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Design Optimization of I-Wall Levee System Supported by Sand Foundation

机译:沙基金会支持的I-Wall堤防系统设计优化

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Failures of I-wall levee systems were found to be the major cause of the extensive flooding after the Hurricane Katrina and the events thereafter. These events suggest that the current design procedures must be revised to reduce the overall probability of failure of the system by incorporating the uncertainties in the input parameters into the system. In this paper, a framework to perform design optimization of a typical I-wall levee made of clay resting on a sand foundation is proposed. The uncertainties in the system such as undrained shear strength of levee fill, friction angle of sand foundation, and flood water level behind I-wall were considered as random variables in the design optimization procedure. The design variables used were the penetration depth of I-wall from the levee crown, width of levee crown, and landside slope of levee. Several design cases were simulated and finite element analysis was performed for selected cases to estimate the overall stability of the system considering the possible variations in the random variables. A response surface was developed based on the FEM simulation results to represent the factor of safety as a function of random and design variables and implemented in optimization procedure. In the design optimization, total cost of I-wall levee system was minimized to reach cost-efficient designs and at the same time the probability of failure was evaluated and minimized. Finally, the optimization yielded a set of preferred designs known as Pareto front from which the optimal design can be selected.
机译:人们发现,在卡特里娜飓风及其后发生的事件中,I墙大堤系统的故障是造成大面积洪水的主要原因。这些事件表明,必须对当前的设计程序进行修改,以通过将输入参数中的不确定性纳入系统中来降低系统出现故障的总体可能性。在本文中,提出了一个框架来对典型的I墙堤进行优化设计的框架,该堤由粘土制成,位于沙地上。在设计优化过程中,系统的不确定性例如堤坝填充物的不排水抗剪强度,砂基础的摩擦角和I墙后面的洪水水位被视为随机变量。所使用的设计变量是I墙从堤顶的穿透深度,堤顶的宽度以及堤岸的边坡。模拟了几个设计案例,并对选定的案例进行了有限元分析,以考虑随机变量的可能变化来估计系统的整体稳定性。根据有限元模拟结果开发了响应面,以表示安全系数作为随机变量和设计变量的函数,并在优化过程中实现。在设计优化中,将I-wall堤防系统的总成本降至最低,以实现具有成本效益的设计,同时评估并最大程度地降低了发生故障的可能性。最后,优化产生了一组称为Pareto front的优选设计,可以从中选择最佳设计。

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