Heuristic estimation of container stacking and reshuffling operations under the containership delay factor and mega-ship challenge

This paper addresses a highly researched area, the reshuffling problem in ports, using a new paradigm-modified containership service order in light of credit risk assessment. Container stacking and reshuffling operations can cause ship delays and additional risk. In deep-sea terminals, outbound containers are tightly stacked according to the retrieval sequence. Due to lack of space, terminals stack containers in multiple tiers. This means any delay in the arrival of a ship can impose extra handlings and reshuffling of containers delaying future cargo handling. This paper addresses the reshuffling problem with a concept similar to the credit scoring and rating of creditworthiness used in the banking industry. By utilizing this comparison to the banking credit risk concept, a heuristic estimation model is proposed that illustrates the side effects of unscheduled modifications in containership service order. Further, the mega-ship trend amplifies the reshuffling debate. Probability of delay, reshuffles given delay, and call size at delay are introduced as the three-point risk metrics of the model. Numerical simulations illustrate the functionality to develop terminal stacking strategies as well as emphasize the mega-ship phenomenon and its side effects on terminals (i.e. yard operation deadlock).     

基于多监测及预警要素的地铁工程安全风险量化评估方法

通过对地铁基坑隧道工程各监测项目实测数据及其预警指标、预警数量等多项因素进行挖掘和综合分析，研究建立一种基于多因素权重矩阵分析法的工程安全风险状态量化评估方法，克服当前监测预警多、风险评判定性为主的工程安全风险状态局限性，填补工程安全风险动态及定量化评估的空白，提升工程预警及安全风险状态判别的合理性、及时性和智能化。将该方法应用于某工程中，有效并及时地指导地铁基坑隧道工程施工中安全风险评估与控制、预警响应及处置工作，提高地铁工程的安全风险预控效果及管理水平。     

Probabilistic analysis of the release of liquefied natural gas (LNG) tenders due to freight-train derailments

Liquefied natural gas (LNG) has emerged as a possible alternative fuel for freight railroads in the United States, due to the availability of cheap domestic natural gas and continued pursuit of environmental and energy sustainability. A safety concern regarding the deployment of LNG-powered trains is the risk of breaching the LNG tender car (a special type of hazardous materials car that stores fuel for adjacent locomotives) in a train accident. When a train is derailed, an LNG tender car might be derailed or damaged, causing a release and possible fire. This paper describes the first study that focuses on modeling the probability of an LNG tender car release incident due to a freight train derailment on a mainline. The model accounts for a number of factors such as FRA track class, method of operation, annual traffic density level, train length, the point of derailment, accident speed, the position(s) of the LNG tender(s) in a train, and LNG tender car design. The model can be applied to any specified route or network with LNG-fueled trains. The implementation of the model can be undertaken by the railroad industry to develop proactive risk management solutions when using LNG as an alternative railroad fuel.     

Real-time crash prediction for expressway weaving segments

Weaving segments are potential recurrent bottlenecks which affect the efficiency and safety of expressways during peak hours. Meanwhile, they are one of the most complicated segments, since on- and off-ramp traffic merges, diverges and weaves in the limited space. One effective way to improve the safety of weaving segments is to study crash likelihood using real-time crash data with the objective of, identifying hazardous conditions and reducing the risk of crashes by Intelligent Transportation Systems (ITS) traffic control. This study presents a multilevel Bayesian logistic regression model for crashes at expressway weaving segments using crash, geometric, Microwave Vehicle Detection System (MVDS) and weather data. The results show that the mainline speed at the beginning of the weaving segments, the speed difference between the beginning and the end of weaving segment, logarithm of volume have significant impacts on the crash risk of the following 5–10 min for weaving segments. The configuration is also an important factor. Weaving segment, in which there is no need for on- or off-ramp traffic to change lane, is with high crash risk because it has more traffic interactions and higher speed differences between weaving and non-weaving traffic. Meanwhile, maximum length, which measures the distance at which weaving turbulence no longer has impact, is found to be positively related to the crash risk at the 95% confidence interval. In addition to traffic and geometric factors, wet pavement surface condition significantly increases the crash ratio by 77%. The proposed model along with ITS, e.g., ramp metering, Dynamic Message Sign (DMS), and high friction surface treatment can be used to enhance the safety of weaving segments in real-time.     

信息安全风险评估方法研究

提出信息安全风险评估的概念，论述当前在信息安全风险评估领域中应用的主要方法以及今后的发展方向。     

基于FTA方法降低涡轮增压器失效风险

故障树分析是一种有效的系统可靠性分析方法,已经广泛应用在机械行业的各个领域。通过故障树分析可以找出涡轮增压器过载的失效原因。对该机型的技术改进证实,所采取的弥补措施能有效降低涡轮增压器的失效风险。     

工程项目管理中的合同管理探讨

企业只有重视合同的重要性,做好合同管理,才能有效降低工程风险,维护企业的利益,增加利润.结合实践经验,提出应通过合同管理提高企业的核心竞争力,在建设项目中推行项目法人负责制、招标投标制、建设监理制改革,坚持从中国国情出发管理项目.以强化合同管理为突破口、以法治理念为基础的合同管理是项目管理的灵魂.     

基于K均值聚类与Bayesian分类器的车型识别方法

不同车型经过感应线圈时,线圈检测器采集过来信号变化的波形不同,同类车型对应采集的波形中如波峰极大值、峰值位置、平均值、波峰数等特征值都具有相似性。根据感应线圈采集所得信号的特点,讨论了一种基于K均值聚类与Bayesian分类器的车型识别方法。学习训练中,通过K均值聚类算法把不同波形的特征值归类,再采用Bayesian分类器算法去获得分类器。实验结果表明,该方法具有较高的车型识别精度。     

道/隧上下交叉段隧道支护分析和加固探讨

研究目的:本文主要针对郴宁公路万华岩右幅隧道(在建)浅埋段受地表水泥厂石灰石长胶带输送廊道交叉跨越施工影响,研究分析在初期支护条件下隧道掌子面发生早期坍塌的原因,后期状况下通过钢架支护试验类比和支撑近似分析两种方法得到冒顶最终发生的原因;从经济技术和风险方面对后期隧道加固方案进行探讨;最后针对隐藏风险,提出合理避险,减少损失。研究结论:对于上下近临(接)施工,必须遵照有关建设程序报批;同期施工双方在本文情况下,应遵循先下后上、先重后轻的施工顺序;对初期支护状态下的濒临冒顶的全～强风化围岩、大跨浅埋隧道应优先采用地表注浆方案,以确保人员安全和方案最终实施。     

北京市公路特殊路段防撞护栏碰撞试验条件研究

现行公路规范规定护栏最高防撞能量为520 kJ,不能满足水资源保护区、水库、跨越干线铁路等特殊危险路段的安全防护需要,通过对北京市各高速公路交通流状况调查分析,对特殊路段护栏碰撞能量和碰撞试验条件进行研究,提出适合北京地区特殊防护路段护栏的碰撞试验条件为33 t重大货车以65 km/h速度、20°角碰撞护栏,碰撞能量为630 kJ,为新型高防护等级护栏的研究开发奠定基础。