基于产业链演化的物流网络资源配置策略

从基础设施、信息系统、服务功能等角度分析物流网络资源,总结地理环境和商业市场因素对物流基础设施的空间构型的影响,提出从市场角度研究物流资源配置的必要性.分析社会经济系统中经济运行链式结构由企业集群至产业链的发展趋势,从服务范围、服务核心、需求市场、利用效率等层面研究不同经济运行结构条件对物流网络资源影响,从设施、信息和功能等分项角度总结瓶颈问题,提出资源配置对策.     

基于多维帧映射的光网络资源描述算法

通过分析光网络资源在复杂网络资源调度中的特点,提出了波分复用(WDM)网络的一种基于多维帧映射的光网络资源描述算法.该算法的设计旨在高效、准确描述光网络拓扑资源状态信息,为对光网络资源的高效利用与快速响应奠定基础.该算法采用多维的方式描述光网络资源状态信息,采用帧模块分层次、分布式的方式呈现光网络资源状态信息,实现资源的准确发现、快速更新、高效调度.通过示例分析证明,该算法可有效缩短资源发现的响应时间,很大程度地提高资源发现的准确性,有效地提高资源调度的效率.     

Durability based design of FRP jackets for seismic retrofit

Although FRP composites are increasingly being used for the rehabilitation of civil infrastructure, there is still a lack of well documented long-term durability data, and of design methodologies that explicitly consider effects of deterioration over time at a structural level. This paper provides results of an investigation aimed at assessing the effect of deterioration over time, at the materials level, on the effectiveness of FRP jackets used for seismic retrofit. Three different systems are investigated and results of accelerated testing are used to provide predictive equations for long-term performance of the material, which are then used to analyze effectiveness at the level of seismic retrofit through four specific cases. The effect of deterioration is expressed, for ease in comparison, to an increase in the required thickness of the jacket with expected service-life. Results using unexposed values for materials performance are compared to those obtained using the values recommended by ACI-440 procedures, as well as through the use of time-dependent materials degradation models. It is shown that the ACI recommendations for durability may be excessively conservative for the 50-year period considered herein. The use of the proposed predictive methodology for materials durability combined with the analytical tools for design of FRP jacket thickness are shown to not only enable a better assessment of required jacket thickness but can also enable assessment of the dominant mechanism controlling selection of thickness which can change with time of exposure. Results of the accelerated tests are also linked to field exposure results providing a set of correlation factors.     

An extended graphical targeting technique for direct reuse/recycle in concentration and property-based resource conservation networks

Minimum flowrate targeting methods for resource conservation networks (RCNs) have been developed over the last decades. The existing methodologies still have certain drawbacks. Their design insights could be deepened and some steps should be more convenient for the users. A targeting tool called the material surplus composite curve (MSCC), which is an improvement of the surplus diagram for water and hydrogen networks is introduced. The approach is illustrated on several cases selected from the literature. Using this technique, it is possible to determine rigorous flowrate targets for different variants of the RCN problem.     

Synthesis of property-based resource conservation network in palm oil mills with time-varying process disturbance

This article presents a mathematical model for resource conservation in a palm oil milling process via property integration. The focus is given to the clay bath system for kernel/shell separation based on flotation principle. In the present study, the clay bath separator is considered as a semi-batch unit under time-dependent process disturbance. This is different from previous works where it is simplified as a continuous unit. The design problem can be formulated as a nonlinear program based on a superstructure approach, with the objective set to minimize the fresh resource consumption. An illustrative case study is solved to demonstrate the proposed model.     

基于神经网络趋势分析

文章在分析研究了国内外现状的基础上 ,利用神经网络的非线性处理特性 ,提出了通过神经网络预测常见机械零件剩余寿命的方法 ,用实例验证了其有效性     

A generalised guideline for process changes for resource conservation networks

In the past one and a half decades, resource conservation network (RCN) synthesis has been well accepted by both academics and industrial practitioners in enhancing sustainability aspect for the process industry. Various insight-based pinch analysis and mathematical optimisation techniques have been proposed to synthesise optimum RCN. For the former, the developments to date have been focusing on various targeting and design tools, with very little emphasis on the systematic assessment of process changes. The latter involves the modification of process operating conditions (e.g., flowrate, concentration, temperature, etc.), which leads to further reduction of minimum fresh resource flowrates. In this study, the plus-minus principle in heat exchanger network synthesis is extended for use with graphical targeting tool in assessing opportunities for process changes in the RCN of fixed-flowrate problems, aiming to further reduce its minimum fresh resource flowrate. Literature examples are used for illustration.     

基于部分可观察马尔可夫决策过程的受控无线网络系统动态资源分配

研究了受控无线网络的动态资源分配。针对传统无线通信传输模型的局限性随着无线通信系统架构的发展日益凸显的问题,提出了一种引入反馈控制策略的受控无线网络模型。该模型结合部分可观察马尔可夫决策过程(POMDP),将用户接收功率与数据传输误码率作为反馈观测对象,对通信小区内基站天线开启数与用户接入数进行动态资源最优匹配。仿真结果表明,这种方法能够有效提升系统传输能效性与可靠性,降低传输误码率,改善系统资源动态匹配控制性能。     

A hybrid genetic based optimization procedure for aircraft conceptual analysis

The problem to define a methodology for the analysis of aircraft performances, in the phase of conceptual design, is addressed. The proposed approach is based on a numerical optimization procedure where a scalar objective function, the take-off weight, is minimized. Deterministic and stochastic approaches as well as hybridizations between these two search techniques are considered. More precisely, we consider two-stage strategies where the optimum localization is performed by a genetic algorithm, while a gradient-based method is used to terminate the optimization process. Also, another type of hybridization strategy is investigated where a partially converged gradient-based method is incorporated in the genetic algorithm as a new operator. A detailed discussion is made and various different solutions are critically compared. The proposed methodology is consistent and capable of giving fundamental information to the designer for further investigating towards the directions identified by the procedure. A basic example is described, and the use of the methodology to establish the effects of different geometrical and technological parameters is discussed.     

基于共振解调与神经网络的滚动轴承故障智能诊断

介绍了一种基于共振解调与神经网络技术的滚动轴承故障诊断方法。对采集系统所拾取的滚动轴承振动信号进行共振解调处理，依据故障包络频谱中必然存在谐波谱线的规律，在共振解调后的包络信号中提取所需的轴承故障谱线特征信息，并将其作为神经网络输入，利用神经网络进行轴承各种故障状态的识别，实现滚动轴承故障的智能诊断。实验表明，该方法能准确而有效地识别出滚动轴承的不同磨损状态，诊断便捷。     

一种加权误差最小化的深度信念网络优化技术

传统的深度信念网络模型缺乏并行有效的算法来确定网络层数以及隐藏层神经元的数目,实验时大多依据经验来选取,这样做不仅使得模型训练困难,且范化能力差,影响实验结果.针对此问题,通过比较重构误差和验证集错误分类率的乘积(加权误差)大小来选取网络层数,网络层数确定后,再根据重构误差使用渐增法或二分法来选择合适的隐层神经元数目,以使整个模型达到最优.实验结果表明,用上述方法确定模型网络层数及隐藏层神经元数目,能有效提高模型分类或预测的精度.     

Flash X-ray radiography source based on plasma-filled rod pinch diode

Results of experiments on the formation of a high-power focused electron beam in a plasma-filled rod pinch diode driven by a high-current MIG generator (maximum voltage, 1.3 MV; impedance, 0.65 Ω) are presented. The proposed diode with a sharpened 1.5-mm-thick tungsten rod anode provides an X-ray source for flash radiography with a size of ∼1 mm, which is capable of producing a radiation dose of 2.4 rad per pulse at a distance of 1 m. The results of comparative experiments with and without plasma injection into the diode are presented.     

A network flow algorithm for optimal resource allocation

This paper introduces a network flow method for manpower scheduling and resource allocation. The network formulation of the problem permits the development of an algorithm that determines the minimal flow of resources through the network. The method presented here corresponds to the Simplex method, for in both methods the value of the objective function is optimized while the capacity limitations are preserved. The procedure proposed here, however, uses a more economical problem representation and is computationally more efficient. The efficacy of the minimal flow algorithm and its use is illustrated for a production system but the applicability of the procedure is sufficiently broad for it to work in other problem situations just as well.     

High-resolution two-dimensional angle measurement technique based on fringe analysis

A novel angle-measurement technique based on fringe analysis for phase-measuring profilometry is proposed. A two-dimensional (2-D) angle between two mirror surfaces is determined by least-squares fitting of a plane to the 2-D distribution of the phase difference introduced by the 2-D tilt angle. To evaluate the performance of the proposed technique, numerical simulations that use the Fourier-transform technique and the phase-shift technique for fringe analysis were performed, and the results are compared. A 2-D angle-measurement interferometer based on a Mirau interference microscope was developed that demonstrated the validity of the proposed principle. It is shown by simulation and experiment that the proposed 2-D angle-measurement technique can achieve both a wide measurement range and a high angular resolution simultaneously.     

Emission constrained power system planning: a pinch analysis based study of Indian electricity sector

In the light of rising electricity demands and a need to curb carbon dioxide emissions, this article investigates the problem of power system planning with emission targeting. A pinch analysis based approach is utilised here. The key aspect of this study is investigating the parameters that decide the priority of one type of power plant over another. For this, a quantity called prioritised cost, a trade off between cost incurred and emission from a new power plant is identified. In addition to cost and emission factor of a power plant, a third parameter, the present state of the system, also plays a significant role in deciding a power plant’s prioritised cost. The analysis done proves that new power plants can be added to the system in the order of their prioritised cost. This methodology is applied to Indian power sector as a case study. Two different problems, involving minimisation of investment and annualised cost, are considered. It is observed that renewables are slightly more favoured when the objective is to minimise overall cost and not just the capital investment. In both cases, the energy mix is still dominated by coal-based power generation. The share of renewables was seen to increase with more stringent emission targets when the objective was to minimise overall cost.     

Robust procedure for fringe analysis

A robust procedure for analyzing fringe patterns obtained from speckle interferometric techniques is proposed. The fringes generally are observed only in a region S of a rectangular lattice L. We give a method for computing (from S) the region R, where the unwrapped phase is to be computed; this computation is done by use of a morphological filter (in particular, a closing filter). We then use a fast-unwrapping algorithm to compute the phase: a preconditioned conjugate-gradient algorithm that uses the discrete Fourier transform.     

An efficient time-windowing procedure for scheduling projects under multiple resource constraints

This paper describes an efficient procedure for resource-constrained project scheduling problems. It starts with a simulated annealing technique to find a base schedule, and then improves the result by a time-windowing process. Every time-window, which is part of the base schedule, is a basis for a small subproject with two sets of specific constraints. Associated subprojects with time-windows are scheduled to optimality and based on their results the base schedule is updated. The overlapping feature of time-windows makes the displacement of an activity possible within the range of the entire project. The process of creating time-windows, scheduling their associated subprojects to optimality and improving the base schedule is controlled by a feed-back based mechanism that realises a trade-off between computational effort and the improvement made. The computational results indicate that the procedure is promising and yields better solutions than several heuristic algorithms presented in the literature.     

Development trend forecasting for coherent light generator technology based on patent citation network analysis

A forecasting methodology for technology development trends is proposed based on a two-level network model consisting of knowledge-transfer among patents and patent subclasses, with the aim to confront the increasing complex challenge in technology investment and management. More specifically, the patents of the “coherent light generators” classification, granted from 1976 to 2014 by examiners of the United States Patent and Trademark Office, are collected and with which the first-level citation network is constructed first. Then, a new approach to assess patent importance from the perspective of topological structure is provided and the second-level citation network, which consists of patent subclasses, is produced with the evaluation results. Moreover, three assessment indices of the subclass citation network are abstracted as impact parameters for technology development trends. Finally, two typical time series models, the Bass and ARIMA model, are utilized and compared for development trend forecasting. Based on the results of evolution prediction and network analysis, the highlighted patent subclasses with more development potential are identified, and the correlation between technology development opportunity and topological structure of the patent citation network is discussed.     

Fault detection,classification, and location for active distribution network based on neural network and phase angle analysis

The improved radial basis function (RBF) method utilizes an orthogonal regression matrix to produce an artificial neural network structure based on regularized least square. The phase angle and amplitude signal of fault voltage and current are extracted based on frequency domain analysis. The proposed method adopts the fault signal for fault diagnosis synchronously. The IEEE 13-bus active distribution network (ADN) simulation model is set up in Matlab. Test results demonstrate that accuracy of the fault diagnosis can reach 98.07% and the response time of the fault classification method is less than 0.04s. The wavelet neural network (WNN) model is developed to extract the maximum decomposition level and time series behavior. The WNN method can resist noise effects and improve the fault classification accuracy by 4.3%. The effect of fault type and fault resistance on the fault location method is researched. The fault simulation result shows that the proposed method can locate a fault precisely and synchronously. The improved RBF method can diagnose the fault section, classify the fault type and locate a fault accurately in ADN. The research is significant to maintain system stability against realistic fault and network restore.