A primary influence vertex approach to identify driving factors in complex integrated agri-industrial systems – an example from sugarcane supply and processing systems

Integrated agri-industrial systems (IAISs), such as sugarcane supply and processing systems, are complex systems and hence generally difficult to understand and manage. The large number factors in IAISs coupled with the complex interrelationships among the factors make it challenging to identify the points of intervention for improving their overall performance. Several approaches, such as the network theory and the Theory of Constraints have been used to identify important factors in systems with variations in success. This paper demonstrates a primary influence vertex approach for identifying and ranking the factors that drive the performance of IAISs. The approach is based on comprehensive causal network analyses and was tested in four relatively diverse large-scale sugarcane milling operations in South Africa. Results from the analyses were found to be consistent with the literature and external knowledge of the milling areas as at the time of the study. It is concluded that the approach can proffer a sound basis from which deeper rooted problems in systems can be identified on an ongoing basis. It is, however, recommended that the approach should be systematically compared with other relevant methods that are used to analyse complex systems.     

Analysis of retailers’ coalition stability for supply chain based on LCS and stable set

To attain the general form of stable coalition structure, this paper addressed the problem of retailers’ coalition stability in a two-stage supply chain consisting of one supplier and multiple retailers. A profit gain function was established via introducing market gain coefficient and coalition cost coefficient for different coalition structures. Based on the function, the profit of each retailer in all kinds of coalition structures was analysed, and the general feature of a stable coalition structure was attained by the largest consistent set method and the stable set method. Furthermore, some insights were obtained. For example, stable coalition structures are equidistributed or approximate equidistributed; with supplier’s cost increasing, the size of the retailers’ coalition increases. Finally, the above conclusions are verified by numerical simulation. The results of this paper provide a reference for retailers’ coalition in a supply chain, such as automobile or Information Technology supply chain.     

New Failure Mode and Effects Analysis: An Evidential Downscaling Method

Failure mode and effects analysis (FMEA) is an engineering and management technique, which is widely used to define, identify, and eliminate known or potential failures, problems, errors, and risk from the design, process, service, and so on. In a typical FMEA, the risk evaluation is determined by using the risk priority number (RPN), which is obtained by multiplying the scores of the occurrence, severity, and detection. However, because of the uncertainty in FMEA, the traditional RPN has been criticized because of several shortcomings. In this paper, an evidential downscaling method for risk evaluation in FMEA is proposed. In FMEA model, we utilize evidential reasoning approach to express the assessment from different experts. Multi‐expert assessments are transformed to a crisp value with weighted average method. Then, Euclidean distance from multi‐scale is applied to construct the basic belief assignments in Dempster–Shafer evidence theory application. According to the proposed method, the number of ratings is decreased from 10 to 3, and the frame of discernment is decreased from 2¹⁰ to 2³, which greatly decreases the computational complexity. Dempster's combination rule is utilized to aggregate the assessment of risk factors. We illustrate a numerical example and use the proposed method to deal with the risk priority evaluation in FMEA. The results and comparison show that the proposed method is more flexible and reasonable for real applications. Copyright © 2014 John Wiley & Sons, Ltd.     

圆柱绕流气动噪声数值分析

为了快速预测刚性圆柱绕流的气动噪声,研究了一种将离散涡方法(DVM)和涡声理论结合起来计算低马赫数、高雷诺数流场气动噪声的方法。首先用Oseen粘性涡模型改进了离散涡方法并模拟了圆柱绕流,分析结果与实际情况相符。根据流场计算的结果,应用涡声理论进一步计算了远场的声压。测点的总声压级与实验值及其他数值计算结果都比较吻合。最后绘制了声场的指向性特性曲线,表明圆柱绕流声场明显的偶极子特性。     

基于粗糙集理论的老年人网页感性设计研究

目的为了满足老年用户的感性需求,提高其使用网页时的情感体验。方法基于感性工学原理,在感性意象调查的基础上,运用粗糙集理论,构建知识表达系统,然后通过属性约简和重要度计算得出对感性评价贡献较大的设计要素,并通过规则的提取,得出相关设计原则。结果在老年人网页设计中,影响老年用户感性意象"简洁的—繁琐的"的最大的设计要素为网页布局,其次为标题文字的大小、内文文字的大小以及超链接样式。结论老年人网页设计应该注重界面的简洁,要对网页的布局、超链接及文字的大小重点考虑。研究结论可为老年人网页界面设计提供参考依据。     

基于图着色理论的异构车联网时隙分配方案

针对异构车联网系统车辆较多导致时隙分配困难的问题,提出了一种基于图着色理论的时隙分配方案。该方案以考虑两跳内节点的图为模型,通过图着色的方法分配时隙,有效降低了隐藏终端带来的丢包;另外给出了一种高效实用的时隙重用分配算法。该算法根据度定义权值以确定车辆分配时隙数目,保证了公平性,提高了时隙重用,进而提高了消息发送的可靠性,同时也适用于网络拓扑多变的车联网场景。仿真结果表明,在车辆数为200、时隙数为100时,与传统时隙分配方法相比,该方案的车辆平均收包率获得大幅提升。此外,随着时隙重用的增加,车辆间干扰增强,从而导致平均收包率降低。研究还发现,增加车辆发射功率时,由于接收端信干噪比先增加后趋于不变,所以平均收包率也先增加后趋于不变。     

金属材料断裂准则研究进展

介绍了金属材料断裂准则的研究进展,包括传统强度理论、现代断裂力学理论及常用断裂准则,并对各种准则的特点进行了简要分析。     

Al/Cu复合材料制备中理论与工艺研究进展

Al/Cu复合材料具有质轻、导电良好和成本低等优点,成为了近年来研究的热点。介绍了Al/Cu复合材料的主要界面复合理论,并着重阐述了近年来对主流理论的研究。综述了国内外关于Al/Cu复合材料的制备工艺和数值模拟的研究进展,指出了各工艺的优缺点,并对制备工艺的改进方向、未来数值模拟的研究方向进行了展望。     

蜂窝层合板结构的隔声特性研究

通过理论建模,着重分析了蜂窝层合板的结构参数对隔声性能的影响。考虑简谐声波垂直入射,基于波传递理论和传递矩阵,引入蜂窝特性阻抗建立蜂窝传声理论模型。通过对理论模型的精度分析,研究了蜂窝层合板结构的芯层厚度、面板厚度、等效杨氏模量等参数对层合板传声特性的影响。由数值分析可知,与传统的理论模型相比,该理论模型相对较简洁,而且精度能满足一般工程要求;其次,芯层厚度、面板厚度以及面板密度对蜂窝层合板结构的传声损失影响较大。