摘要：A surrogate based particle swarm optimization （SBPSO） algorithm which combines the surrogate modeling technique and particle swarm optimization is applied to the reliability- based robust design （RBRD） of composite pressure vessels. The algorithm and efficiency of SBPSO are displayed through numerical examples. A model for filament-wound composite pressure vessels with metallic liner is then studied by netting analysis and its responses are analyzed by using Finite element method （performed by software ANSYS）. An optimization problem for maximizing the performance factor is formulated by choosing the winding orientation of the helical plies in the cylindrical portion, the thickness of metal liner and the drop off region size as the design variables. Strength constraints for composite layers and the metal liner are constructed by using Tsai-Wu failure criterion and Mises failure criterion respectively. Numerical examples show that the method proposed can effectively solve the RBRD problem, and the optimal results of the proposed model can satisfy certain reliability requirement and have the robustness to the fluctuation of design variables.

摘要：The large design freedom of variable-stiffness (VS) composite material presupposes its potential for wide engineering application. Previous research indicates that the design of VS cylindrical structures helps to increase the buckling load as compared to quasi-isotropic (QI) cylindrical structures. This paper focuses on the anti-buckling performance of VS cylindrical structures under combined loads and the efficient optimization design method. Two kinds of conditions, bending moment and internal pressure, and bending moment and torque are considered. Influences of the geometrical defects, ovality, on the cylinder's performances are also investigated. To increase the computational efficiency, an adaptive Kriging meta-model is proposed to approximate the structural response of the cylinders. In this improved Kriging model, a mixed updating rule is used in constructing the meta-model. A genetic algorithm (GA) is implemented in the optimization design. The optimal results show that the buckling load of VS cylinders in all cases is greatly increased as compared with a QI cylinder.

摘要：This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.

摘要：In conventional reliability-based optimum design of structures, the reliability is computed based on the probability assumption, and the design objective and constraint are considered as deterministic ones. In many cases, however, there exist some fuzzy factors in the design objective and constraint functions. In this paper, the fuzzy reliability and fuzzy constraint are introduced to establish the fuzzy reliability-based optimum model for laminated composites. The examples show that the method developed in this paper can give consideration to both the reliability demand and the economic aspect of a structure. Since the fuzzy reliability-based optimum design is a ＇soft＇ design, the present results provide a new methodology for the effective evaluation of structural reliability and bring us an alternative optimum design idea.

摘要：The present work aims to develop a method for reliability-based optimum design of composite structures. A procedure combining particle swarm optimization （PSO） and finite element analysis （FEA） has been proposed. Numerical examples for the reliability design optimization （RDO） of a laminate and a composite cylindrical shell are worked out to demonstrate the effectiveness of the method. Then a design for composite pressure vessels is studied. The advantages and necessity of RDO over the conventional equi-strength design are addressed. Examples show that the proposed method has good stability and is efficient in dealing with the probabilistic optimal design of composite structures. It may serve as an effective tool to optimize other complicated structures with uncertainties.

摘要：提出对复合材料结构进行稳健可靠性设计,设计中同时考虑了随机因素和模糊因素的影响。首先考虑约束的模糊性,建立了复合材料层合板的模糊优化设计模型。在模糊优化设计的基础上,考虑纤维角度和单层板厚度的变异对模糊约束的影响,进一步研究了复合材料层合板的模糊稳健设计。算例说明了本文提出的方法的有效性,对复合材料结构的合理设计具有一定的指导意义。

摘要：研究层合板结构基于最终层失效准则的可靠性分析方法,在此基础上,对复合材料层合板可靠性优化设计的方法和算法进行讨论。层合板作为一个系统考虑,其可靠性分析含以下几个步骤:(1)随机载荷和强度参数作为随机变量,利用一次二阶矩法(first order reliability method,FORM)分析单层板的失效概率。(2)假定失效概率最大的单层板首先破坏,然后通过修改刚度矩阵对结构进行再分析,得到剩余结构各单层板的失效概率,从而建立主要失效序列。(3)计算系统的可靠度。在确立复合材料基于最终层失效准则的可靠性分析方法的基础上,以系统可靠度指标最大为目标,研究层合板的可靠性优化问题。建立和发展基于最终层失效准则的复合材料层合板可靠性优化方法以及相应的算法,并对比讨论单变量和多变量优化设计问题。

摘要：采用遗传算法分析了存在初始缺陷的复合材料层合板的可靠性优化和鲁棒问题.单元层可靠性分析时,取初始缺陷、强度参数为随机变量,采用一阶矩法和Tsai-Wu准则分析每个单元层的失效概率.系统失效概率的计算基于首层失效假定,把系统看作为单元层的串联结构,系统中任何一个单元层的破坏就看作为系统的失效.在此基础上,对结构的可靠性优化和鲁棒特征进行了研究,分析了对称层合板的层数、可靠度和纤维方向角之间的关系,为结构设计提供参考.

摘要：采用粒子群算法(PSO)分析了存在初始缺陷的复合材料层合板的可靠性优化问题.在层合板结构总厚度一定的情况下,以系统可靠度最大为目标函数,对复合材料的纤维方向角和相对厚度进行优化设计.单层板失效与否应用Tsai-Wu准则判断,采用一次二阶矩法(FORM)计算和评价失效概率.通过具体算例及借鉴遗传算法中的在线性能和离线性能评估准则,对粒子群算法的收敛性能进行评估,结果表明:与遗传算法相比,该方法具有操作简单、计算效率高等特点,对复合材料层合结构的可靠性优化设计十分有效.

摘要：纤维增强复合材料是由高强度、低密度的纤维材料与基体组成，具有很多其它材料所不具有的特性，其应用范围越来越大。复合材料的机械性能与加工制造等过程密切相关，其材料性能的离散度较大，因此考虑不确定性因素的结构可靠性分析非常必要。可设计性是复合材料的另一个特点，因此复合材料结构的优化设计也是研究的热点之一。本文讨论了复合材料层合板结构的可靠性分析方法，优化设计，可靠性优化设计以及鲁棒优化等，并对其发展趋势作出展望。