scholarly journals Comparison of Efficient Explicit Schemes for Shallow-Water Equations—Characteristics-Based Fractional-Step Method and Multimoment Eulerian Scheme

2007 ◽  
Vol 46 (3) ◽  
pp. 388-395 ◽  
Author(s):  
Yohsuke Imai ◽  
Takayuki Aoki ◽  
Magdi Shoucri
Keyword(s):  
Shallow Water ◽  
Shallow Water Equations ◽  
Parallel Architecture ◽  
Fractional Step ◽  
Processing Unit ◽  
Step Method ◽  
Fractional Step Method ◽  
Central Processing ◽  
Explicit Schemes ◽  
Coarse Meshes

Abstract Two explicit schemes for the numerical solution of the shallow-water equations are examined. The directional-splitting fractional-step method permits relatively large time steps without an iterative process by using a treatment based on the characteristics of the governing equations. The interpolated differential operator (IDO) scheme has fourth-order accuracy in time and space by using a Hermite interpolation function covering local domains, and accurate results are obtained with coarse meshes. It is shown that the two schemes are very efficient for hydrostatic meteorological models from the viewpoints of numerical accuracy and central processing unit time, and the fact that they are explicit makes them suitable for computers with parallel architecture.

The fully discrete fractional-step method for the Oldroyd model

2018 ◽  
Vol 129 ◽  
pp. 83-103 ◽  
Author(s):  
Tong Zhang ◽  
Yanxia Qian ◽  
JinYun Yuan
Keyword(s):  
Fractional Step ◽  
Step Method ◽  
Fractional Step Method ◽  
Oldroyd Model ◽  
Fully Discrete

Numerical Study of Density-Currents Using the Non-Staggered Grid Fractional-Step-Method

2000 ◽  
Author(s):  
J. Rafael Pacheco ◽  
Arturo Pacheco-Vega ◽  
Sigfrido Pacheco-Vega
Keyword(s):  
Numerical Study ◽  
Density Variation ◽  
Staggered Grid ◽  
Mapping Technique ◽  
Fractional Step ◽  
Density Currents ◽  
Step Method ◽  
Fractional Step Method ◽  
New Approach ◽  
Flow Equations

Abstract A new approach for the solution of time-dependent calculations of buoyancy driven currents is presented. This method employs the idea that density variation can be pursued by using markers distributed in the flow field. The analysis based on the finite difference technique with the non-staggered grid fractional step method is used to solve the flow equations written in terms of primitive variables. The physical domain is transformed to a rectangle by means of a numerical mapping technique. The problems analyzed include two-fluid flow in a tank with sloping bottom and colliding density currents. The numerical experiments performed show that this approach is efficient and robust.

scholarly journals A GPU-based 2D shallow water quality model

2020 ◽  
Vol 22 (5) ◽  
pp. 1182-1197
Author(s):  
Geovanny Gordillo ◽  
Mario Morales-Hernández ◽  
I. Echeverribar ◽  
Javier Fernández-Pato ◽  
Pilar García-Navarro
Keyword(s):  
Water Quality ◽  
Shallow Water ◽  
Graphics Processing Unit ◽  
Temporal Distribution ◽  
Water Quality Model ◽  
Quality Analysis ◽  
Test Case ◽  
Processing Unit ◽  
Quality Model ◽  
Central Processing

Abstract 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.

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