多失效模式机械系统可靠性稳健设计方法研究

将机械系统可靠性设计理论和稳健设计方法相结合,讨论了多失效模式机械系统可靠性稳健设计问题,提出了多失效模式机械系统可靠性稳健设计的计算方法．把可靠性灵敏度融入可靠性优化设计模型之中,将机械系统可靠性稳健设计归结为满足可靠性要求的多目标优化问题．在基本随机参数的前二阶矩已知的情况下,可以迅速准确地得到机械系统可靠性稳健设计信息．     

Reliability-based design optimization of knuckle component using conservative method of moving least squares meta-models

This paper discusses reliability-based design optimization (RBDO) of an automotive knuckle component under bump and brake loading conditions. The probabilistic design problem is to minimize the weight of a knuckle component subject to stresses, deformations, and frequency constraints in order to meet the given target reliability. The initial design is generated based on an actual vehicle specification. The finite element analysis is conducted using ABAQUS, and the probabilistic optimal solutions are obtained via the moving least squares method (MLSM) in the context of approximate optimization. For the meta-modeling of inequality constraint functions, a constraint-feasible moving least squares method (CF-MLSM) is used in the present study. The method of CF-MLSM based RBDO has been shown to not only ensure constraint feasibility in a case where the meta-model-based RBDO process is employed, but also to require low expense, as compared with both conventional MLSM and non-approximate RBDO methods.     

Reliability-based design optimization under stationary stochastic process loads

Time-dependent reliability-based design ensures the satisfaction of reliability requirements for a given period of time, but with a high computational cost. This work improves the computational efficiency by extending the sequential optimization and reliability analysis (SORA) method to time-dependent problems with both stationary stochastic process loads and random variables. The challenge of the extension is the identification of the most probable point (MPP) associated with time-dependent reliability targets. Since a direct relationship between the MPP and reliability target does not exist, this work defines the concept of equivalent MPP, which is identified by the extreme value analysis and the inverse saddlepoint approximation. With the equivalent MPP, the time-dependent reliability-based design optimization is decomposed into two decoupled loops: deterministic design optimization and reliability analysis, and both are performed sequentially. Two numerical examples are used to show the efficiency of the proposed method.     

A reliability-based robust optimization design for the drum brake using adaptive Kriging surrogate model

To decrease random parameters’ influence on the drum brake reliability, the reliability-based robust optimization design (RBROD) of the electric vehicle brake is proposed. Based on the assumption that the maximum temperature of the brake cannot exceed the allowable temperature, a performance function model of thermal–mechanical coupling reliability of drum brakes is established by the adaptive Kriging method, and the analysis of reliability sensitivity and RBROD are conducted. The accuracy of the proposed model is verified by temperature measurement experiment under emergency braking condition. The robust optimization design improves the drum brake reliability to 0.99998 and reduce the influence of the design parameters on the reliability, with the absolute values of the reliability sensitivity and the weight of the drum brake are significantly smaller. Therefore, the objectives of reliability design, robustness design, and optimization design are simultaneously achieved by the proposed methods. Besides, the relative error of the proposed method is 0.373%, the number of function evaluations is 39, and the comparison with four meta-model methods show that the proposed method holds high-accuracy and high-efficiency. This study provides a high-precision theoretical explanation for the robust optimization design of drum brake.     

汽车零部件的可靠性稳健优化设计——理论部分*

将可靠性优化设计理论与可靠性灵敏度分析方法相结合，讨论了汽车零部件的可靠性稳健优化设计问题，提出了可靠性稳健优化设计的计算方法。把可靠性灵敏度融入可靠性优化设计模型之中，将可靠性稳健优化设计归结为满足可靠性要求的多目标优化问题。     

多失效模式典型结构系统可靠性稳健设计方法研究

应用随机摄动技术与二阶矩方法,结合概率网络估算法（Probability Network Evaluation Technique）,讨论了多失效模式下结构系统的可靠性和可靠性灵敏度问题,并进一步对结构系统的可靠性稳健设计进行了分析。获得了不同失效模式间的相关统计特性,应用概率网络估算法确定了系统的代表失效模式,得出了...     

Structural optimization of uncertain dynamical systems considering mixed-design variables

In this paper attention is directed to the reliability-based optimization of uncertain structural systems under stochastic excitation involving discrete-continuous sizing type of design variables. The reliability-based optimization problem is formulated as the minimization of an objective function subject to multiple reliability constraints. The probability that design conditions are satisfied within a given time interval is used as a measure of system reliability. The problem is solved by a sequential approximate optimization strategy cast into the framework of conservative convex and separable approximations. To this end, the objective function and the reliability constraints are approximated by using a hybrid form of linear, reciprocal and quadratic approximations. The approximations are combined with an effective sensitivity analysis of the reliability constraints in order to generate explicit expressions of the constraints in terms of the design variables. The explicit approximate sub-optimization problems are solved by an appropriate discrete optimization technique. The optimization scheme exhibits monotonic convergence properties. Two numerical examples showing the effectiveness of the approach reported herein are presented.     

A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.     

Reliability-based robust design optimization of gap size of annular nuclear fuels using kriging and inverse distance weighting methods

In this study, the design optimization of the gap size of annular nuclear fuels used in pressurized water reactors (PWRs) was performed. For this, thermoelastic–plasticity–creep (TEPC) analysis of PWR annular fuels was carried out using an in-house code to investigate the performance of nuclear fuels. Surrogate models based on the kriging and inverse distance weighting models were generated using computational performance data based on optimal Latin hypercube design. Using these surrogate models, the gap size of PWR annular fuel was deterministically optimized using the micro-genetic algorithm to improve the heat transfer efficiency and maintain a lower level of stress. Reliability-based design optimization and reliability-based robust design optimization were conducted to satisfy target reliability and secure the robustness of the PWRs’ performance. The optimal gap size was validated through TEPC analysis and the optimum solutions were compared according to the approximate method and reliability index.     

基于鞍点逼近的机械结构可靠性稳健优化设计

将可靠性优化设计理论与可靠性灵敏度分析方法相结合,讨论了机械零部件稳健优化设计的问题.系统地推导了基于鞍点逼近的可靠性灵敏度公式,并把可靠性灵敏度计算结果融入可靠性稳健优化设计模型之中,将可靠性稳健优化设计归结为满足可靠性要求的多目标优化问题.在基本随机参数概率分布已知的前提下,应用鞍点逼近技术,得到极限状态函数的分布函数与概率密度函数,并且将此结果应用到机械零部件的可靠性灵敏度分析中,进而实现了机械零部件的可靠性稳健优化设计.通过与Monte-Carlo方法计算所得的结果相比可知,应用鞍点逼近技术可以迅速、准确地得到机械零部件可靠性稳健设计信息．     

A reliability method for optimization of [+,−]n fiber reinforced composite pipes

This paper presents damage strength optimization of laminates using a reliability-based method. Two complementary analyses are developed: the first is a mechanical analysis of damage behavior using a thermodynamics framework that determines the failure criterion; the second is a reliability method which takes not only randomness, but also statistical uncertainties into account for failure probability calculation. This method is based on a first order reliability method that requires the resolution of a constrained problem of optimization. To solve this problem, a hybrid algorithm, combining evolutionary computation techniques with deterministic procedure is presented. Filament-wound pipe optimization under pressure is discussed as a working example.     

Multi-objective system reliability-based optimization method for design of a fully parametric concept car body

This article investigates multi-objective optimization under reliability constraints with applications in vehicle structural design. To improve computational efficiency, an improved multi-objective system reliability-based design optimization (MOSRBDO) method is developed, and used to explore the lightweight and high-performance design of a concept car body under uncertainty. A parametric model knowledge base is established, followed by the construction of a fully parametric concept car body of a multi-purpose vehicle (FPCCB-MPV) based on the knowledge base. The structural shape, gauge and topology optimization are then designed on the basis of FPCCB-MPV. The numerical implementation of MOSRBDO employs the double-loop method with design optimization in the outer loop and system reliability analysis in the inner loop. Multi-objective particle swarm optimization is used as the outer loop optimization solver. An improved multi-modal radial-based importance sampling (MRBIS) method is utilized as the system reliability solver for multi-constraint analysis in the inner loop. The accuracy and efficiency of the MRBIS method are demonstrated on three widely used test problems. In conclusion, MOSRBDO has been successfully applied for the design of a full parametric concept car body. The results show that the improved MOSRBDO method is more effective and efficient than the traditional MOSRBDO while achieving the same accuracy, and that the optimized body-in-white structure signifies a noticeable improvement from the baseline model.     

考虑可靠度可信区间的结构可靠性优化设计

 在贝叶斯统计理论和结构可靠性优化设计方法的基础上,研究了结构在小样本情况下考虑可靠度可信区间的结构可靠性优化设计问题.将结构可靠度作为随机变量,根据先验信息和样本信息,采用贝叶斯推断技术获得结构可靠度的概率分布,给出了可靠度的点估计及区间估计.建立了考虑可靠度可信区间的结构可靠性优化设计模型,提出了考虑可靠度可信区间的结构可靠性优化设计方法.所提出的方法为解决小样本情况下的结构可靠性优化设计问题提供了新的解决方案.数值算例验证了所提出的结构可靠性优化设计方法的有效性和正确性.     

任意分布参数的机械零件的可靠性稳健设计（一）：理论部分

 将可靠性优化设计理论、可靠性灵敏度技术和稳健设计方法相结合，讨论了具有任意分布参数的机械零件的可靠性稳健设计问题，提出了可靠性稳健设计的计算方法．把可靠性灵敏度融入可靠性优化设计模型之中，将可靠性稳健设计归结为满足可靠性要求的多目标优化问题．在基本随机参数的前四阶矩已知的情况下，通过计算机程序可以实现具有任意分布参数的机械零件的可靠性稳健设计，迅速准确地得到具有任意分布参数的机械零件的可靠性稳健设计信息。     

Life-cycle reliability-based robust design optimization for GP model with response uncertainty

Reliability-based robust design optimization (RBRDO) is a crucial tool for life-cycle quality improvement. Gaussian process (GP) model is an effective alternative modeling technique that is widely used in robust parameter design. However, there are few studies to deal with reliability-based design problems by using GP model. This article proposes a novel life-cycle RBRDO approach concerning response uncertainty under the framework of GP modeling technique. First, the hyperparameters of GP model are estimated by using the Gibbs sampling procedure. Second, the expected partial derivative expression is derived based on GP modeling technique. Moreover, a novel failure risk cost function is constructed to assess the life-cycle reliability. Then, the quality loss function and confidence interval are constructed by simulated outputs to evaluate the robustness of optimal settings and response uncertainty, respectively. Finally, an optimization model integrating failure risk cost function, quality loss function, and confidence interval analysis approach is constructed to find reasonable optimal input settings. Two case studies are given to illustrate the performance of the proposed approach. The results show that the proposed approach can make better trade-offs between the quality characteristics and reliability requirements by considering response uncertainty.     

Structural reliability optimization using an efficient safety index calculation procedure

The objective of this paper is to conduct reliability-based structural optimization in a multidisciplinary environment. An efficient reliability analysis is developed by expanding the limit functions in terms of intermediate design variables. The design constraints are approximated using multivariate splines in searching for the optimum. The reduction in computational cost realized in safety index calculation and optimization are demonstrated through several structural problems. This paper presents safety index computation, analytical sensitivity analysis of reliability constraints and optimization using truss, frame and plate examples.     

Bayesian modeling and test planning for multiphase reliability assessment

We propose a Bayesian hierarchical model to assess the reliability of a family of vehicles, based on the development of the joint light tactical vehicle (JLTV). The proposed model effectively combines information across three phases of testing and across common vehicle components. The analysis yields estimates of failure rates for specific failure modes and vehicles as well as an overall estimate of the failure rate for the family of vehicles. We are also able to obtain estimates of how well vehicle modifications between test phases improve failure rates. In addition to using all data to improve on current assessments of reliability and reliability growth, we illustrate how to leverage the information learned from the three phases to determine appropriate specifications for subsequent testing that will demonstrate if the reliability meets a given reliability threshold.     

压杆稳定可靠性优化设计

在稳定可靠性设计理论和优化设计方法的基础上,讨论了压杆稳定可靠性优化设计问题,提出了压 杆稳定可靠性优化设计的计算方法。在基本随机参数的前两阶矩已知的情况下,通过计算机程序可以实现压杆 稳定可靠性优化设计,迅速准确地得到压杆稳定可靠性优化设计信息。     

Reliability-based optimization of trusses with random parameters under dynamic loads

In this work, a reliability-based optimization technique is addressed to obtain the minimum mean value of random mass of the structures with random parameters under stationary stochastic process excitation. The challenge of the problem lies in randomness involved from both structural parameters and dynamic load, which renders the structural reliability becoming the random dynamic reliability of the first passage problem. In order to obtain minimum mean value of random gross mass, element and system dynamic reliability constraints are constructed, respectively, and the structural sizing and shape optimization models based on the dynamic reliability are then presented. Moreover, among two optimal strategies proposed for optimization models, the second one can effectively reduce the workload by avoiding the computation of the variance of the dynamic response during the iterative process. Finally, the implementation of three examples is discussed to display the feasibility and validity of optimization technique given.