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引用次数: 0
摘要
本文详述的工作是大坝安全模拟软件内部侵蚀性能和最佳实践评估国际计划的一部分。主要实验包括使用两种不同的模型模拟两座大坝溃坝事件的不确定性:DLBreach 是由 Wu 开发的基于物理的大坝/堤坝溃决模型。WinDAM C 也是一种基于物理的溃坝模型,能够分析大坝翻浆和内部侵蚀。选择用于分析的大坝包括在实验室测试的 1.3 米高的大坝和在现场发生溃坝的 15.56 米高的更大的大坝。通过对方差、灵敏度和优化的进一步分析,对这些实验结果进行了扩展。最后,利用这些模拟器的结果训练了一个回归模型,以探究如何利用机器学习技术捕捉这样的系统。这些实验的结果,连同该计划其他成员的结果,增进了我们对用户使用这些工具所带来的影响的理解。
Analysis of Uncertainty in Internal Erosion Simulations for DLBreach and WinDAM C
The work detailed here is part of an international initiative on the evaluation of dam safety simulation software for internal erosion performance and best practices. The primary experiments involve simulating uncertainty in the failure events of two dams with two different models: DLBreach and WinDAM C. DLBreach is a physically-based dam/levee breach model developed by Wu. WinDAM C is also a physically based dam breach model capable of analyzing both dam overtopping and internal erosion. The dams selected for the analysis include a 1.3 m high dam tested in the lab and a larger 15.56 m high dam, which suffered a failure in the field. The findings from these experiments are extended with a further analysis on variance, sensitivity, and optimization. Finally, a regression model is trained using the results of these simulators as an inquiry into how well such a system can be captured using machine learning techniques. The results of these experiments, together with the results of the other members of the initiative, improve our understanding of the influences that users bring to using these tools.