requirements for model predictions in a three-dimensional ocean waveguide are expected to become more relevant, and thus expected to become more accurate as the amount of available environmental information (water temperature, bottom properties, etc.) grows. However, despite the increasing performance of modern processors, models that take into account 3D propagation still have a high computational cost which often hampers the usage of such models. Thus, the work presented in this thesis investigates a solution to enhance the numerical and computational performance of the TRACEO3D Gaussian beam model, which is able to handle full three-dimensional propagation. In this context, the development of a robust method for 3D eigenrays search is addressed, which is fundamental for the calculation of a channel impulse response. A remarkable aspect of the search strategy was its ability to provide accurate values of initial eigenray launching angles, even dealing with nonlinearity induced by the complex regime propagation of ray bouncing on the boundaries. In the same way, a optimized method for pressure eld calculation is presented, that accounts for a large numbers of sensors. These numerical enhancements and optimization of the sequential version of TRACEO3D led to signi cant improvements in its performance and accuracy. Furthermore, the present work considered the development of parallel algorithms to take advantage of the GPU architecture, looking carefully to the inherent parallelism of ray tracing and the high workload of predictions for 3D propagation. The combination of numerical enhancements and parallelization aimed to achieve the highest performance of TRACEO3D. An important aspect of this research is that validation and performance assessment were carried out not only for idealized waveguides, but also for the experimental results of a tank scale experiment. The results will demonstrate that a remarkable performance was achieved without compromising accuracy. It is expected that the contributions and remarkable reduction in runtime achieved will certainly help to overcome some of the reserves in employing a 3D model for predictions of acoustic elds.