Effect of strain rate on the dynamic compressive mechanical behaviors of rock material subjected to high temperatures

Strain rate is not only an important measure to characterize the deformation property, but also an important parameter to analyze the dynamic mechanical properties of rock materials. In this paper, by using the SHPB test system improved with high temperature device, the dynamic compressive tests of sandstone at seven temperatures in the range of room temperature to 1000 °C and five impact velocities in the range of 11.0–15.0 m/s were conducted. Investigations were carried out on the influences of strain rate on dynamic compressive mechanical behaviors of sandstone. The results of the study indicate that the enhancement effects of strain rates on dynamic compressive strength, peak strain, energy absorption ratio of sandstone under high temperatures still exist. However, the increase ratios of dynamic compressive strength, peak strain, and energy absorption ratio of rock under high temperature compared to room temperature have no obvious strain rate effects. The temperatures at which the strain rates affect dynamic compressive strength and peak strain most, are 800, and 1000 °C, respectively. The temperatures at which the strain rates affect dynamic compressive strength and peak strain weakest, are 1000 °C, and room temperature, respectively. At 200 and 800 °C, the strain rate effect on energy absorption ratio are most significant, while at 1000 °C, it is weakest. There are no obvious strain rate effects on elastic modulus and increase ratio of elastic modulus under high temperatures. According to test results, the relationship formula of strain rate with high temperature and impact load was derived by internalizing fitting parameters. Compared with the strain rate effect at room temperature condition, essential differences have occurred in the strain rate effect of rock material under the influence of high temperature.     

Effects of apparent image velocity and complexity on the dynamic visual field using a high-speed train driving simulator

Train driving is a highly visual task. The visual capabilities of the train driver affects driving safety and driving performance. Understanding the effects of train speed and background image complexity on the visual behavior of the high-speed train driver is essential for optimizing performance and safety. This study investigated the role of the apparent image velocity and complexity on the dynamic visual field of drivers. Participants in a repeated-measures experiment drove a train at nine different speeds in a state-of-the-art high-speed train simulator. Eye movement analysis indicated that the effect of image velocity on the dynamic visual field of high-speed train driver was significant while image complexity had no effect on it. The fixation range was increasingly concentrated on the middle of the track as the speed increased, meanwhile there was a logarithmic decline in fixation range for areas surrounding the track. The extent of the visual search field decreased gradually, both vertically and horizontally, as the speed of train increased, and the rate of decrease was more rapid in the vertical direction. A model is proposed that predicts the extent of this tunnel vision phenomenon as a function of the train speed.Relevance to industryThis finding can be used as a basis for the design of high-speed railway system and as a foundation for improving the operational procedures of high-speed train driver for safety.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

无源光网络标准发展及关键技术研究

无源光网络(Passive Optical Network,PON)作为当今接入网的主要技术解决方案,具有带宽使用效率高、传输距离远、抗干扰能力强等特点.通过研究PON技术的发展动态,本文首先归纳了各种PON技术的产生背景和应用特点,整理出各技术间的连接关系及主要标准;其次介绍了PON技术的帧结构,并对带宽、波长、传输模式等PON技术的主要参数进行了汇总;然后将国内外研究热点进行划分,围绕媒体访问控制协议、帧结构、动态带宽分配算法、节能机制等关键技术,阐述了其研究现状及在PON中的重要作用;最后对PON技术的发展趋势进行了展望.     

高氧化态（Ⅱ─Ⅳ）三核金属簇合物构型的人工神经网络判别方法

本文运用一典型的人工神经网络模型─“反向传播”模型，对高氧化态（Ⅱ─Ⅳ）三核金属簇合物的构型分布进行了分析，得到了较好的分类、预报结果为化合物结构分析提供了新的工具。     

冲裁模CAD／CAM结构库之原型法

本文首先给出了一种新的2.5D 实体表示法,然后在此基础上提出了“原型”的概念。原型法的思想运用在结构库的管理中主要体现在它将模具结构与构成这种结构的零件之间的强联系变成弱联系,结构库面向的对象是一个具有整体性和可运算性的结构原型。这样的原型结构库基本上达到了通用性与开放性的要求。     

台北101层国际金融中心之结构施工技术与其设计考量概述

本文旨在简要说明目前正在施工中之超高层大楼—台北国际金融中心之结构系统、钢结构工程、钢筋混凝土工程基础与深开挖工程等特殊施工技术,并佐以相关之设计考量与施工规划概要,以供工程界做参考。     

Distribution of properties from sampling inhomogeneous materials by line transects

A theory related to the statistics of the structure and properties of inhomogeneous materials has been proposed, dealing with the distribution of properties from sampling of inhomogeneous structures by line transects. It is demonstrated that the empirical cumulative distribution functions of the intercepts from the microstructural constituents and their variances are important fingerprints of the inhomogeneous structures.Simulated sampling of the images of the microstructure by line transects has been proposed as a powerful method for characterization the distribution of properties of inhomogeneous structures. One of the advantages of the method based on the expected values of the order statistics of the intercepts is that the probability bounds of the property are determined without prior knowledge of the functional relationship between the property and the intercepts from the structural constituents.The concept intercept variance has an important application in determining the minimum transect length that stabilizes the variation of the intercept at a low value. Additionally, the concept ‘intercept variance’ can be used for topological optimization of the microstructure regarding the risk of intercepting a large amount of the weaker constituent. Equations regarding the variance of the intercepted fraction characterizing transect lengths with a specified distribution have also been derived.     

DCS在50MW供热机组上的应用

介绍I/A’S系统在巨化热电厂八号50MW供热机组上应用实例,并从DCS系统的整体设计到实现的功能、控制效果等多方面进行了分折,总结了调试和运行经验。     

Motion and structure interpretation of an optical switch

This paper focuses on tracking, reconstruction and motion estimation of a well-defined MEMS optical switch from a microscopic view. For out-of-view reconstruction, a homography capable of transforming feature points and feature lines between a microscopic image and a CAD model of the switch is implemented. The homography between two sequential microscopic images is decomposed and factorized for motion estimation. Optical flow has also been explored to provide rough estimations of rotation centre and angle. The paper also illustrates motion parameter optimization principles to deal with uncertainty inherent in micro world. After non-linear optimization, estimation accuracy for rotation angle and rotation centre can reach 0.06° and pixel level, respectively.