Optimization of the light distribution of luminaries for tunnel and street lighting

An optimization approach is discussed for the problem of designing light distributions for luminaries for tunnel and street lighting which satisfy luminance-based and glare-based requirements set by the International Commision on Illumination (CIE) and the European Committee for Standardization (CEN) while consuming minimal power. The problem is formulated as a linear optimization problem that incorporates the geometrical parameters of the lighting installation and the reflective properties of the road surface. A polynomial representation for the light intensities is used in order to construct smooth light distribution curves, so that the luminaries can be manufactured with existing technology. Computational experiments indicate that optimization models can substantially improve the lighting parameters of luminaries, and make lighting installations more energy-efficient.     

新型智能路灯照明调控系统

路灯照明光源通常是高压钠灯和汞灯,调控设备具有变压与稳压的双重功能,通过控制电路和时控电路,实现最优化的智能控制。智能照明调控装置,通过补偿变压器、多抽头变压器,实现主回路输出电压的增减。智能照明调控设备结合节能产品的优点,并克服存存的缺陷。     

A multicriteria evolutionary algorithm for mechanical design optimization with expert rules

This paper addresses the problem of optimizing mechanical components during the first stage of the design process. While a previous study focused on parameterized designs with fixed configurations—which led to the development of the PAMUC (Preferences Applied to Multiobjectivity and Constraints) method, to tackle constraints and preferences in evolutionary algorithms (EAs)—, the models to be considered in this work are enriched by the presence of topological variables. In this context, in order to create optimal but also realistic designs, i.e. fulfilling not only technical requirements but also technological constraints (more naturally expressed in terms of rules), a novel approach is proposed: PAMUC II. It consists in integrating an inference engine within the EA to repair the individuals violating the user‐defined rules. PAMUC II is tested on mechanical benchmarks, and provides very satisfactory results in comparison with a weighted sum method with penalization to deal with the constraints. Copyright © 2004 John Wiley & Sons, Ltd.     

Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives

The current competitive situation increases the importance of realistically estimating product costs during the early phases of product and assembly line planning projects. In this article, several multi-objective algorithms using difference dominance rules are proposed to solve the problem associated with the selection of the most effective combination of product and assembly lines. The list of developed algorithms includes variants of ant colony algorithms, evolutionary algorithms and imperialist competitive algorithms. The performance of each algorithm and dominance rule is analysed by five multi-objective quality indicators and fifty problem instances. The algorithms and dominance rules are ranked using a non-parametric statistical test.     

A parallel bi-level multidisciplinary design optimization architecture with convergence proof for general problem

Quite a number of distributed Multidisciplinary Design Optimization (MDO) architectures have been proposed for the optimal design of large-scale multidisciplinary systems. However, just a few of them have available numerical convergence proof. In this article, a parallel bi-level MDO architecture is presented to solve the general MDO problem with shared constraints and a shared objective. The presented architecture decomposes the original MDO problem into one implicit nonlinear equation and multiple concurrent sub-optimization problems, then solves them through a bi-level process. In particular, this architecture allows each sub-optimization problem to be solved in parallel and its solution is proven to converge to the Karush–Kuhn–Tucker (KKT) point of the original MDO problem. Finally, two MDO problems are introduced to perform a comprehensive evaluation and verification of the presented architecture and the results demonstrate that it has a good performance both in convergence and efficiency.     

严寒地区太阳能-地源热泵耦合系统的优化设计

针对严寒地区的负荷特点,并结合实际项目,设计一套太阳能-地源热泵耦合系统。对系统的热平衡进行计算分析,优化太阳能的补热运行方式,保证系统在严寒地区高效、稳定运行,系统的节能环保效益显著。     

A global single-loop deterministic approach for reliability-based design optimization of truss structures with continuous and discrete design variables

A single-loop deterministic method (SLDM) has previously been proposed for solving reliability-based design optimization (RBDO) problems. In SLDM, probabilistic constraints are converted to approximate deterministic constraints. Consequently, RBDO problems can be transformed into approximate deterministic optimization problems, and hence the computational cost of solving such problems is reduced significantly. However, SLDM is limited to continuous design variables, and the obtained solutions are often trapped into local extrema. To overcome these two disadvantages, a global single-loop deterministic approach is developed in this article, and then it is applied to solve the RBDO problems of truss structures with both continuous and discrete design variables. The proposed approach is a combination of SLDM and improved differential evolution (IDE). The IDE algorithm is an improved version of the original differential evolution (DE) algorithm with two improvements: a roulette wheel selection with stochastic acceptance and an elitist selection technique. These improvements are applied to the mutation and selection phases of DE to enhance its convergence rate and accuracy. To demonstrate the reliability, efficiency and applicability of the proposed method, three numerical examples are executed, and the obtained results are compared with those available in the literature.     

普光气田钻井井身结构优化设计及管材优选技术

普光气田是我国迄今发现的最大的高酸性整装气田,但由于其地质环境异常复杂,目的层深且存在"斜、塌、喷、漏、硬、毒"等世界级工程技术难题,钻井难度大且风险高。分析了普光气田复杂的地质特点,提出了井身结构优化设计和管材优选思路。根据开发认识的加深及要求论述了4种相应井身结构优化方案,介绍了应用效果并作了相应分析。通过井身结构优化设计实现了用尽可能少的套管程序封隔地层的必封点,提供尽可能大的完井井眼,以保证固井质量和满足高产需求,从而最终实现安全、经济的开发目的。     

Conceptual robustness in simultaneous engineering: An extension of Taguchi's parameter design

Simultaneous engineering processes involve multifunctional teams; team members simultaneously make decisions about many parts of the product-production system and aspects of the product life cycle. This paper argues that such simultaneous distributed decisions should be based on communications about sets of possibilities rather than single solutions. By extending Taguchi's parameter design concepts, we develop a robust and distributed decision-making procedure based on such communications. The procedure shows how a member of a design team can make appropriate decisions based on incomplete information from the other members of the team. More specifically, it (1) treats variations among the designs considered by other members of the design team asconceptual noise; (2) shows how to incorporate such noises into decisions that are robust against these variations; (3) describes a method for using the same data to provide preference information back to the other team members; and (4) provides a procedure for determining whether to release theconceptually robust design or to wait for further decisions by others. The method is demonstrated by part of a distributed design process for a rotary CNC milling machine. While Taguchi's approach is used as a starting point because it is widely known, these results can be generalized to use other robust decision techniques.     

The constraints satisfaction problem approach in the design of an architectural functional layout

A design support system with a new strategy for finding the optimal functional configurations of rooms for architectural layouts is presented. A set of configurations satisfying given constraints is generated and ranked according to multiple objectives. The method can be applied to problems in architectural practice, urban or graphic design—wherever allocation of related geometrical elements of known shape is optimized. Although the methodology is shown using simplified examples—a single story residential building with two apartments each having two rooms—the results resemble realistic functional layouts. One example of a practical size problem of a layout of three apartments with a total of 20 rooms is demonstrated, where the generated solution can be used as a base for a realistic architectural blueprint. The discretization of design space is discussed, followed by application of a backtrack search algorithm used for generating a set of potentially ‘good’ room configurations. Next the solutions are classified by a machine learning method (FFN) as ‘proper’ or ‘improper’ according to the internal communication criteria. Examples of interactive ranking of the ‘proper’ configurations according to multiple criteria and choosing ‘the best’ ones are presented. The proposed framework is general and universal—the criteria, parameters and weights can be individually defined by a user and the search algorithm can be adjusted to a specific problem.     

The cognitive basis of emergence: implications for design support

Emergent shapes play a significant role in the creative design process. Designers frequently visualize emergent shapes and structure their understanding of the design and their reasoning about it in terms of emergent entities and relations. In design research, effort has concentrated on developing computational models capable of representing emergent shapes. Much less attention has been paid to the cognitive processes that give rise to emergence. In cognitive science, however, emergence has been the subject of empirical study. It is suggested that both the study of perception and that of mental imagery can contribute to understanding the cognitive psychological basis of emergence and the nature of emergent shapes that arise. Relevant cognitive science research findings are reviewed in this paper. Based on these findings two main classes of emergence processes are developed. Their implications for the development of user-interactive computational models of emergent shapes are then discussed.     

Multi-agent genetic algorithm with controllable mutation probability utilizing back propagation neural network for global optimization of trajectory design

A Controllable Mutation Probability (CMP) strategy is proposed and applied to a Multi-Agent Genetic Algorithm (MAGA) to deal with the global optimization of trajectory design in deep space, which is called MGA-CMP. MAGA-CMP is an algorithm setting all the individuals (or agents) on a grid and having two controlling functions to adjust the performance probability of a mutation operator. It pays more attention to global search in the earlier part of the process, and devotes more effort to local search at later stages. Four experiments are implemented to illustrate the efficiency of MAGA-CMP, and results show that MGA-CMP performs better in most examined cases than other well-known search algorithms.     

The use of nested desirability functions and quality indices for multi-response robust parameter design problems

A multi-response robust parameter design (RPD) problem-solving technique based on desirability functions is presented in which the means and variances of all responses are placed on a level playing field. The proposal allows a decision maker to integrate their preferences for the individual means and variances. It is shown that the ensuing operating point is a system setting that produces a mutually robust set of responses. In addition, this article offers an approach to assess several RPD strategies via quality indices. The measures presented here allow for a more knowledgeable and comprehensive evaluation of the competing RPD strategies.     

Self-organizing maps for pattern recognition in design of alloys

A combined experimental–computational methodology for accelerated design of AlNiCo-type permanent magnetic alloys is presented with the objective of simultaneously extremizing several magnetic properties. Chemical concentrations of eight alloying elements were initially generated using a quasi-random number generator so as to achieve a uniform distribution in the design variable space. It was followed by manufacture and experimental evaluation of these alloys using an identical thermo-magnetic protocol. These experimental data were used to develop meta-models capable of directly relating the chemical composition with desired macroscopic properties of the alloys. These properties were simultaneously optimized to predict chemical compositions that result in improvement of properties. These data were further utilized to discover various correlations within the experimental dataset by using several concepts of artificial intelligence. In this work, an unsupervised neural network known as self-organizing maps was used to discover various patterns reported in the literature. These maps were also used to screen the composition of the next set of alloys to be manufactured and tested in the next iterative cycle. Several of these Pareto-optimized predictions out-performed the initial batch of alloys. This approach helps significantly reducing the time and the number of alloys needed in the alloy development process.     

任意分布参数的机械零件的可靠性稳健设计（二）：轴

 应用具有任意分布参数机械零件可靠性稳健设计的理论方法，对具有任意分布参数机械典型轴系零件如半轴、前轴和后桥进行了可靠性稳健设计，给出了计算仿真分析结果，对工程实际的机械零件的可靠性稳健设计提供了理论依据。     

Reliability-oriented optimal design of intentional mistuning for a bladed disk with random and interval uncertainties

When interblade coupling is weak, the dynamic response of a bladed disk is very sensitive to the presence of uncertainties. Excessive response variation can be very harmful. Previous studies have indicated that introducing blade-to-blade difference in nominal design, known as intentional mistuning, could reduce the level of response variation. In this research, an efficient computational framework that yields the optimal design of intentional mistuning is developed to maximize the bladed disk reliability. Both the random uncertainty of blades and the interval uncertainty of disk connections are considered. The Metropolis–Hastings algorithm is applied to find the worst case response under interval uncertainty, and Monte Carlo simulation is employed to account for the random mistuning effect. A gradient-based approach is then established to find the minimum design modification needed to achieve a designated reliability level. Case studies are carried out to illustrate the effectiveness of the proposed method.     

任意分布参数的机械零件的可靠性稳健设计（三）：弹簧

 应用具有任意分布参数机械零件可靠性稳健设计的理论方法，对具有任意分布参数机械典型弹簧系零件如扭杆弹簧和螺旋弹簧，进行了可靠性稳健设计，给出了计算仿真分析结果，对工程实际的机械零件的可靠性稳健设计提供了理论依据．     

Decision monotonicity in incremental design: A case study of design for manufacture

Design has often been described as searching the space of solutions to a given problem for either a feasible or optimal solution. Usually, this search is conducted in an incremental, iterative manner. Unfortunately, there is a tendency for the feasible space in some domains to exhibit such poor structure that the incremental design process becomes both difficult and time consuming. This is especially true in the domain of design-for-manufacture by machining. In this paper we present the view that in such cases the sources of ill-structure must be aggressively eliminated by making strategic improvements and modifications to the target technology. To illustrate this point, we show that the domain of design-for-manufacture is ill-structured due to a class of interactions known as global interactions. We then show how global interactions can be virtually eliminated by a combination of a new workholding technology and a new interfacing technique. In the absence of global interactions, we show how the design structure exhibits a property of monotonicity. We describe the ramifications of this monotonicity on the design process, and show how design can then be considered to be deterministic. As a backdrop, we draw examples from other fields where similar strategies have resulted in greater designability.     

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。     

考虑结构损伤的消能减震结构能量设计方法

RC框架结构在地震作用下多出现局部楼层损伤明显或抗力不足问题,通过对抗侧力构件性能的合理优化可实现各楼层损伤程度相近的设计效果,消除薄弱层,达到更为理想的均匀损伤分布模式。提出RC框架结构的均匀损伤设计方法,以各楼层损伤指数相等或相近为优化目标,各层框架柱配筋率为优化变量,通过智能算法与有限元平台协同计算技术,实现RC框架结构均匀损伤优化设计,并采用弹塑性时程分析和IDA方法对优化效果进行验证分析。结果表明,通过智能算法优化框架柱配筋方案可以有效调控结构各层损伤程度,不同地震波作用下结构最优配筋率分布是不完全相同的,并且框架柱的最优配筋率分布也未呈现明显的统计规律,但将不同地震波下优化结果的均值作为框架柱配筋方案可以提高结构抗震能力,该优化方法合理有效。