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Water 2017, 9(3), 184; doi:10.3390/w9030184

Depth-Averaged Non-Hydrostatic Hydrodynamic Model Using a New Multithreading Parallel Computing Method

School of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
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Academic Editors: Yung-Tse Hung and Michele Mossa
Received: 22 November 2016 / Revised: 22 February 2017 / Accepted: 1 March 2017 / Published: 5 March 2017
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Abstract

Compared to the hydrostatic hydrodynamic model, the non-hydrostatic hydrodynamic model can accurately simulate flows that feature vertical accelerations. The model’s low computational efficiency severely restricts its wider application. This paper proposes a non-hydrostatic hydrodynamic model based on a multithreading parallel computing method. The horizontal momentum equation is obtained by integrating the Navier–Stokes equations from the bottom to the free surface. The vertical momentum equation is approximated by the Keller-box scheme. A two-step method is used to solve the model equations. A parallel strategy based on block decomposition computation is utilized. The original computational domain is subdivided into two subdomains that are physically connected via a virtual boundary technique. Two sub-threads are created and tasked with the computation of the two subdomains. The producer–consumer model and the thread lock technique are used to achieve synchronous communication between sub-threads. The validity of the model was verified by solitary wave propagation experiments over a flat bottom and slope, followed by two sinusoidal wave propagation experiments over submerged breakwater. The parallel computing method proposed here was found to effectively enhance computational efficiency and save 20%–40% computation time compared to serial computing. The parallel acceleration rate and acceleration efficiency are approximately 1.45% and 72%, respectively. The parallel computing method makes a contribution to the popularization of non-hydrostatic models. View Full-Text
Keywords: hydrodynamics; non-hydrostatic; parallel computing; wave propagation hydrodynamics; non-hydrostatic; parallel computing; wave propagation
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Kang, L.; Jing, Z. Depth-Averaged Non-Hydrostatic Hydrodynamic Model Using a New Multithreading Parallel Computing Method. Water 2017, 9, 184.

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