船体板格极限强度数值计算影响因素及敏感分析

船体板格极限强度的有限元计算方法应用广泛,但其计算方法具有一定的不稳定性,计算结果受多种因素的影响.本文针对船体板格有限元计算方法的不稳定性进行研究,通过将有限元计算结果与其他学者的研究成果进行对比,验证本文所采用的有限元方法的可靠性,然后针对板格材料、初始缺陷、网格密度、边界条件等几种因素的敏感性进行具体研究,发现理想应力应变关系会使得结果偏于危险.网格形状和网格密度对于结果均有影响,边界条件对于有限元结果有影响,最大误差在7.2%,并且模型3会使得结果偏于危险.初始缺陷是一敏感因素,最大误差在20%,因此需要根据实际缺陷选取合适的屈曲模态和比例因子.     

基于相关性模型的舰船系统测试性建模与分析

本文提出一种基于相关性模型的舰船系统级产品的测试性建模与分析方法.该方法通过建立产品任务模型、相关性图示模型等,利用一阶相关性列矢量法求解产品的相关性数学模型,进而建立产品诊断树和进行测试性预计,并为优化产品诊断策略提供建议.同时,根据舰用燃气轮机滑油系统组成和任务特征,建立其典型任务模型并进行精简,并在此基础上进行测试性建模、诊断树建立、测试性预计以及诊断策略优化等工作,为舰船系统级产品的测试性建模、分析和诊断策略研究提供新思路和手段.     

营运船舶航行性能和海洋环境监测平台开发验证

EEDI是衡量船舶能效水平的重要指标.由于试验条件限制,目前主要还是依靠模型试验结果对交船测试进行修正换算得到.上海船舶运输科学研究所自主研发了航行性能和海洋环境监测平台,可对营运船舶开展长期跟踪监测,实时收集船舶营运阶段的航行环境和性能参数,通过自动识别航行状态,划分海区、海况和船舶载况等因素对于船舶功率与航速的影响,可获得营运船舶实际EEDI指标,提高EEDI实船验证结果的准确性.监测平台在某万箱级集装箱船进行相关验证,并已展开长期监测.     

Simulating ad-hoc demand-responsive transportation: a comparison of three approaches

Transport models are used to evaluate new infrastructure and public transport services, varied levels of demand, and new ideas for demand management. Exploring these proposals virtually is easier than implementation and testing in situ. However, existing models are based around traditional forms of transportation. As part of a feature analysis using a case study approach, three different simulation packages (a simple custom-developed package, traffic microsimulation, and agent-based simulation) are used to develop and demonstrate simulations of demand-responsive transportation (DRT) and analyze the advantages and disadvantages of each simulation approach for evaluating DRT. While the simulations display some relational replication (meaning they produce similar relational patterns with respect to certain variables), they do not show distributional replication (that is, the value of the results is not statistically similar), meaning that under- or over-estimation of predicted travel could occur. Recommendations for the application of each modeling approach are made.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem

This paper proposes simple and direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem. It is only necessary to account for random variables independent of link flows by performing a simple transformation of the perceived link travel time with a normal distribution. At every iteration of a Monte-Carlo simulation procedure, the values of the random variables are sampled based on their probability distributions, and then a regular deterministic user equilibrium assignment is carried out to produce link flows. The link flows produced at each iteration of the Monte-Carlo simulation are averaged to yield the final flow pattern. Two test networks demonstrate that the proposed algorithms and the traditional algorithm (the Method of Successive Averages) produce similar results and that the proposed algorithms can be extended to the computation of the case in which the random error term depends on measured travel time.     

Impact of regional population density on walking behavior

Land use can influence walking (measured by the number of steps) and so the health of people. This paper presents the result of empirical research on the impact of regional population densities (inhabitants per inhabitable area) on the number of steps (all steps, both outdoors and indoors). With data collected from almost 11,000 respondents in 148 Japanese regions, we estimate polynomial regression models, the total number of steps being the dependent variable and densities being the main independent variable. Regional population density significantly affects the number of steps after controlling for individual and household attributes. The estimated population density that maximizes the number of steps is around 11,000?persons/km². Increasing densities, up to levels of around 11,000?inhabitants/km², could increase walking and consequently the health of inhabitants. The population density elasticity of the number of steps is 0.046–0.049 in a simple log linear regression model without a peak.     

基于AIGA-WLSSVM的埋地管道腐蚀速率预测方法

为了降低埋地管道腐蚀影响因素之间的复杂相关性,提高腐蚀预测精度,文中提出一种基于自适应免疫遗传算法-加权最小二乘支持向量机(AIGA-WLSSVM)的埋地管道腐蚀速率预测建模方法,并采用AIGA优化模型参数,进一步提高模型的学习能力和稳定性。最后通过实例分析验证了AIGA-WLSSVM建模方法在埋地管道腐蚀速率预测中的可行性和有效性,为埋地管道的检修与更换提供参考。     

典型地铁站台射频天线电磁暴露安全评估

为有效评估典型地铁站台射频天线对乘客电磁暴露的安全性,设计地铁站台无线通信系统吸顶天线和乘客人体模型,利用基于有限元的电磁仿真软件,构建吸顶天线辐射下的地铁站台乘客候车电磁环境模型,研究候车乘客的公众电磁暴露问题。结果表明:天线分别工作在900和2 440 MHz时,人体组织的平均比吸收率最大值分别为4.441×10-7和1.165×10^-6W·kg^-1,电场强度最大值分别为0.139和0.148V·m^-1,平均比吸收率在人体组织内的衰减均大于电场强度的衰减;2 440MHz时的射频电磁能量在颅内的穿透能力小于900MHz时;所有计算值均低于国际非电离辐射委员会制定的公众电磁暴露限值,说明地铁站台射频天线对乘客的电磁暴露不会构成健康威胁。     

基于改进云模型的地铁站行人拥挤辨识方法

为降低城市地铁站内行人拥挤识别时多指标和多等级带来的不确定性和模糊性,采用改进云模型构建行人拥挤状态辨识模型。基于AHP-熵权法标定指标权重和行人拥挤状态等级,以标定的指标权重和各指标等级阈值作为输入,计算云数字特征值,采用正向正态云发生器,建立模板云和待识别云模型,计算两者之间的隶属度,根据最大隶属度原则辨识车站内各服务设施的行人拥挤状态,最后输出各服务设施的拥挤等级辨识结果。以宁波市鼓楼站为实证对象,对辨识结果进行实证分析。结果表明:采用四级行人拥挤状态划分方法合理可行。