微机械陀螺结构的稳健优化设计

本文提出一种基于容差分析的微机械陀螺稳健设计方法,开发了相应的稳健优化设计流程.该方法采用估算目标函数和约束的名义值与扰动值来定义系统稳健性,同时将最坏情况容差作为设计参数的扰动.在集成了器件建模和优化工具的设计环境中开发了相应的自动化设计流程,可用于微机械陀螺的结构设计.优化算法使用遗传算法.讨论了不同的稳健设计方法,结果表明本文的方法能以合适的计算成本获得高质量的结果.系统敏感性分析表明,稳健优化设计结果对误差是不敏感的.采用蒙特卡洛分析检验稳健设计的产出率,结果表明有88%的试验样本是可接受的,而对于确定性优化,仅有50%的可接受样本.微结构已经采用键合-深反应离子刻蚀工艺加工出来.     

虚拟MEMS加工工艺建模、实现与系统验证

利用虚拟现实技术对MEMS加工工艺进行仿真,并将其引入设计环节,最终可以解决MEMS生产中设计与加工脱节的问题。MEMS加工工艺的核心是工艺模型。首先,在深入分析单步MEMS加工工艺的基础上给出了规则描述的工艺模型,其次,利用专家系统技术实现了系统。进一步用一种全新的器件微流量泵的工艺设计和虚拟加工过程验证了系统的可扩充性。     

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．     

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。     

机械稳健设计的研究概况与趋势

机械稳健设计是一种降低生产成本提高产品质量的现代设计方法，本文论述了稳健设计的基本概念，研究概况，存在问题与发展趋势。     

基于双响应面法的公差设计研究

探讨了产品综合成本的构成,以此为基础提出了以产品综合成本最低为目标的公差稳健设计模型,并利用双响应面法(Response Surface Methodology ,RSM) 来实现公差的稳健优化设计。     

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．     

基于田口方法的柔性铰链柔度稳健优化设计

柔顺机构柔度稳健性是柔性机构在微机电系统与精密工程等领域广泛应用的前提和基础,但在实际工程中传统设计方法未充分考虑其稳健性.引入田口稳健优化设计方法,选取柔性铰链各结构参数为可控因素,工作载荷为噪声因子,通过正交试验数据分析得出各个可控因素的信噪比和贡献率,进而选出最佳的参数水平组合,并对柔度综合稳健性能的最优方案进行了验证.算例表明,采用田口稳健优化设计的柔性铰链柔度稳健性比传统方法信噪比水平提高了4.68dB,降低了其质量损失,实现了柔性铰链柔度稳定性优化.田口稳健优化设计方法具有普适性,在实际工程应用中具有较高参考价值.     

单层宽频柔性微穿孔板的加工方法和声学特性研究

针对单层微穿孔板吸声带宽较窄、常规加工方法难以制造超微孔径微穿孔板等技术现状,着重研究了具有较宽吸声频带的单层柔性超微孔微穿孔板的加工方法,包括微机电系统（Micro-Electro-Mechanical System,MEMS）模板浇铸脱模法、热压印穿孔法、针辊式穿孔法、数控铣床穿孔法,并比较、分析了这些加工方法各自的特点。其中MEMS模板浇铸脱模法和数控铣床穿孔法都可以实现孔径小于100 μm的超微孔柔性微穿孔板加工。前者可以实现批量化加工,但成本较高;后者加工精确,但不适合孔径过小、穿孔密度太大的柔性微穿孔板批量化加工。热压印穿孔法和针辊式穿孔法可以实现批量化加工,不过难以加工出孔径100 μm以下的超微孔,且加工误差较大。进而,加工了多种柔性材质的微穿孔板膜片,包括聚二甲基硅氧烷,硬纸板,聚氯乙烯（Polyvinyl Chloride,PVC）,聚碳酸酯,耐高温聚酯。其中,采用数控铣床穿孔法加工的PVC微穿孔板膜片有较好的吸声性能,部分单层PVC微穿孔板的吸声带宽可以达到3倍频程。     

浅析MEMS喷嘴的加工

近年人们试图将MEMS、激光等一些新兴的加工方法引入到喷嘴加工领域。MEMS技术已经用于加工微型推进器,同样的概念,MEMS可以用于加工微喷嘴。我们采用不同测量方法对MEMS加工出的喷嘴几何尺寸进行测量实验,得出其数据的真实差异。     

Lightweight and crashworthiness design of an electric vehicle using a six-sigma robust design optimization method

Design optimization plays an important role in electric vehicle (EV) design. However, fluctuations in design variables and noise factors during the forming process affect the stability of optimization results. This study uses six-sigma robust design optimization to explore the lightweight design and crashworthiness of EVs with uncertainty. A full-scale finite element model of an EV is established. Then, multi-objective design optimization is performed by integrating optimal Latin hypercube sampling, radial basis functions and non-dominated sorting genetic algorithm-II to achieve minimum peak acceleration and mass. Finally, six-sigma robust optimization designs are applied to improve the reliability and sigma level. Robust optimization using adaptive importance sampling is shown to be more efficient than that using Monte Carlo sampling. Moreover, deformation of the battery compartment and peak acceleration of the B-pillar are greatly decreased. The EV’s safety performance is improved and the lightweight effect is remarkable, validating the strong engineering practicability of the method.     

Combining iterative heuristic optimization and uncertainty analysis methods for robust parameter design

A number of investigators have pointed out that products and processes lack quality because of performance inconsistency, which is often due to uncontrollable parameters in the manufacturing process or product usage. Robust design methods are aimed at finding product/process designs that are less sensitive to parameter variation. Robust design of computer simulations requires a large number of runs, which are very time consuming. A novel methodology for robust design is presented in this article. It integrates an iterative heuristic optimization method with uncertainty analysis to achieve effective variability reductions, exploring a large parameter domain with an accessible number of simulations. To demonstrate the effectiveness of this methodology, the robust design of a 0.15 μm CMOS device is shown.     

Structural design of high-performance capacitive accelerometers using parametric optimization with uncertainties

Electrostatic or capacitive accelerometers are among the highest volume microelectromechanical systems (MEMS) products nowadays. The design of such devices is a complex task, since they depend on many performance requirements, which are often conflicting. Therefore, optimization techniques are often used in the design stage of these MEMS devices. Because of problems with reliability, the technology of MEMS is not yet well established. Thus, in this work, size optimization is combined with the reliability-based design optimization (RBDO) method to improve the performance of accelerometers. To account for uncertainties in the dimensions and material properties of these devices, the first order reliability method is applied to calculate the probabilities involved in the RBDO formulation. Practical examples of bulk-type capacitive accelerometer designs are presented and discussed to evaluate the potential of the implemented RBDO solver.     

复合材料机翼鲁棒气动弹性优化设计

针对气动弹性结构, 利用遗传-敏度混合算法开展鲁棒优化设计。以大展弦比复合材料机翼的鲁棒气动弹性结构优化设计为例验证了鲁棒设计方法的适用性和有效性, 比较了鲁棒结构优化设计与传统优化设计的区别。研究结果表明: 在设计变量存在不确定性的情况下, 考虑鲁棒性约束优化得到的结构较传统优化结构具有更好的抗干扰性; 但鲁棒性的满足是以增加结构质量为代价的, 鲁棒性要求越高, 结构增重越明显。      

A new interval optimization method considering tolerance design

This study considers the design variable uncertainty in the actual manufacturing process for a product or structure and proposes a new interval optimization method based on tolerance design, which can provide not only an optimal design but also the allowable maximal manufacturing errors that the design can bear. The design variables' manufacturing errors are depicted using the interval method, and an interval optimization model for the structure is constructed. A dimensionless design tolerance index is defined to describe the overall uncertainty of all design variables, and by combining the nominal objective function, a deterministic two-objective optimization model is built. The possibility degree of interval is used to represent the reliability of the constraints under uncertainty, through which the model is transformed to a deterministic optimization problem. Three numerical examples are investigated to verify the effectiveness of the present method.     

An Affordable Approach for Robust Design of Thick Laminated Composite Structure

A systematic and affordable approach is proposed for the robust design of thick laminated composite structures. Our approach integrates the principles of the Robust Concept Exploration Method (RCEM) for designing complex engineering systems and the hierarchical multi-level optimization procedure for managing the complexity of composite structure optimization. Foundational to the proposed approach is the use of Design of Experiments (DOE) techniques and the Response Surface Methodology (RSM) for improving computational efficiency in using high fidelity design simulations; and the use of the robust design method for improving the quality of a product that is insensitive to potential variations of design parameters. Our approach is illustrated through the design of a laminated composite femoral component for hip joint arthroplasty. The solution yields the robust design of a composite hip implant, which is applicable for a range of bone stiffness, thereby eliminating the need to design specifically for an individual.     

考虑不确定性的多学科设计优化方法研究综述

目的研究多学科不确定性设计优化中多学科设计优化方法、不确定性建模与传递、不确定性设计优化的相关理论。方法通过研究并分析国内外相关文献,总结归纳考虑不确定性的多学科设计优化中的耦合系统解耦方法、参数和代理模型不确定性的建模方法,以及高效的不确定性传递和设计优化方法。结论系统探讨了在面对复杂多变的外界环境时,多学科设计优化对不确定性量化与传递的需求,提出多学科设计优化不仅要考虑确定性的系统,而且需要考虑由于外界环境变化导致的系统响应的不确定性。针对现有的多学科不确定性设计优化方法的理论研究,提出提高计算效率的关键在于将传统的三层嵌套循环计算框架解耦成单层循环。研究结果表明,考虑不确定性的多学科设计优化将成为复杂多学科系统设计的有力支撑,能显著提高系统的可靠性和稳健性,提高使用寿命,同时能够加快产品的更新换代设计。     

A method for the preliminary design of gears using a reduced number of American Gear Manufacturers Association (AGMA) correction factors

Typically, the preliminary design of mechanical components such as gears is carried out using standardized design processes such as those developed by the American Gear Manufacturers Association (AGMA). These design standards include a large number of ‘correction factors’ to account for various uncertainties. As the knowledge about these uncertainties increases, it becomes possible to include them systematically in the design procedure, thereby reducing the number of empirical correction factors. Robust design provides a way to design in the presence of various uncertainties. In this article, a design method is proposed to eliminate empirical correction factors and is demonstrated by eliminating two correction factors from the AGMA design standards for a spur gear, namely, the factor of safety in contact and the reliability factor by the formal introduction of uncertainty in the magnitude of load and material properties. The proposed method is illustrated with the design of an automotive gear with desired reliability, cost and robustness.     

Robust design using Bayesian Monte Carlo

In this paper, we propose an efficient strategy for robust design based on Bayesian Monte Carlo simulation. Robust design is formulated as a multiobjective problem to allow explicit trade‐off between the mean performance and variability. The proposed method is applied to a compressor blade design in the presence of manufacturing uncertainty. Process capability data are utilized in conjunction with a parametric geometry model for manufacturing uncertainty quantification. High‐fidelity computational fluid dynamics simulations are used to evaluate the aerodynamic performance of the compressor blade. A probabilistic analysis for estimating the effect of manufacturing variations on the aerodynamic performance of the blade is performed and a case for the application of robust design is established. The proposed approach is applied to robust design of compressor blades and a selected design from the final Pareto set is compared with an optimal design obtained by minimizing the nominal performance. The selected robust blade has substantial improvement in robustness against manufacturing variations in comparison with the deterministic optimal blade. Significant savings in computational effort using the proposed method are also illustrated. Copyright © 2007 John Wiley & Sons, Ltd.     

A robust optimization methodology for preliminary aircraft design

This article focuses on a robust optimization of an aircraft preliminary design under operational constraints. According to engineers' know-how, the aircraft preliminary design problem can be modelled as an uncertain optimization problem whose objective (the cost or the fuel consumption) is almost affine, and whose constraints are convex. It is shown that this uncertain optimization problem can be approximated in a conservative manner by an uncertain linear optimization program, which enables the use of the techniques of robust linear programming of Ben-Tal, El Ghaoui, and Nemirovski [Robust Optimization, Princeton University Press, 2009]. This methodology is then applied to two real cases of aircraft design and numerical results are presented.