Abstract In the present research, the reliability-based design optimization (RBDO) of labyrinth weirs has been investigated. The optimization problem is formulated such that the optimal shape of trapezoidal labyrinth weir described by a number of variables is found by minimizing the volume of the trapezoidal labyrinth weir and maximizing the reliability index. The constraint conditions are the weir geometric shape and its different ratios. In order to achieve this purpose, a framework is presented whereby non-dominated sorting genetic algorithm (NSGA-II) is integrated with monte carlo simulation (MCS) method to solve the RBDO approach of trapezoidal labyrinth weirs. The proposed method is applied to UTE Dam labyrinth weir, and the results are compared with the real one. The results show the need for design based on reliability in the labyrinth weirs that propose using RBDO for weir design. The results showed that RBDO approach can achieve a more reliable design in addition to reducing the volume of the trapezoidal labyrinth weir. Finally, the sensitivity analysis of the parameters effective on the reliability index revealed that three design variables of weir width, total upstream head and discharge coefficient are the main parameters affecting weir RBDO solution.

中文翻译：

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基于多目标可靠性的梯形迷宫堰设计优化

摘要 在目前的研究中，对迷宫堰基于可靠性的设计优化（RBDO）进行了研究。优化问题被公式化，使得通过最小化梯形迷宫堰的体积和最大化可靠性指标来找到由多个变量描述的梯形迷宫堰的最佳形状。约束条件是堰的几何形状及其不同的比例。为了实现这一目的，提出了一种框架，将非支配排序遗传算法（NSGA-II）与蒙特卡罗模拟（MCS）方法相结合，解决梯形迷宫堰的RBDO方法。将该方法应用于UTE大坝迷宫堰，并与实际结果进行对比。结果表明，迷宫堰建议使用 RBDO 进行堰设计，需要基于可靠性进行设计。结果表明，RBDO方法除了减少梯形迷宫堰的体积外，还可以获得更可靠的设计。最后，对可靠性指标有效参数的敏感性分析表明，堰宽、上游总水头和流量系数三个设计变量是影响堰RBDO解决方案的主要参数。