炼油厂酮苯装置空冷器腐蚀原因分析

炼厂酮苯装置空冷器因空冷管束腐蚀穿孔被迫停工检修，经取样分析和现场调查，得出结论：溶解氧含量偏高，设备本身存在震动，无盐水质量不稳定及空冷管束选材不当是造成空冷器管束腐蚀穿孔的主要原因，提出有效大的防腐措施。     

中厚板轧机工作辊失效分析及对策

介绍了济钢中厚板厂使用国外高镍铬和高铬工作辊的主要失效形式 ,并对该工作辊的断裂和裂纹产生原因进行了分析 ,同时针对所存在的问题提出了对策和具体改进措施。     

漏电保护器投运难题的解决方案

分析剩余电流动作保护装置的常见故障,编制常见故障排查口袋书,采取简单易懂、能按图索骥的快速查找方法,破解剩余电流动作保护装置投运难题.     

The vulnerability of structures to unforeseen events

A structure is vulnerable to an unforeseen event if it is not sufficiently robust. One insight into the lack of robustness is gained through the vulnerability of a structure to disproportionate collapse. In this paper, the importance of assessing the vulnerability of a structure to unforeseen events is highlighted and the nature of unforeseen events examined. A theory of structural vulnerability which examines the form of the structure to determine the most vulnerable sequence of failure events is briefly described. The potential for damage to propagate through a structure is examined through a new measure of hazard potential and vertical pushover analysis. An analysis of an example structure shows that such an approach is able to capture the weaknesses in a structure either due to form or external actions.     

基于因果的自适应双阈值镜头边界检测算法

将因果检测法与双阈值法相结合,提出了一种基于因果的自适应双阈值镜头边界检测算法.首先,利用相邻两帧之间的帧间差异值对突变和渐变进行预检;然后,加入渐变检测容忍度、边缘和非相邻帧间差异值等信息,对初检结果进行复检,排除闪光灯、剧烈物体运动、淡入、淡出以及溶解等造成的误检和漏检,以提高整体检测效果.实验结果表明,与传统的双阈值镜头检测方法相比,本方法可获得更好的检测性能.     

特殊构造砖烟囱定向爆破拆除

介绍了定向控制爆破技术拆除一座烟囱、水塔的结合体,拟爆结构物地坪以上27 m处设置钢筋混凝土结构水箱,致使重心高于一般烟囱,其外壁采用ф12 mm钢筋网箍和60 mm厚混凝土进行加固。周边环境复杂,距高压配电房仅1.4 m,为避免地坪处+0.5 m烟道口对定向的影响,将爆破切口位置提高到+3.0 m处;为减小触地振动、防止倾倒过程中出现后座,采用梯形切口,爆破切口长度取其周长62%,爆破切口高度取1.4 m。为克服烟囱外壁加固层和圆拱墙体钻凿深度不准确的影响,同排相邻炮孔采用一深、一浅的布置方式,其炮眼深度差值2~3 cm,装药结构应用正、反向起爆综合技术。采用开挖减震沟、设置缓冲带控制爆破振动等措施,爆破效果理想,保证了邻近建筑物及设施安全。     

基于AEM法的爆破拆除倒塌过程的数值模拟

利用应用单元法(AEM法),以含填充墙的某多层框架结构定向爆破拆除为例,进行倒塌过程的数值模拟。结果表明:在框架结构爆破切口形成后,结构由于重力作用逐渐沿横向偏转,并在横向最外侧的一排柱上形成活动铰,产生翻转倒塌,模拟结果与实际倒塌结果基本相符。在倒塌的过程中,结构爆破切口的横向很快进入大变形倒塌,同时引起横向隔墙的平面失去稳定而倒塌。落地的倒塌碎块,在纵向产生150kN左右的峰值冲击力,在横向产生30~50kN的峰值冲击力。基于仿真结果,可以定量设置防护措施,避免安全隐患。     

Learning Causes: Psychological Explanations of Causal Explanation1

I argue that psychologists interested in human causal judgment should understand and adopt a representation of causal mechanisms by directed graphs that encode conditional independence (screening off) relations. I illustrate the benefits of that representation, now widely used in computer science and increasingly in statistics, by (i) showing that a dispute in psychology between mechanist and associationist psychological theories of causation rests on a false and confused dichotomy; (ii) showing that a recent, much-cited experiment, purporting to show that human subjects, incorrectly let large causes overshadow small causes, misrepresents the most likely, and warranted, causal explanation available to the subjects, in the light of which their responses were normative; (iii) showing how a recent psychological theory (due to P. Cheng) of human judgment of causal power can be considerably generalized: and (iv) suggesting a range of possible experiments comparing human and computer abilities to extract causal information from associations.     

Morphological Models for the Collapse of Area Features in Digital Map Generalization

Collapse is an essential operation for the manipulation of area features in digital data generalization. This operation can be categorized into two types: complete collapse and partial collapse. The former is composed of another two types: area-to-point and area-to-line collapse. In this paper, a set of algebraic models built upon the operators in mathematical morphology is described for the area-to-line collapse and partial collapse operations. For the area-to-line collapse operation, a modified skeleton algorithm is presented. For the partial collapse operation, a procedure is designed which consists of a set of operations, i.e., the skeletonization, separation of areal and linear parts, simplification of areas and an overlay operation. These models are tested using real map data sets.     

Fuzzy logic based assignable cause diagnosis using control chart patterns

Control chart patterns, besides determining the presence of assignable causes, also provide hints on the nature of assignable cause(s) present. Relating the patterns exhibited on the control chart to assignable causes is an ambiguous and vague task especially when multiple patterns co-exist. In this work, a rule based fuzzy inference system is developed for control chart to prioritize the control chart causes based on the accumulated evidence. When a process goes out of control, search for assignable causes can be assisted by the priorities assigned to the causes. For an in-control process, developing patterns can be tracked and preventive action can be taken to prevent the process from going out of control.