Asier Lacasta

An optimized GPU implementation of a 2D free surface simulation model on unstructured meshes

A GPU implementation of a FV method for the 2D Shallow Water Equations is presented.Structured and unstructured meshes allow different implementations.NVIDIA C2070 GPU is compared against Intel Core 2 Quad Processor.The basic GPU implementation obtains between 20× and 30× of speed-up.Some strategies on the mesh order allow to double the performance, reaching 50×. This work is related with the implementation of a finite volume method to solve the 2D Shallow Water Equations on Graphic Processing Units (GPU). The strategy is fully oriented to work efficiently with unstructured meshes which are widely used in many fields of Engineering. Due to the design of the GPU cards, structured meshes are better suited to work with than unstructured meshes. In order to overcome this situation, some strategies are proposed and analyzed in terms of computational gain, by means of introducing certain ordering on the unstructured meshes. The necessity of performing the simulations using unstructured instead of structured meshes is also justified by means of some test cases with analytical solution.

GPU implementation of the 2D shallow water equations for the simulation of rainfall/runoff events

Hydrological processes that occur in catchments usually require large space resolution over long periods of time. The advance on numerical methods as well as the increasing power of computation are making possible the physically based simulation of these phenomena. In particular, the 2D shallow water equations can be used to provide distributions of water depth and velocity fields. The necessity of spatial resolution involves the use of a large number of elements hence increasing the computational time when simulating realistic scenarios for a long time period. This work deals with an efficient GPU implementation of the 2D shallow water equations on unstructured meshes analysing the influence of the mesh resolution both on the computational performance and the quality of the results to simulate a rainfall/runoff event. The numerical method to solve them has been developed and compared following three programming approaches: the sequential implementation and its adaptation to the multi-thread and many-core architectures. The particular detail of the influence of the mesh ordering when using unstructured triangular meshes is paid attention in this work to find the best strategy to further reduce the computational time in the context of GPU simulation. The resulting approach is efficient and can become very useful in environmental simulation of hydrological processes.

An efficient solution for hazardous geophysical flows simulation using GPUs

The movement of poorly sorted material over steep areas constitutes a hazardous environmental problem. Computational tools help in the understanding and predictions of such landslides. The main drawback is the high computational effort required for obtaining accurate numerical solutions due to the high number of cells involved in the calculus. In order to overcome this problem, this work proposes the use of GPUs for decreasing significantly the CPU simulation time. The numerical scheme implemented in GPU is based on a finite volume scheme and it was validated in previous work with exact solutions and experimental data. The computational cost time obtained with the Graphical Hardware technology, GPU, is compared against Single-Core (sequential) and Multi-Core (parallel) CPU implementations. The GPU implementation allows to reduce the computational cost time in two orders of magnitude. HighlightsA GPU implementation of a FV method for geophysical shallow flows is presented.The GPU implementation has been performed over unstructured meshes.The GPU implementation allows to reduce in two orders of magnitude the computational cost.Real and up-to-date environmental problems are now affordable without the necessity of using coarse meshes.

An efficient GPU implementation for a faster simulation of unsteady bed-load transport

ABSTRACT Computational tools may help engineers in the assessment of sediment transport during the decision-making processes. The main requirements are that the numerical results have to be accurate and simulation models must be fast. The present work is based on the 2D shallow water equations in combination with the 2D Exner equation. The resulting numerical model accuracy was already discussed in previous work. Regarding the speed of the computation, the Exner equation slows down the already costly 2D shallow water model as the number of variables to solve is increased and the numerical stability is more restrictive. In order to reduce the computational effort required for simulating realistic scenarios, the authors have exploited the use of Graphics Processing Units in combination with non-trivial optimization procedures. The gain in computing cost obtained with the graphic hardware is compared against single-core (sequential) and multi-core (parallel) CPU implementations in two unsteady cases.

A Riemann coupled edge (RCE) 1D–2D finite volume inundation and solute transport model

A novel 1D–2D shallow water model based on the resolution of the Riemann problem at the coupled grid edges is presented in this work. Both the 1D and the 2D shallow water models are implemented in a finite volume framework using approximate Roe’s solvers that are able to deal correctly with wet/dry fronts. After an appropriate geometric link between the models, it is possible to define local Riemann problems at each coupled interface and estimate the contributions that update the cell solutions from the interfaces. The solute transport equation is also incorporated into the proposed procedure. The numerical results achieved by the 1D–2D coupled model are compared against a complete 2D model, which is considered the reference solution. The computational time is also examined.

Application of the Adjoint Method for the Reconstruction of the Boundary Condition in Unsteady Shallow Water Flow Simulation

Hydraulic phenomena in open-channel flows are usually described by means of the shallow water equations. This hyperbolic non-linear system can be used for predictive purposes provided that initial and boundary conditions are supplied and the roughness coefficient is calibrated. When calibration is required to fully pose the problem, several strategies can be adopted. In the present work, an inverse technique, useful for any of such purposes, based on the adjoint system and gradient descent is presented. It is used to find the optimal time evolution of the inlet boundary condition required to meet the 20 measured water depth data in an experimental test case of unsteady flow on a beach. The partial differential systems are solved using an upwind finite volume scheme. Several subsets of probes were selected and the quality of the reconstructed boundary tested against the experimental results. The results show that the adjoint technique is useful and robust for these problems, and exhibits some sensitivity to the choice of probes, which can be used to properly select probes in real applications.

Application of an adjoint-based optimization procedure for the optimal control of internal boundary conditions in the shallow water equations

ABSTRACT The shallow water equations have been extensively studied and used to model unsteady open channel flows in different applications. They belong to the category of hyperbolic partial differential equations and their treatment has recently been benefited from many numerical contributions leading to robust, accurate and well-balanced solutions. The correct formulation of external and internal boundary conditions is required to achieve a useful model in practical application. Control of internal boundary conditions may be useful in water distribution facilities. Therefore, development of a control strategy based on the fully dynamical mathematical model becomes attractive and justified. This work is devoted to the implementation of an adjoint based sensitivity analysis for the control of sluice gates in open-channel flow, formulated as internal boundary conditions. This is one of the most complex tasks in multiple regulated water delivery situations. Based on gradient method optimizers, the control of the whole channel to satisfy different requirements at several points of the channel is discussed. One of the achievements in this work is that the whole optimization process is performed two orders of magnitude faster than in real time. Moreover, the numerical results show this promising technique is a feasible way to obtain a robust and efficient control method.

EFFICIENT TWO-DIMENSIONAL SIMULATION MODELS FOR HYDRAULIC AND MORPHODYNAMIC TRANSIENTS

Recent advances in the simulation of shallow flows over mobile bed have shown that accurate and stable results in realistic problems can be provided if an appropriate coupling between the shallow water equations (SWE) and the Exner equation is performed. In this way the computational cost may become unaffordable in situations involving large time and space scales. Therefore, for restoring the numerical efficiency, the coupling technique is simplified, not decreasing the number of waves involved in the Riemann problem but simplifying their definitions. The effects of the approximations made are tested against experimental data which include transient problems over erodible bed. The simplified model is formulated under a general framework able to insert any desirable discharge solid load formula. Also, the movement of poorly sorted material over steep areas constitutes a hazardous environmental problem. Computational tools help in the understanding and predictions of such landslides. The main drawback is the high computational effort required for obtaining accurate numerical solutions due to the high number of cells involved. However, recent advances in massive parallelization techniques for 2D hydraulic models are able to reduce computer times by orders of magnitude making 2D applications competitive and practical for operational flood prediction in large river reaches. Moreover, high performance code development can take advantage of general purpose and inexpensive Graphical Processing Units (GPU), allowing to run 2D simulations more than 100 times faster than old generation 2D codes, in some cases.