Data Driven Uncertainty Evaluation for Complex Engineered System Design

Complex engineered systems are often difficult to analyze and design due to the tangled interdependencies among their subsystems and components. Conventional design methods often need exact modeling or accurate structure decomposition, which limits their practical application. The rapid expansion of data makes utilizing data to guide and improve system design indispensable in practical engineering. In this paper, a data driven uncertainty evaluation approach is proposed to support the design of complex engineered systems. The core of the approach is a data-mining based uncertainty evaluation method that predicts the uncertainty level of a specific system design by means of analyzing association relations along different system attributes and synthesizing the information entropy of the covered attribute areas, and a quantitative measure of system uncertainty can be obtained accordingly. Monte Carlo simulation is introduced to get the uncertainty extrema, and the possible data distributions under different situations is discussed in detail The uncertainty values can be normalized using the simulation results and the values can be used to evaluate different system designs. A prototype system is established, and two case studies have been carded out. The case of an inverted pendulum system validates the effectiveness of the proposed method, and the case of an oil sump design shows the practicability when two or more design plans need to be compared. This research can be used to evaluate the uncertainty of complex engineered systems completely relying on data, and is ideally suited for plan selection and performance analysis in system design.

Evaluating the conceptual design schemes of complex products based on FAHP using fuzzy number

In the conceptual design stage of complex products, CBR（Case-Based Reasoning） tool is useful to offer a feasible set of schemes. Then the most adaptive scheme can be generated through a procedure of comparison and evaluation. The procedure is essentially a multiple criteria decision-making problem. The traditional multiple criteria programming is not flexible enough in executing the system evaluation algorithm due to both the limited experimental data and the lack of human experiences. To make the CBR tool to be more efficient, a new method for the best choice among the feasible schemes based on the Fuzzy AHP using Fuzzy numbers （FFAHP） is proposed. Since the final results become a problem of ranking the mean of fuzzy numbers by the optimism of decision-maker using the FFAHP, its execution is much more intuitive and effective than with the traditional method.

Special Issue on Innovative Design of Complex Products

With the development of science and technology as well as the diversification and individualization of market demand,modern products update more and more rapidly.e rapid development of new products to satisfy the increasingly improved and personalized customer demands greatly depends on the progress in the innovative design theory and performance optimization

The Complex System Modeling Method Based on Uniform Design and Neural Network

In this paper, the method based on uniform design and neural network is proposed to model the complex system. In order to express the system characteristics all round, uniform design method is used to choose the modeling samples and obtain the overall information of the system;for the purpose of modeling the system or its characteristics, the artificial neural network is used to construct the model. Experiment indicates that this method can model the complex system effectively.

Design of complex FIR filters with arbitrary magnitude and group delay responses

To design approximately linear-phase complex coefficient finite impulse response （FIR） digital filters with arbitrary magnitude and group delay responses, a novel neural network approach is studied. The approach is based on a batch back-propagation neural network algorithm by directly minimizing the real magnitude error and phase error from the linear-phase to obtain the filter＇s coefficients. The approach can deal with both the real and complex coefficient FIR digital filters design problems. The main advantage of the proposed design method is the significant reduction in the group delay error. The effectiveness of the proposed method is illustrated with two optimal design examples.

Design of Complex Waveform for Detection of Ship and Aircraft Targets by a HF Radar

This paper presents a complex design of frequency modulated interrupted continuous wave (FMICW) and frequency-coded pulses (FCP) for detection of aircraft and ship targets. Here, FMICW is used to satisfy requirements of aircraft detection and FCP is used to satisfy requirements of ship detection for the differences in maneuverability and scatter characteristics of targets and interference background. The design of such a complex waveform for detection of aircraft and ship targets by a HF radar is discussed in detail with different considerations for better performance.

Integrated Design Approach for Solving Complexity of Design Problem

The engineering problems today become more and more complex particularly in the area of new product development. It requires the multi-disciplinary design method to solve complex problems. This paper presents an integrated design system for solving complexity during multi-disciplinary design. Complexity could be solved if the design problems, given by any individuals who are concerned, are structured. The design system uses the multi-viewpoint concept to allow experts to share their information and knowledge in common views. Knowledge modules are used to store semantics from the experts of different disciplines. Then the system agent acts as an internal designer to help support the individuals to translate any semantics provided from one discipline and then propagate to other related disciplines. With these tools, the integrated design system can structure and solve the complexity of design problems.

A COMPLEX OF TWO OPTIMIZATION IDEAS IN OPTICAL AUTOMATIC DESIGN

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Landscape Design of Commercial Housing Based on the Comprehensive Development Model of City Complex——A Case Study on Landscape Design of Chenglong-International

With the acceleration of urbanization, city complex as an intensive urban organization form has gradually grown up in China. By consulting relevant documents of city complex, emergence background and related concepts of city complex were introduced, landscape design of Chenglong-International was analyzed to propose landscape design principles and concepts of city complex under the compound development model, landscape processing techniques of outdoor functional subareas and transitional areas were introduced to provide useful reference for the landscape design of city complex.

Multi-parameter Sensitivity Analysis and Application Research in the Robust Optimization Design for Complex Nonlinear System

The current research of complex nonlinear system robust optimization mainly focuses on the features of design parameters, such as probability density functions, boundary conditions, etc. After parameters study, high-dimensional curve or robust control design is used to find an accurate robust solution. However, there may exist complex interaction between parameters and practical engineering system. With the increase of the number of parameters, it is getting hard to determine high-dimensional curves and robust control methods, thus it＇s difficult to get the robust design solutions. In this paper, a method of global sensitivity analysis based on divided variables in groups is proposed. By making relevant variables in one group and keeping each other independent among sets of variables, global sensitivity analysis is conducted in grouped variables and the importance of parameters is evaluated by calculating the contribution value of each parameter to the total variance of system response. By ranking the importance of input parameters, relatively important parameters are chosen to conduct robust design analysis of the system. By applying this method to the robust optimization design of a real complex nonlinear system-a vehicle occupant restraint system with multi-parameter, good solution is gained and the response variance of the objective function is reduced to 0.01, which indicates that the robustness of the occupant restraint system is improved in a great degree and the method is effective and valuable for the robust design of complex nonlinear system. This research proposes a new method which can be used to obtain solutions for complex nonlinear system robust design.

Response surface methodology-based hybrid robust design optimization for complex product under mixed uncertainties

Minimizing the impact of the mixed uncertainties(i.e.,the aleatory uncertainty and the epistemic uncertainty) for a complex product of compliant mechanism(CPCM) quality improvement signifies a fascinating research topic to enhance the robustness.However, most of the existing works in the CPCM robust design optimization neglect the mixed uncertainties, which might result in an unstable design or even an infeasible design. To solve this issue, a response surface methodology-based hybrid robust design optimization(RSM-based HRDO) approach is proposed to improve the robustness of the quality characteristic for the CPCM via considering the mixed uncertainties in the robust design optimization. A bridge-type amplification mechanism is used to manifest the effectiveness of the proposed approach. The comparison results prove that the proposed approach can not only keep its superiority in the robustness, but also provide a robust scheme for optimizing the design parameters.

A Design Method with Knowledge Modeling for Complex Product Based on Ontology

Innovation design for complex products is a difficult issue in the military manufacturing industry. Ontology may provide a feasible way to rebuild the design process for complex products via sharing and reusing of design knowledge. In this paper, a design method used in the innovation design process of the complex products with knowledge modeling is proposed. Knowledge modeling is realized through ontology construction by combining the cycling evolutional theory of constructing ontology and OWL (Ontology Web Language)-based knowledge representation. As a case study, the satellite is selected as one of the complex products. The application domain of the satellite ontology is analyzed. According to the analysis result, the knowledge structure of satellite ontology is put forward based on OWL. The application of satellite product design shows that the method can effectively organize and reuse the knowledge resources in the innovation design of complex product and help companies to create more competitive products based on the existing knowledge and experience.

Characterization of Feed Properties for Conceptual Process Design Involving Complex Mixtures, Such as Natural Extracts

The number of products used as agro-chemicals, food additives, flavors, aromas, pharmaceuticals and nutraceuticals which are made by fermentation or extraction from plants has increased significantly. Despite this growth, initial predictions for a potential product purification process for these complex mixtures remains entirely experimentally based. The present work represents an initial study to demonstrate the benefits of a systematic approach. For process development of chemically well-studied systems model based process design methods are already available. Therefore the proposed approach focuses on a method for the efficient characterization of the physical properties of the key components. Once this is adequately defined, unit operations and their potential to separate the feed components can be modeled. The current state of research is discussed. Based on this evaluation the most efficient method for conceptual process development has been identified and further developed. The resulting methodology consists of model-based cost accounting accompanied by experimental model-parameter determination. The latter is carried out at in miniaturized laboratory-scale measurement cells for each unit operation using the complete original feed. The model-based modelparameter determination from these experiments is accompanied by a comprehensive error analysis. The experimental plan currently includes the determination of thermodynamic equilibrium conditions in the mixture directly from the raw material mixture. Transport kinetics and fluid dynamic parameters are first estimated from known correlations or preexisting knowledge. Later on these parameters are determined exactly in mini-plant experiments. Furthermore, biological and botanical-based guidelines are developed to identify thermodynamically favored basic operations. Finally, the developed approaches are successfully validated using two plant extracts. Firstly, it could be proven that the botanical pre-selection can reduce the experimental plan significantly. Secondly, it was shown that the experimental equilibrium data of the kinetics and fluid dynamics can have a significant impact on the separation costs. Therefore, detailed rigorous modeling approaches have to be chosen instead of short-cut methods in order to make any valid process development conclusions or to further optimize the system.

A Study on the Evolution of Labor Self-Organizations and the Design of Governmental Mechanism from A Complex Network Perspective

Self-organization theory informs an analysis on the evolution of labor self-organizations (LSOs), but lacks technical analysis on the evolution of their organizational structures. Fortunately, complex network technology offers a new approach to analyzing these structures. Built on an extension of the Barabási-Albert (BA) model, we can simulate the evolution of LSOs by analyzing indicators including the clustering coefficient, degree distribution (DD) and average path length (APL) of workers, thereby demonstrating the evolving patterns of LSOs. Accordingly, governmental mechanism designs based on such patterns may not only stimulate energy growth and functional realization of LSOs, but also reduce the social percussions of abrupt evolutions. A comparative analysis of the evolutionary trajectories of LSOs in China and the U.S. finds that the U.S. government’s mechanism designs for protecting capitalism not only prevented the effective gathering of workers, but also prolonged the history of industrial conflicts. Such mechanism designs also led to the early dispersion and decline of LSOs and hindered the evolution of the working class. In contrast, the Chinese government established a socialist system that allowed workers to become the underlying force of socialist productivity. This design reduced labor strife while accelerating the evolution of workers towards higher stages.

Designed Syntheses and Crystal Structures of Two Cis-cyanide Bridged Trinuclear Complexes

Two cyanide bridged trinuclear compounds [Fe（bpy）2（CN）2]·[Cu（Cyclam）]2（ClO4）4·DMF 1 and [Fe（Phen）2（CN）2]·[Cu（Cyclam）]2（ClO4）4·2CH3CN·4H2O 2 （Bpy = 2,2＇- bipyridine, Phen = 1,10-phenanthroline, Cyclam = 1,4,8,11-tetraaza-cyclotetradecane, and DMF = N,N-dimethylformamide） have been synthesized by using mononuclear [Fe（Phen）2（CN）2]·2H2O and [Fe（bpy）2（CN）2]·3H2O as precursors. These two complexes crystallize in monoclinic space groups P21/c and C2/c, respectively. For 1, a = 25.164（2）, b = 12.0405（11）, c = 20.4433（15） A, β = 91.948（3）°, V = 6190.5（9） A^3, Z = 4, Mr = 1418.90, Dc = 1.522 g/cm^3, F（000） = 2936, μ = 1.161 mm^-1, the final R = 0.0722 and wR = 0.2011 for 10779 observed reflections （I 〉 2σ（I））. For 2, a = 43.5945（0）, b = 11.8447（0）, c = 29.5637（2）A, β = 120.430（11）o, V = 13162.76（9） A^3, Z = 8, Mr = 1518.48, Dc = 1.533 g/cm^3, F（000） = 6288, μ = 1.101 mm^-1, the final R = 0.0711 and wR = 0.1783 for 11262 observed reflections （I 〉 2σ（I））.

Molecular Design and Electronic Structure of Polynuclear Rare Earth Complexes and Clusters

Studies on the electronic structure,molecular design,syntheses of some novel series of tetranuclear rare earth complexes in our laboratory have been reviewed.Spin-unrestricted localized INDO method was used to calculate the electronic structure and the chemical bonding in the typical rare earth cluster Sc[Sc_6Cl_(12)Co]was discussed.

车载信息交互系统复杂性设计管理发展研究

目的梳理车载信息交互系统及其复杂性管理的发展脉络,并提出多元设计策略以指导车载信息交互系统设计。方法首先利用Vosviewer进行文献检索,梳理出目前车载信息交互领域的研究热点;然后通过文献回顾的方式总结传统车载信息交互系统的复杂性演变;最后利用Design X的设计策略,从用户、系统、信息等角度,分析数智时代下的车载信息交互系统存在的任务复杂性及交互复杂性。结论基于Design X的设计策略,从用户群体分析、车载信息优化、智慧交通系统搭建等角度,提出有关管理车载信息交互系统复杂性的多元设计策略,为后续车载信息交互设计提供参考。

山区铁路工程节能设计关键要素识别研究

为从设计源头减少山区铁路工程能源消耗总量、优化能源消费结构,充分发挥铁路绿色发展优势,开展山区铁路工程节能研究,识别山区铁路工程节能设计关键要素非常重要。首先,分析山区铁路工程能源消耗,梳理山区铁路线路、桥梁、隧道等重点工程的节能要点。在此基础上,提取山区铁路工程节能设计要素和能源消耗要素,并根据各要素属性特点,明确其量化指标,建立山区铁路工程−能源消耗要素及指标体系。其次,结合CRITIC-熵权法与C-OWA算子法构建“山区铁路工程−能源消耗”双层复杂网络模型,依次确定各要素节点重要度、节点间影响强度和节点综合重要度,用以识别山区铁路工程节能设计关键要素。最后,以某山区重大铁路工程某标段为例,验证方法模型并识别出该标段影响施工阶段的节能设计关键要素为:隧道作业设备选型、隧道出渣控制、隧道通风方式选择;影响运营阶段的节能设计关键要素为:曲线半径设置、线路纵坡设置、线路坡度设置、节能坡设置、客站供热设计、客站体形设计。经验证,构建的山区铁路工程−能源消耗要素及指标体系符合山区铁路工程特点,“山区铁路工程−能源消耗”复杂网络模型具有良好的适用性,识别出的节能设计关键要素及其优化建议可为山区铁路工程节能设计提供参考。

面向复杂工程问题的算法系列课程教学案例选择与设计方法探讨

案例教学是算法系列课程行之有效的一种教学方式,有效的教学案例是案例教学取得成功的重要标志。针对教学案例选取不具代表性、案例分析不到位等问题,该文提出相应的解决方案。该方案从复杂工程问题与教学案例之间的关系入手,围绕如何解决复杂工程问题组织教学过程,形成“选择案例、分析案例、形成解题思路、撰写算法、编写程序、运行程序、验证案例”的案例教学过程,提出案例选择等7个原则,以及基于枚举法的教学案例分析方法,举例说明论文所提方法的具体实施过程。该文所提原则和方法对其他课程教学案例的选择与分析具有一定的借鉴意义。