无线传感器网络安全路由协议SNEP的分析与仿真实现

以提供可靠保密通信为目标的安全路由协议的分析是无线传感器网络安全基本研究领域之一．阐述了针对无线传感器网络的攻击手段所采取的措施,研究了安全路由协议,重点研究了其中的传感网络加密协议（Sensor Network Encryption Protocol,SNEP）,并进行了仿真实现,最后针对无线传感网络的攻击方式对SNEP的安全性进行了分析．结果证明SNEP协议具有数据机密性、数据认证、防御重放攻击等安全服务．     

Numerical simulations of fatigue crack initiation and propagation based on re-tensile plastic zone generating load criterion for in-plane gusset welded joints

Many accidents are caused by fatigue in welded built-up steel structures, and so it is important to estimate the fatigue lives of such structures quantitatively for safety reasons. By assuming that fatigue cracks cannot grow without an accumulation of alternating tensile/compressional plastic strain, one of the authors identified an improved effective stress intensity factor range ΔK _RPG based on the re-tensile plastic zone generating (RPG) load, which represents the driving force for fatigue cracks, and suggested that ΔK _RPG should be used as the parameter to describe fatigue crack growth behavior. The “FLARP” numerical simulation code in which ΔK _RPG is implemented as the fatigue crack growth parameter, was developed in order to predict fatigue crack initiation and propagation behavior. In this paper, it is demonstrated that FLARP gives accurate estimates for fatigue life by comparing the estimated fatigue crack growth curves and S–N curves with the experimental results for in-plane gusset welded joints, which are used in many welded steel structures. Moreover, the effect of induced bending moment due to the linear misalignment in the out of plane direction on the fatigue strength of in-plane gusset welded joints is investigated through numerical simulations.     

小样本情况下的船舶溢油事故风险评价研究

船舶溢油风险评价是一项复杂的多因素问题,是船舶溢油应急管理的关键环节.作为智能搜索算法的代表理论,BP神经网络被认为是进行不确定风险评价的较好方法之一,然而船舶溢油事故属于小样本事件,统计数据往往难以满足BP神经网络要求的样本容量.针对这一困境,首先提出一种利用B样条最小二乘理论的数据拟合法,显著增加样本数.其次,根据船舶溢油特点建立了基于BP神经网络的船舶溢油风险评价模型.最后以上海港近年发生的10起溢油事故为实例,检验了模型的可行性.     

网络计划技术在船舶修造中的应用

文章介绍网络计划技术方法,并将其应用于船舶修造的生产管理,可以克服横道图的缺点,实现利用计算机在船舶修造生产中的现代化管理。     

重箱堆场地下管网施工

重箱堆场作为集装箱码头后方的存储腹地,对集装箱的储运起着十分重要的作用。文章表明,在重箱堆场施工过程中,对地下管网施工,如何选择有效的施工方法,安排控制好相关工序的衔接,是保证重箱堆场工程有条不紊进行,确保施工进度与质量的重中之重。     

城市轨道交通中压网络供电分区的划分

以主变电所集中供电的中压网络为基础,从建设、运营经济性、过补偿和继电保护设置配合方面,分析供电分区划分应考虑的问题;网络构成及供电分区的划分位置应考虑与运行交路的结合,最大限度地满足车辆的运行,不因网络局部故障造成全线车辆停运.供电分区的划分在满足规范要求电压损失的前提下,尽可能减少供电分区的数量,以使工程具有较好的经济性.提出在满足继电保护要求等的前提下,线路电压损失要求是中压网络供电分区划分从建设和运营经济性考虑的合理结合点.     

工期固定多目标资源优化的方法

资源是指为完成工程任务所需的劳动力、材料、机械设备和资金等的统称。资源优化就是通过改变工作的实施时间,使资源按时间的分布能够符合优化目标。     

Emission rates of intermodal rail/road and road-only transportation in Europe: A comprehensive simulation study

Intermodal rail/road transportation combines advantages of both modes of transport and is often seen as an effective approach for reducing the environmental impact of freight transportation. This is because it is often expected that rail transportation emits less greenhouse gases than road transportation. However, the actual emissions of both modes of transport depend on various factors like vehicle type, traction type, fuel emission factors, payload utilization, slope profile or traffic conditions. Still, comprehensive experimental results for estimating emission rates from heavy and voluminous goods in large-scale transportation systems are hardly available so far. This study describes an intermodal rail/road network model that covers the majority of European countries. Using this network model, we estimate emission rates with a mesoscopic model within and between the considered countries by conducting a large-scale simulation of road-only transports and intermodal transports. We show that there are high variations of emission rates for both road-only transportation and intermodal rail/road transportation over the different transport relations in Europe. We found that intermodal routing is more eco-friendly than road-only routing for more than 90% of the simulated shipments. Again, this value varies strongly among country pairs.     

Morning commute in a single-entry traffic corridor with no late arrivals

This paper analyzes a model of early morning traffic congestion, that is a special case of the model considered in Newell (1988). A fixed number of identical vehicles travel along a single-lane road of constant width from a common origin to a common destination, with LWR flow congestion and Greenshields’ Relation. Vehicles have a common work start time, late arrivals are not permitted, and trip cost is linear in travel time and time early. The paper explores traffic dynamics for the social optimum, in which total trip cost is minimized, and for the user optimum, in which no vehicle’s trip cost can be reduced by altering its departure time. Closed-form solutions for the social optimum and quasi-analytic solutions for the user optimum are presented, along with numerical examples, and it is shown that this model includes the bottleneck model (with no late arrivals) as a limit case where the length of the road shrinks to zero.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.