鱼雷高压气舱的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,提出了可靠性稳健优化设计方法.采用该方法对鱼雷高压气舱进行了实例分析,并给出了仿真计算结果,为工程实际的机械产品的可靠性稳健优化设计提供了理论依据.     

鱼雷螺钉联接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,应用可靠性稳健设计优化理论方法,对鱼雷螺钉联接结构进行了可靠性稳健优化设计.给出了计算分析结果.为工程实际的机械产品的可靠性稳健优化设计提供了理论依据.     

整体法兰的可靠性稳健优化设计

将可靠性优化设计理论、可靠性灵敏度分析技术与稳健设计方法相结合,讨论整体法兰的可靠性稳健优化设计问题,提出可靠性稳健优化设计的计算方法。把可靠性灵敏度溶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。数值算例表明所提出的数值计算方法是一种非常方便和实用的可靠性稳健优化设计方法。     

气动高压贮气瓶的优化设计

本文讨论了气动贮气瓶壁厚(外径)的设计,特别就采用热套容器时的设计方法进行了详尽的论述,并给出了将高压贮气瓶按加道林条件设计成热套组合筒的设计公式和设计方法。为设计承压能力高、重量轻的气动高压贮气瓶提供了一种实用的崭新方法。     

基于灵敏度附加目标函数的可靠性稳健优化设计

以实现多约束非线性优化问题的可靠性稳健优化设计为目标,在应用可靠性随机摄动技术建立多失效模式下机械零部件可靠度约束函数的基础上,构建了可靠性优化设计数学模型;通过对其目标函数和约束条件进行灵敏度分析,生成目标函数和约束函数的灵敏度附加项,提出了两种基于灵敏度附加目标函数的可靠性稳健优化设计模型;应用Matlab语言的优化和符号工具箱来实现新型旋转式立体车库载车台主梁结构的可靠性稳健优化设计。算例表明,提出的可靠性稳健优化设计方法具有较高的精度和可靠度,为机械零件的可靠性设计提供了理论依据。     

基于灵敏度附加目标函数的可靠性稳健优化设计

以实现多约束非线性优化问题的可靠性稳健优化设计为目标,在应用可靠性随机摄动技术建立多失效模式下机械零部件可靠度约束函数的基础上,构建了可靠性优化设计数学模型;通过对其目标函数和约束条件进行灵敏度分析,生成目标函数和约束函数的灵敏度附加项,提出了两种基于灵敏度附加目标函数的可靠性稳健优化设计模型;应用Matlab语言的优化和符号工具箱来实现新型旋转式立体车库载车台主梁结构的可靠性稳健优化设计。算例表明,提出的可靠性稳健优化设计方法具有较高的精度和可靠度,为机械零件的可靠性设计提供了理论依据。     

机械零件的稳健可靠性优化设计

提出一种可以提高机械零件可靠性和稳健性的优化设计方法.用凸集模型描述零件设计中存在的不确定性,采用物理规划方法构造不确定性参数的不满意度函数,通过极小化不满意度函数最差值实现目标函数的稳健性,通过灵敏度分析实现约束函数的稳健性.建立了基于物理规划和灵敏度分析的稳健可靠性优化模型,这种模型是一种嵌套的优化模型,采用分层方法对其求解.通过气门弹簧优化设计实例说明了该方法的有效性和合理性.     

磁力泵密封壳可靠性稳健优化设计研究

为实现磁力泵密封壳的可靠性稳健优化设计,本文在可靠性优化设计理论的基础上,结合敏度分析与稳健设计理论,提出了基于敏度分析的可靠性稳健优化的设计方法。在应力、强度及其他随机变量均服从正态分布的条件下,推导出密封壳优化设计的数学模型。以某型号磁力泵密封壳为例验证提出方法的可行性与实用性,为工程实际中同类产品的设计提供了一定的方法指导。     

空心传动轴的可靠性稳健优化设计

在以单目标为主要型式的普通可靠性优化设计模型的基础上，考虑把可靠性灵敏度也作为一个目标函数融入到可靠性优化设计中，建立起空心传动轴的多目标可靠性稳健优化设计模型。并结合实例说明可靠性稳健优化设计方法比传统设计方法更实用。     

车辆转向机构运动精度的可靠性稳健优化设计

在车辆转向机构设计中,考虑了可控因素和噪声因素对运动精度的影响,将可靠性优化和稳健设计方法相结合,以转向机构运动精度为目标函数建立转向机构的可靠性稳健优化数学模型.把运动精度的可靠性灵敏度溶入可靠性优化设计模型之中,将可靠性稳健优化设计转化为满足可靠性要求的多目标优化问题.实例计算表明,考虑制造误差、运动副间隙等不确定因素的影响,可靠性稳健优化设计方法能有效保证转向机构的运动精度和可靠性.     

Reliability-based robust optimization design of automobile components with non-normal distribution parameters

In the reliability designing procedure of the vehicle components, when the distribution styles of the random variables are unknown or non-normal distribution, the result evaluated contains great error or even is wrong if the reliability value R is larger than 1 by using the existent method, in which case the formula is necessary to be revised. This is obviously inconvenient for programming. Combining reliability-based optimization theory, robust designing method and reliability based sensitivity analysis, a new method for reliability robust designing is proposed. Therefore the influence level of the designing parameters’ changing to the reliability of vehicle components can be obtained. The reliability sensitivity with respect to design parameters is viewed as a sub-objective function in the multi-objective optimization problem satisfying reliability constraints. Given the first four moments of basic random variables, a fourth-moment technique and the proposed optimization procedure can obtain reliability-based robust design of automobile components with non-normal distribution parameters accurately and quickly. By using the proposed method, the distribution style of the random parameters is relaxed. Therefore it is much closer to the actual reliability problems. The numerical examples indicate the following: (1) The reliability value obtained by the robust method proposed increases (>0.04%) comparing to the value obtained by the ordinary optimization algorithm; (2) The absolute value of reliability-based sensitivity decreases (>0.01%), and the robustness of the products’ quality is improved accordingly. Utilizing the reliability-based optimization and robust design method in the reliability designing procedure reduces the manufacture cost and provides the theoretical basis for the reliability and robust design of the vehicle components.     

Reliability-based robust design optimization of vehicle components,Part I: Theory

The reliability-based design optimization, the reliability sensitivity analysis and robust design method are employed to present a practical and effective approach for reliability-based robust design optimization of vehicle components. A procedure for reliability-based robust design optimization of vehicle components is proposed. Application of the method is illustrated by reliability-based robust design optimization of axle and spring. Numerical results have shown that the proposed method can be trusted to perform reliability-based robust design optimization of vehicle components.     

Reliability-based robust design optimization for torque ripple reduction considering manufacturing uncertainty of interior permanent magnet synchronous motor

Journal of Mechanical Science and Technology - This study performed reliability-based robust design optimization (RBRDO) of stator and rotor shape of the IPM type electric motor to reduce the...     

Reliability-based design optimization of slider air bearings

This paper presents a design methodology for determining configurations of slider air bearings considering the randomness of the air-bearing surface (ABS) geometry by using the iSIGHT. A reliability-based design optimization (RBDO) problem is formulated to minimize the variations in the mean values of the flying heights from a target value while satisfying the desired probabilistic constraints keeping the pitch and roll angles within a suitable range. The reliability analysis is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the reliability constraints affected by the random variables. Reliability constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with minimum increase in the objective. The simulation results of the RBDO are listed in comparison with the values of the initial design and the results of the deterministic optimization, respectively. To show the effectiveness of the proposed approach, the reliability analyses are simply carried out by using the mean value first-order second-moment (MVFO) method. The Monte Carlo simulation of the RBDO’s results is also performed to estimate the efficiency of the proposed approach. Those results are demonstrated to satisfy all the desired probabilistic constraints, where the target reliability level for constraints is defined as 0.8.     

高压气瓶强力旋压工艺研究

从旋压毛坯设计、旋压后零件状态确定、旋压参数选择、旋压芯轴和旋轮的设计等几个方面,讨论某型高压气瓶瓶身强力旋压工艺。结合旋压成形试验过程,制定出合理的工艺方案。通过试验验证该工艺方案完全适应高压气瓶瓶身的加工。     

Reliability-based design optimization of time-dependent systems with stochastic degradation

A major hurdle in the application of reliability-based design optimization (RBDO) to time-dependent systems is the continual interplay between calculating time-variant reliability (to ensure reliability policies are met) and moving the design point to optimize some objective function, such as cost, weight, size and so forth. In most cases the reliability can be obtained readily using so-called fast integration methods. However, this option is not available when certain stochastic processes are invoked to model gradual damage or deterioration. In this case, sampling methods must be used. This paper provides a novel way to obviate this inefficiency. First, a meta-model is built to relate time-variant system reliability to the entire design space (and noise space if required). A design of experiments paradigm and Monte Carlo simulation using the mechanistic model determines the corresponding system reliability accurately. A moving least-squares meta-model relates the data. Then, the optimization process to find the best design point, accesses the meta-model to quickly evaluate objectives and reliability constraints. Case-studies include a parallel Daniel's system and a series servo control system. The meta-model approach is simple, accurate and very fast, suggesting an attractive means for RBDO of time-dependent systems.

     

Reliability-based design optimization via high order response surface method

To reduce the computational effort of reliability-based design optimization (RBDO), the response surface method (RSM) has been widely used to evaluate reliability constraints. We propose an efficient methodology for solving RBDO problems based on an improved high order response surface method (HORSM) that takes advantage of an efficient sampling method, Hermite polynomials and uncertainty contribution concept to construct a high order response surface function with cross terms for reliability analysis. The sampling method generates supporting points from Gauss-Hermite quadrature points, which can be used to approximate response surface function without cross terms, to identify the highest order of each random variable and to determine the significant variables connected with point estimate method. The cross terms between two significant random variables are added to the response surface function to improve the approximation accuracy. Integrating the nested strategy, the improved HORSM is explored in solving RBDO problems. Additionally, a sampling based reliability sensitivity analysis method is employed to reduce the computational effort further when design variables are distributional parameters of input random variables. The proposed methodology is applied on two test problems to validate its accuracy and efficiency. The proposed methodology is more efficient than first order reliability method based RBDO and Monte Carlo simulation based RBDO, and enables the use of RBDO as a practical design tool.