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Novel reliability-based optimization method for thermal structure with hybrid random, interval and fuzzy parameters

机译：混合随机，区间和模糊参数的热结构可靠性优化方法

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摘要

In this paper, novel reliability-based optimization model and method are proposed for thermal structure design with random, interval and fuzzy uncertainties in material properties, external loads and boundary conditions. Random variables are used to quantify the probabilistic uncertainty with sufficient sample data; whereas, interval variables and fuzzy variables are adopted to model the non-probabilistic uncertainty associated with objective limited information and subjective expert opinions, respectively. Using the interval ranking strategy, the level-cut limit state function is precisely quantified to represent the safety state. The eventual safety possibility is derived based on multiple integral, where the cut levels of different fuzzy variables are considered to be independent. Then a hybrid reliability-based optimization model is established with considerable computational cost caused by three-layer nested loop. To improve the computational efficiency, a subinterval vertex method is presented to replace the inner-loop and middle-loop. Comparing numerical results with traditional reliability model, a mono-objective example and a multi-objective example are provided to demonstrate the feasibility of proposed method for hybrid reliability analysis and optimization in practical engineering.
机译：本文提出了一种新的基于可靠性的优化模型和方法，用于热结构设计，其材料特性，外部载荷和边界条件具有随机，区间和模糊不确定性。随机变量用于通过足够的样本数据来量化概率不确定性。分别采用区间变量和模糊变量对与客观有限信息和主观专家意见有关的非概率不确定性进行建模。使用区间分级策略，可以精确地量化级别削减极限状态函数以表示安全状态。最终的安全可能性是基于多个积分得出的，其中不同模糊变量的切割水平被认为是独立的。然后建立了基于混合可靠性的优化模型，该模型具有由三层嵌套循环引起的大量计算量。为了提高计算效率，提出了一种子区间顶点法来代替内环和中环。将数值结果与传统可靠性模型进行比较，提供了一个单目标实例和一个多目标实例，以证明所提出的方法在实际工程中进行混合可靠性分析和优化的可行性。

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