非均质床垫硬度测试的方法及改进

针对使用较广泛的EN 1957:2012与QBT 1952.2-2011(LGA法)床垫硬度测试方法,提出了3种优化方法。首先,设置2个实验对比组：1组为8款弹簧床垫,另1组为8款海绵床垫,利用特制测试仪测得各床垫的加载挠度曲线,并假设这2组实验床垫因材料的不同其硬度有明显差异;其次,分别使用LGA测试方法及3种优化方法对2组实验床垫进行测算;最后,利用组间和组内t检验得出较好的测算方法。结果显示：LGA测试方法及优化方法2对床垫硬度的测试基于人为规定,测试结果不具有唯一性;优化方法2、3显示2组间的硬度有明显差异,与假设相符;优化方法3对床垫硬度值的测算具有唯一性,且不受测试设备的影响,是较为理想的优化方法。     

智能温控床垫的设计与研究

目的 睡眠温度是影响睡眠的重要因素。设计一款基于睡眠温度曲线的三分区智能温控床垫,通过分区、分时段调整睡眠温度,有效改善用户睡眠质量。方法 通过温度记录仪,记录并绘制人体不同部位的睡眠温度曲线。根据人体在睡眠期间不同时间段及不同部位的温度需求,将床垫分为头肩、躯干和腿部三个区域,通过分区、分时段进行温度控制,使人体在睡眠期间各区域、各时间段均处于睡眠温度舒适域内。针对硬件、软件和结构三个方面,以智能化和人性化为原则,对智能温控床垫进行创新性设计。结果 实验结果显示,该床垫实现了高精度的分区、分时段温度控制,同时能够按照用户设定进行温控时段和制热制冷自适应调整。结论 该床垫温度控制精准、安全高效、智能化和人性化程度高,能够有效改善用户睡眠质量。     

Design of a rotational three-dimensional nonimaging device by a compensated two-dimensional design process

A compensation process has been developed to design rotational three-dimensional (3D) nonimaging devices. By compensating the desired light distribution during a two-dimensional (2D) design process for an extended Lambertian source using a compensation coefficient, the meridian plane of a 3D device with good performance can be obtained. This method is suitable in many cases with fast calculation speed. Solutions to two kinds of optical design problems have been proposed, and the limitation of this compensated 2D design method is discussed.     

A Geodesign Method of Human-Energy-Water Interactive Systems for Urban Infrastructure Design: 10KM2 Near-Zero District Project in Shanghai

The grand challenges of climate change demand a new paradigm of urban design that takes the performance of urban systems into account, such as energy and water efficiency. Traditional urban design methods focus on the form-making process and lack performance dimensions. Geodesign is an emerging approach that emphasizes the links between systems thinking, digital technology, and geographic context. This paper presents the research results of the first phase of a larger research collaboration and proposes an extended geodesign method for a district-scale urban design to integrate systems of renewable energy production, energy consumption, and storm water management, as well as a measurement of human experiences in cities. The method incorporates geographic information system (GIS), parametric modeling techniques, and multidisciplinary design optimization (MDO) tools that enable collaborative design decision-making. The method is tested and refined in a test case with the objective of designing a near-zero-energy urban district. Our final method has three characteristics. ① Integrated geodesign and parametric design: It uses a parametric design approach to generate focal-scale district prototypes by means of a custom procedural algorithm, and applies geodesign to evaluate the performances of design proposals. ② A focus on design flow: It elaborates how to define problems, what information is selected, and what criteria are used in making design decisions. ③ Multi-objective optimization: The test case produces indicators from performance modeling and derives principles through a multi-objective computational experiment to inform how the design can be improved. This paper concludes with issues and next steps in modeling urban design and infrastructure systems based on MDO tools.     

Robustness of reduced‐order observer‐based feedback control for discrete two‐time‐scale systems

Abstract

A design method to achieve robust stability and performance criteria for discrete two‐time‐scale systems controlled by low‐order observer‐based compensators is proposed. Sufficient conditions for stability and performance robustness are established by an easy extension of the small gain theorem. The theoretical analysis is illustrated by a numerical example.     

A constraint‐based approach for the optimum redesign of a packaging operation

The task of the design engineer is to configure a design such that a predetermined functional requirement is fulfilled, and that it is achieved within a given set of performance criteria. As a design evolves, so these performance criteria change, driven by the ever‐increasing needs of the customer and the inherent competition between manufacturers. It is during this evolutionary process that the engineer demands a CAD system which can represent knowledge about the design and explore solutions regarding the relationship between geometry and behaviour. This is necessary in order to realize the full potential of an existing design, or to examine modifications to an existing design that may achieve the desired performance characteristics. The work described in this paper uses a constraint‐based modelling environment to represent and analyse a high‐speed packaging operation. The goal of the modelling work is to produce an optimal design solution for the given performance requirements, as well as to satisfy the constraints imposed by the existing machine system and packaging process. The construction of the model is described and the identification and representation of the design constraints are discussed. These constraints are then applied to a possible machine modification or redesign and an optimized configuration is developed in the modelling environment. Copyright © 2003 John Wiley & Sons, Ltd.     

Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions.     

低振动旋翼桨尖代理优化设计

为探索直升机低振动旋翼的工程设计方法,将代理优化与旋翼气弹耦合分析相结合,开展了旋翼桨尖几何外形设计,推导了非平直桨叶气弹动力学方程,训练了旋翼功率、模态阻尼以及振动载荷预测的Kriging代理模型.以气动性能与气弹稳定性为约束,以桨毂振动载荷最小化为目标,采用自适应加点准则设计了优化流程.以某旋翼为例,计算了其气动性...     

A human‐like numerical technique for design of engineering systems

Because of the necessity for considering various creative and engineering design criteria, optimal design of an engineering system results in a highly‐constrained multi‐objective optimization problem. Major numerical approaches to such optimal design are to force the problem into a single objective function by introducing unjustifiable additional parameters and solve it using a single‐objective optimization method. Due to its difference from human design in process, the resulting design often becomes completely different from that by a human designer. This paper presents a novel numerical design approach, which resembles the human design process. Similar to the human design process, the approach consists of two steps: (1) search for the solution space of the highly‐constrained multi‐objective optimization problem and (2) derivation of a final design solution from the solution space. Multi‐objective gradient‐based method with Lagrangian multipliers (MOGM‐LM) and centre‐of‐gravity method (CoGM) are further proposed as numerical methods for each step. The proposed approach was first applied to problems with test functions where the exact solutions are known, and results demonstrate that the proposed approach can find robust solutions, which cannot be found by conventional numerical design approaches. The approach was then applied to two practical design problems. Successful design in both the examples concludes that the proposed approach can be used for various design problems that involve both the creative and engineering design criteria. Copyright © 2005 John Wiley & Sons, Ltd.     

Optimal design approach for eco-efficient machine tool bed

An optimal design approach of machine tool bed with the aim of obtaining an eco-efficient machine structure is studied. The suggested method includes three phases. The first is the layout design optimization of stiffener plates inside bed. In order to improve the design efficiency, a simplified design model called fiber model is suggested, and the layout of the stiffener plates inside bed is optimized by changing a 3-dimensional topology design optimization problem to a 2-dimensional problem. The second is the detailed sizing optimization of stiffener plates and supporting blocks under the structure based on the initial optimal model resulted from phase one. Finally, a topology design optimization process is implemented to obtain a reasonable distribution of manufacturing holes in bed structure. By considering the manufacturing requirement, an optimal bed structure is obtained. The validity of the suggested method is confirmed by a typical cylindrical grinding machine tool bed, and the result shows that the suggested method is effective, and the optimal structure has much better mechanical and economical performance by comparing with the original structures.     

Quantifying and using expert opinion for variable-selection problems in regression

This paper gives a general method for use in the chemical industry for eliciting and quantifying an expert's subjective opinion concerning a normal linear regression model. The intention is to ask the expert assessment questions that he or she can meaningfully answer and to use the elicited values to determine a probability distribution on the regression parameters that quantifies and expresses the expert's opinions. A regression model may represent a chemical production process, for example, and the corresponding elicited distribution would embody the expert's opinion concerning the effects on product output of independent variables for process control and environmental factors. It may be uncertain what independent variables should be featured in the regression, so the expert's opinion is represented by a mixture of multivariate distributions, where each distribution in the mixture corresponds to a different subset of independent variables. Among the uses to which an elicited distribution might be put is design of experiments, discussed here with regard to Bayesian design criteria. An example is given of the elicitation and use of a subjective distribution in which an industrial chemist quantified his opinion about a chemical process.     

A shock process with a non-cumulative damage

Two types of non-cumulative damage shock models are considered. Based on the distribution of damage, caused by a shock effecting a system, the intervals with small, intermediate and large damage are introduced. The initial homogeneous Poisson shock process is split into three homogeneous Poisson processes and studied independently. Several criteria of failure are considered, based on the assumption that shocks with a small level of damage are harmless for a system, shocks with a large level of damage results in the system's failure and shocks with an intermediate level of damage can result in the system's failure only with some probability. The second model is based on an assumption that shocks with a small level of damage are harmless to a system, if they are not too close to each other. The probability of the system's failure-free performance in [0,t) is derived explicitly. Simple asymptotic exponential approximations are obtained The accuracy of this method is analyzed. Possible generalizations are discussed.     

Process capability: a criterion for optimizing multiple response product and process design

In this research, we consider the maximization of process capability as the criterion in product/process design that is used for selecting preferred design factor levels and propose several approaches for single and multiple response performance measure designs. All of these approaches assume that the relationship between a process performance measure and a set of design factors is represented via an estimate of a response surface function. In particular, we develop; (i) criteria for selecting an optimal design, which we call MCpk and MCpm; (h) mathematical programming formulations for maximizing MCpk and MCpm, including formulations for maximizing the desirability index (Harrington, 1965) and for maximizing the standardized performance criteria (Barton and Tsui, 1991) as special cases of the formulation for maximizing MCpk, (iii) formulations for considering cost when maximizing MCpk and MCpm, (iv) a means for assessing propagation of error; (v) a robust design method for assessing design factor effects on residual variance; (vi) a means for assessing the optimality of a proposed solution: and (vii) an original application in the screening of printed circuit board panels.     

Probabilistic uncertainty analysis by mean-value first order Saddlepoint Approximation

Probabilistic uncertainty analysis quantifies the effect of input random variables on model outputs. It is an integral part of reliability-based design, robust design, and design for Six Sigma. The efficiency and accuracy of probabilistic uncertainty analysis is a trade-off issue in engineering applications. In this paper, an efficient and accurate mean-value first order Saddlepoint Approximation (MVFOSA) method is proposed. Similar to the mean-value first order Second Moment (MVFOSM) approach, a performance function is approximated with the first order Taylor expansion at the mean values of random input variables. Instead of simply using the first two moments of the random variables as in MVFOSM, MVFOSA estimates the probability density function and cumulative distribution function of the response by the accurate Saddlepoint Approximation. Because of the use of complete distribution information, MVFOSA is generally more accurate than MVFOSM with the same computational effort. Without the nonlinear transformation from non-normal variables to normal variables as required by the first order reliability method (FORM), MVFOSA is also more accurate than FORM in certain circumstances, especially when the transformation significantly increases the nonlinearity of a performance function. It is also more efficient than FORM because an iterative search process for the so-called Most Probable Point is not required. The features of the proposed method are demonstrated with four numerical examples.     

Development of a simple and efficient method for robust optimization

Robust optimization problems are newly formulated and an efficient computational scheme is proposed. Both design variables and design parameters are considered as random variables about their nominal values. To ensure the robustness of objective performance, we introduce a new performance index bounding the performance together with a constraint limiting the performance variation. The constraint variations are regulated by considering the probability of feasibility. Each probability constraint is transformed into a sub‐optimization problem by the advanced first‐order second moment (AFOSM) method for computational efficiency. The proposed robust optimization method has the advantages that the mean value and the variation of the performance function are controlled simultaneously and rationally and the second‐order sensitivity information is not required even in case of gradient‐based optimization process. The suggested method is examined by solving three examples and the results are compared with those for the deterministic case and those available in the literature. Copyright © 2002 John Wiley & Sons, Ltd.     

Design of a composite structure to achieve a specified reliability level

Safety factors are widely used in structural design. For composite material structures, however, the lack of experimental feed-back does not allow the use of safety factors optimized from cost and reliability point of view. Reliability methods are one way to achieve the calibration of partial safety factors using a more rational method than judgement alone. First we present the calibration process. The reliability methods FORM, SORM, simulation, are initially applied to a laminate plate under uniform pressure. In this example, we compare three design criteria; the different reliability methods agree with the reference method for all criteria used. We chose the Tsai-Hill criteria and the FORM method to calculate safety factors. Then, a calibration process is undertaken on a composite pipe and this serves to illustrate the different steps in the calculation. Finally, we present a calibration of a general plate structure. The partial safety factors and their sensitivities to the different parameters of the stochastic variables are given according to load type.     

Bayesian calculation of cost optimal burn-in test durations for mixed exponential populations

The burn-in process is a part of the production process whereby manufactured products are operated for a short period of time before release. In this paper, a Bayesian method is developed for calculating the optimal burn-in duration for a batch of products whose life distribution is modeled as a mixture of two (denoted ‘strong’ and ‘weak’) exponential sub-populations. The criteria used is the minimization of a total expected cost function reflecting costs related to the burn-in process and to product failures throughout a warranty period. The expectation is taken with respect to the mixed exponential failure model and its parameters. The prior distribution for the parameters is constructed using a beta density for the mixture parameter and independent gamma densities for the failure rate parameters of the sub-populations. It is assumed that the optimal burn-in time is selected in advance and remains fixed throughout the burn-in process. When additional failure information is available prior to the burn-in process, the minimization of posterior total cost is used as the criteria for selecting the optimal burn-in time. Expressions for the joint posterior distribution and cost are provided for the case of both complete and truncated data. The method is illustrated with an example.     

A new measure for supplier performance evaluation

Recently the concept of dimensional analysis was used to propose a supplier performance measure and to obtain an index called the VPI (Vendor Performance Index). Usually the performance criteria used in supplier performance evaluation include quantitative and qualitative criteria. Here a new supplier performance measure is proposed as an alternative to the VPI. For qualitative criteria, a two-directional consideration is used instead of a one-directional approach, which results in only a single score. The fuzzy bag method is used to compensate for blindness in human judgement. Then all scores for quantitative and qualitative criteria are combined in an intuitive sum of weighted averages called the SUR. The SUR is illustrated and compared with the VPI by means of two examples.