A regression and beam theory based approach for fatigue assessment of containership structures including bending and torsion contributions

Container shipping has been expanding dramatically during the last decade. Due to their special structural characteristics, such as the wide breadth and large hatch openings, horizontal bending and torsion play an important role to the fatigue safety of containerships. In this study the fatigue contributions from vertical bending, horizontal bending and torsion are investigated using full-scale measurements of strain records on two containerships. Further, these contributions are compared to results from direct calculations where a nonlinear 3D panel method is used to compute wave loads in time domain. It is concluded that both bending and torsion have significant impacts on the fatigue assessment of containerships. The stresses caused by these loads could be correctly computed by full-ship finite element analysis. However, this requires large computational effort, since for fatigue assessment purposes the FE analysis needs to be carried out for all encountered sea states and operational conditions with sufficient time steps for each condition. In this paper, a new procedure is proposed to run the structure finite element analysis under only one sea condition for only a few time steps. Then, these results are used to obtain a relationship between wave loads and structural stresses through a linear regression analysis. This relation can be further used to compute stresses for arbitrary sea states and operational conditions using the computed wave loads (bending and torsion moments) as input. Based on this proposed method for structure stress analysis, an efficient procedure is formulated and found to be in very good agreement with the full-ship finite element analysis. In addition it is several orders of magnitude more time efficient for fatigue assessment of containership structures.     

Autonomous cars: The tension between occupant experience and intersection capacity

Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks.In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation.On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda.This paper concludes with a brief discussion of research needs to advance this line of inquiry.     

Predicting the adoption of connected autonomous vehicles: A new approach based on the theory of diffusion of innovations

On the grounds that individuals heavily rely on the information that they receive from their peers when evaluating adoption of a radical innovation, this paper proposes a new approach to forecast long-term adoption of connected autonomous vehicles (CAVs). The concept of resistance is employed to explain why individuals typically tend to defer the adoption of an innovation. We assume that there exists a social network among individuals through which they communicate based on certain frequencies. In addition, individuals can be subject to media advertisement based on certain frequencies. An individual’s perceptions are dynamic and change over time as the individual is exposed to advertisement and communicates with satisfied and dissatisfied adopters. We also explicitly allow willingness-to-pay (WTP) to change as a result of peer-to-peer communication. An individual decides to adopt when (i) there is a need for a new vehicles; (ii) his/her WTP is greater than CAV price; and (iii) his/her overall impression about CAVs reaches a cutoff value. Applicability of the proposed approach is shown using a survey of employees of the University of Memphis. Our results show that the automobile fleet will be near homogenous in about 2050 only if CAV prices decrease at an annual rate of 15% or 20%. We find that a 6-month pre-introduction marketing campaign may have no significant impact on adoption trend. Marketing is shown to ignite CAV diffusion but its effect is capped. CAV market share will be close to 100% only if all adopters are satisfied with their purchases; therefore, the probability that an individual becomes a satisfied adopter plays an important role in the trend of adoption. The effect of the latter probability is more pronounced as time goes by and is also more prominent when CAV price reduces at greater rates. Some caveats may be inserted when considering the study results as the findings are subject to sample bias and data limitations.     

运梁河特大桥转体梁不平衡重称重试验分析

哈大客专运粮河特大桥跨既有线连续梁采用平转法施工,为确保转体顺利进行,转体前进行了T构不平衡重试验分析,文中介绍了一种转体构件不平衡重的测试方法和应用过程。结果表明,方法有效可行,可供同类工程借鉴。     

STX1(2)型驮背多功能运输车超偏载检测标准

分析了STX₁₍₂)型驮背多功能运输车对既有超偏载检测方法和标准的适应性,提出了该车的超偏载检测方案,明确了公路货车或半挂车超偏载的检测方法及评判标准。     

浅谈新常态下海员的现状与可持续发展

海员是我国从海洋大国向海洋强国转变的中流砥柱,他们为发展国民经济、保证航运安全和扩大对外开放做出了巨大的贡献。但是从当前形势来分析,我国对海员的教育培训力度和关怀力度却远远跟不上海洋经济的发展。文中主要指出我国海员目前所面临的发展现状,结合国外海员的发展模式及可吸取的经验,对我国海员的可持续发展做出较为全面的策略探讨。     

地下工程注浆技术研究新进展

注浆是土木、水利和矿山等工程建设中重要的防渗和加固技术。文章基于国内外注浆技术研究文献,总结了水泥等颗粒性浆液的“渗滤效应”及“黏度时空变异性”等理论研究成果,论述了非水反应高聚物、CW环氧树脂和微生物菌液等注浆新材料的应用现状及发展前景,介绍了细观力学数值模拟研究的突破性进展,可为地下工程注浆技术发展提供借鉴和启发作用。     

桥墩及桩基形式对墩底平转施工转盘设计的影响

以新建福厦(福州—厦门)高速铁路17500 t转体刚构为背景,采用实体有限元方法分析了不同桥墩类型及桩基布置对墩底平转转体中转盘受力的影响,并对桥墩及桩基进行了优化。结果表明:实体墩对上转盘受力最有利,其次是空心墩,最不利的是双薄壁墩;增加墩底实体段能够有效降低空心墩、双薄壁墩上转盘的主拉应力;随着墩底实体段高度的增加,主拉应力降低的幅度逐渐变小;球铰正下方有桩基时对下转盘底部受力更加有利;距离球铰中心越远,桩基受力越小,适当增加中桩桩径,可使各桩基应力状态更加均衡。     

格拉斯磁环匀强磁场分析

以毕奥-萨伐尔定律为基础,建立亥姆霍兹线圈以及格拉斯磁环中心磁场分布模型,并计算了它们内部的轴向磁感应强度分布,绘出了空间分布图,分析了轴向磁感应强度与x、y坐标的关系,分析结果得到了亥姆霍兹线圈和格拉斯磁环内部匀强磁场分布区域,通过比较得到格拉斯磁环内部的匀强磁场区域比亥姆霍兹线圈内部的匀强磁场分布区域更大的结论。     

Locating emergency vehicles with an approximate queuing model and a meta-heuristic solution approach

In this paper, the location of emergency service (ES) vehicles is studied on fully connected networks. Queuing theory is utilized to obtain the performance metrics of the system. An approximate queuing model the (AQM) is proposed. For the AQM, different service rate formulations are constructed. These formulations are tested with a simulation study for different approximation levels. A mathematical model is proposed to minimize the mean response time of ES systems based on AQM. In the model, multiple vehicles are allowed at a single location. The objective function of the model has no closed form expression. A genetic algorithm is constructed to solve the model. With the help of the genetic algorithm, the effect of assigning multiple vehicles on the mean response time is reported.