Parallel Cloning Simulation of Flood Mitigation Operations in the Upper-Middle Reach of Huaihe River

Guoyi Zhang, Minghui Fang, Mingkai Qian, Shijin Xu
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引用次数: 3

Abstract

Simulation based decision tools have been playing a significant role in the flood mitigation operation, especially for a river network with a large number of flood control structures. However, to evaluate the feasibility of alternative scenarios, decision-makers must repeat executing a simulation, which is a tiresome and time-consuming work. Based upon the technique of simulation cloning, a parallel and progressive incremental simulation cloning (PPISC) approach was proposed in this paper to concurrently analyze alternative scenarios of flood mitigation operations in the upper and middle reach of Huaihe River system. The objective of which was to optimize the simulation execution by avoiding unnecessary repeated computation among multiple associated scenarios. The basic idea of the PPISC was: merging associated scenarios into a compound one and performing the parallel incremental simulation cloning for each compound scenario according to the time sequence of its decision points. Both the theoretical analysis and test results show that the PPISC algorithm has the characteristic of high computational performance and twice more the parallel efficiency than traditional parallel and distributed simulation methods under the same time complexity.
淮河中上游防洪行动并行克隆模拟
基于仿真的决策工具在防洪调度中发挥着重要的作用,特别是在具有大量防洪设施的河网中。然而,为了评估备选方案的可行性,决策者必须重复执行模拟,这是一项令人厌烦且耗时的工作。基于模拟克隆技术,提出了一种并行渐进式增量模拟克隆(PPISC)方法,对淮河中上游水系防洪调度备选方案进行并行分析。其目的是通过避免多个相关场景之间不必要的重复计算来优化仿真执行。PPISC的基本思想是:将关联的场景合并为复合场景,并根据决策点的时间序列对每个复合场景执行并行增量模拟克隆。理论分析和实验结果表明,在相同时间复杂度下,PPISC算法具有较高的计算性能,并行效率是传统并行和分布式仿真方法的2倍以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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