(Multi)wavelet-based Godunov-type simulators of flood inundation: Static versus dynamic adaptivity
(Multi)wavelet-based Godunov-type simulators of flood inundation: Static versus dynamic adaptivity
复制标题
基于（多）小波的 Godunov 型洪水淹没模拟器：静态自适应与动态自适应
DOI：
10.1016/j.advwatres.2022.104357
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发表时间：
2023
影响因子：
4.7
通讯作者：
Kesserwani G
中科院分区：
文献类型：
--
作者：
Kesserwani G
现实世界的洪水模拟器通常使用浅水方程的一阶有限体积（FV1）求解器，利用图形处理单元（GPU）上的并行化和固定网格上的静态自适应来提高效率。二阶不连续Galerkin（DG2）求解器大大提高了均匀网格上的预测精度，运行成本相对较高，但其作为使用静态自适应的洪水模拟替代方案的实际效用尚未评估。这也是使用Haar小波（HW）缩放FV1分段常数解（HWFV1）的多分辨率分析（MRA）和缩放DG2分段平面解（MWDG2）的平滑多小波（MW）的动态自适应性的情况，以随时间调整其网格的分辨率。因此，动态MWDG2和HWFV1自适应性是新探索的实际现实世界的模拟，找出当他们产生更好的预测比静态DG2和FV1自适应性。提出了一种新的GPU实现，包括动态MWDG2自适应性，以评估GPU并行化在多大程度上使其运行时实际可行。动态和静态的适应性评估三个测试，涉及缓慢，逐渐快速的洪水流量的预测精度和计算成本的分析，参考均匀网格DG2模拟在最好的分辨率的数字高程模型（DEM）。研究结果表明，有利于静态FV1适应性的长期模拟缓慢逐渐传播的洪水和动态MWDG2适应性，以模拟事件驱动的快速传播的流量。在GPU上，动态MWDG2自适应比均匀DG2更快，导致更高的加速比，其初始固定网格上的元素减少更多。
Real-world flood simulators often use first-order finite volume (FV1) solvers of the shallow water equations with efficiency enhancements exploiting parallelisation on Graphical Processing Units (GPUs) and the use of static adaptivity on fixed grids. A second-order discontinuous Galerkin (DG2) solver greatly increases the accuracy in the predictions on uniform grids, where it is comparatively costly to run, but its practical utility as an alternative for flood simulations using static adaptivity is not yet assessed. This is also the case for the dynamic adaptivity using the multiresolution analysis (MRA) of the Haar wavelet (HW) scaling FV1 piecewise-constant solutions (HWFV1) and of the smoother Multiwavelets (MWs) that scales DG2 piecewise-planar solutions (MWDG2) to adapt the resolution of their grids over time. Therefore, dynamic MWDG2 and HWFV1 adaptivity is newly explored for practical real-world simulations, to find out when they yield better predictions than static DG2 and FV1 adaptivity. A new GPU implementation is proposed to include dynamic MWDG2 adaptivity to also assess how far GPU parallelisation renders its runtime practically feasible. Dynamic and static adaptivity are assessed for three tests involving slow, gradual to rapid flood flows with analyses of their predictive accuracy and computational costs with reference to uniform grid DG2 simulations at the finest resolution of the digital elevation model (DEM). Findings suggest favouring static FV1 adaptivity for long-duration simulations of slowly to gradually propagating floods and dynamic MWDG2 adaptivity to simulate events driven by rapidly propagating flows. On the GPU, dynamic MWDG2 adaptivity is faster than uniform DG2, leading to a higher speedup ratio with higher reduction in the elements on its initial, fixed grid.