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A GPU-based 2D shallow water quality model
Journal of Hydroinformatics ( IF 2.7 ) Pub Date : 2020-09-01 , DOI: 10.2166/hydro.2020.030
Geovanny Gordillo 1 , Mario Morales-Hernández 2 , I. Echeverribar 1, 3 , Javier Fernández-Pato 3 , Pilar García-Navarro 1
Affiliation  

In this study, a 2D shallow water flow solver integrated with a water quality model is presented. The interaction between the main water quality constituents included is based on the Water Quality Analysis Simulation Program. Efficiency is achieved by computing with a combination of a Central Processing Unit (CPU) and a Graphics Processing Unit (GPU) device. This technique is intended to provide robust and accurate simulations with high computation speedups with respect to a single-core CPU in real events. The proposed numerical model is evaluated in cases that include the transport and reaction of water quality components over irregular bed topography and dry–wet fronts, verifying that the numerical solution in these situations conserves the required properties (C-property and positivity). The model can operate in any steady or unsteady form allowing an efficient assessment of the environmental impact of water flows. The field data from an unsteady river reach test case are used to show that the model is capable of predicting the measured temporal distribution of dissolved oxygen and water temperature, proving the robustness and computational efficiency of the model, even in the presence of noisy signals such as wind speed.



中文翻译:

基于GPU的2D浅水水质模型

在这项研究中,提出了一种与水质模型集成的二维浅水流求解器。所包含的主要水质成分之间的相互作用基于水质分析模拟程序。通过结合使用中央处理器(CPU)和图形处理器(GPU)设备来实现效率。该技术旨在针对真实事件中的单核CPU提供具有高计算速度的强大,准确的仿真。在包括水质成分在不规则床形地形和干湿锋线上的运输和反应在内的情况下,对提出的数值模型进行了评估,验证了在这些情况下的数值解决方案保留了所需的特性(碳质和正性)。该模型可以以任何稳定或不稳定的形式运行,从而可以有效评估水流对环境的影响。来自不稳定河段测试案例的现场数据用于表明,该模型能够预测溶氧和水温的测量时间分布,即使存在噪声信号,也能证明模型的鲁棒性和计算效率。作为风速。

更新日期:2020-09-30
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