基于新型光纤的传输技术探讨

随着互联网的高速发展，引发了网络流量、电信骨干网流量急速增长，使得网络容量的提升迫在眉睫。目前，100G 系统已经商用，超100G系统能够更有效地解决流量和网络带宽持续增长带来的压力，本文主要介绍新型单模光纤的特性以及探讨基于新型单模光纤的传输技术。     

Experimental and numerical analysis of the influence of cable tray arrangements on the resulting mass loss rate and fire spreading

In the context of industrial buildings and power plants, electrical installations and cable trays represent a main fuel load and a potential initial fire source due to possible short circuits or comparable malfunction. Furthermore, a fire can spread from one tray to additional trays mounted above and/or horizontally on one tray. Because of the high significance of cable fires, several research projects have been carried out, investigating the fire behaviour of cables from small‐scale tests, eg, the cone calorimeter, up to large‐scale tests, analysing complete cable tray constructions. The goal of the work presented in this paper is the extension of the knowledge regarding the influence of geometrical parameters like the packing density and tray distance on the burning behaviour and fire spread of cable tray installations. The results are considered, together with test results from the literature, to quantify the main physical parameters describing the burning behaviour. In a next step, the general applicability of these parameters as input data for the parametrization of the source term of numerical simulations is shown. The test results show that the burning behaviour and the fire spreading highly depend on the cable arrangement of the cables on the cable tray, in combination with other boundary conditions. By applying the results as input for a fire simulation, the mass loss rate is considered appropriately.     

Design structure matrix (DSM) method application to issue of modeling and analyzing the fault tree of a wind energy asset

The perpetual energy production of a wind farm could be accomplished (under proper weather conditions) if no failures occurred. But even the best possible design, manufacturing, and maintenance of a system cannot eliminate the failure possibility. In order to understand and minimize the system failures, the most crucial components of the wind turbines, which are prone to failures, should be identified. Moreover, it is essential to determine and classify the criticality of the system failures according to the impact of these failure events on wind turbine safety. The present study is processing the failure data from a wind farm and uses the Fault Tree Analysis as a baseline for applying the Design Structure Matrix technique to reveal the failure and risk interactions between wind turbine subsystems. Based on the analysis performed and by introducing new importance measures, the “readiness to fail” of a subsystem in conjunction with the “failure riskiness” can determine the “failure criticality.” The value of the failure criticality can define the frame within which interventions could be done. The arising interventions could be applied either to the whole system or could be focused in specified pairs of wind turbine subsystems. In conclusion, the method analyzed in the present research can be effectively applied by the wind turbine manufacturers and the wind farm operators as an operation framework, which can lead to a limited (as possible) design‐out maintenance cost, failures' minimization, and safety maximization for the whole wind turbine system.     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

大直径平底负压容器优化设计

通过对大直径平底负压容器平底板的设计计算,平底板计算厚度很厚。通过分析,提出了对平底板采取加强措施,从而减薄平底板计算厚度的方法。该容器在实际生产过程中性能可靠、稳定,对类似设备设计具有借鉴意义。     

DP980+Z烘烤硬化值与退火温度的关系

摘要：为了研究退火温度对镀锌DP980+Z烘烤硬化值的影响，退火温度控制在760～820℃之间，系统分析退火温度对烘烤硬化值的影响。通过准静态拉伸试验机测量烘烤硬化值及抗拉强度，采用lepara试剂对组织中的马氏体进行着色，利用金相显微镜及图像处理软件测量马氏体的体积分数；采用扫描电镜观察DP980+Z的双相组织特点，并且将组织图片通过CAD转化成有限元图进行网格划分，建立代表性体积单元（RVE），通过有限元分析铁素体、马氏体强度对烘烤硬化值的影响。在同样的变形量情况下，DP980+Z的原始屈服强度越高，烘烤硬化值越高。     

空间红外大口径折射式低温镜头设计与验证

针对目标探测类空间红外相机大范围成像、高灵敏度探测、高精度定位等应用需求,文中提出采用像方远心光路和低温光学技术结合的解决方案,设计了物方视场角8°×8°、入瞳口径265 mm、工作温度200 K的像方远心折射式光学系统。镜头最大口径280 mm,采用多级分散的弹性支撑设计,解决大口径低温透镜装框、透镜组件支撑和镜头整体安装各环节的热应力卸载问题。在保证高刚度和低漏热的情况下,使低温下透镜的热应力对镜头能量集中度的影响降低到可接受范围内。镜头完成装调及室温下像质确认后,进行了力学振动试验,并将其制冷到200 K水平测试像质,测试结果表明,镜头能量集中度达到轴上75%,边缘视场72%。     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

Does decision quality (always) increase with the size of information samples? Some vicissitudes in applying the law of large numbers.

Adaptive decision making requires that contingencies between decision options and their relative assets be assessed accurately and quickly. The present research addresses the challenging notion that contingencies may be more visible from small than from large samples of observations. An algorithmic account for such a seemingly paradoxical effect is offered within a satisficing-choice framework. Accordingly, a choice is only made when the sample contingency describing the relative evaluation of the 2 options exceeds a critical threshold. Small samples, because of the high dispersion of their sampling distribution, facilitate above-threshold contingencies. Across a broad range of parameters, the resulting small-sample advantage in terms of hits is stronger than their disadvantage in false alarms. Computer simulations and experiments support the model predictions. The relative advantage of small samples is most apparent when information loss is low, when the threshold is high relative to the ecological contingency, and when the sampling process is self-truncated. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

一种大尺度二维直线度精密测量的新方法

本文提出了一种远距离、大范围二维直线度测量的新方法．该方法采用特殊设计的十字线准直激光器及线阵CCD，通过特殊的光学系统结构设计，能在0-20m距离内连续测量，直线度范围可达70mm，精度优于0．1mm，实际测量结果表明，该方法可适应野外作业环境。