城市燃气管网的地震紧急处置系统研究

燃气管网的地震破坏有时会导致火灾、爆炸等严重的次生灾害。城市中的燃气管网系统若能具备地震紧急处置功能,在地震来临时及时采取自动关闭燃气供应阀门等紧急处置措施,可以避免或减少此类次生灾害的发生。介绍了普遍用于燃气管网日常调度管理的SCADA系统的组成与工作原理,探讨了在SCADA系统中加入地震紧急处置功能的可行性,并基于ArcGIS地理软件,通过VBA二次开发编制了燃气管网的地震紧急处置模拟程序,为燃气管网地震紧急处置系统的实现提供了一定依据。     

基于遗传算法的生命线工程网络抗震优化设计

进行网络抗震可靠性分析的目的,不仅在于定量评价生命线工程网络系统的抗震性能,更重要的是利用这种分析工具指导网络抗震性能的优化设计。以无向边权网络系统为分析对象,分别以管网造价和系统抗震可靠度作为优化目标和约束条件,建立网络系统拓扑优化模型,利用递推分解算法作为网络系统抗震可靠性分析工具,并引入系统单元的灵敏度分析,采用遗传算法求解网络系统的拓扑优化问题,从而发展了一类工程网络抗震优化设计方法。实例分析结果表明,网络系统拓扑结构与系统可靠度之间有显著的正相关关系。     

深水平台施工过程自然风险定量评估

在分析现有风险理论的基础上,结合海洋施工实际,提出了一种对海洋施工自然风险进行定量评估的模型。根据目标系统各风险事件与影响因素之间存在高度非线性复杂映射的特点,提出了利用BP神经网络拟合方法,对主要风险事件发生概率进行量化的模型。针对传统的梯度下降优化算法收敛速度慢的特点,采用可避免计算Hesse矩阵的Levenberg-Marquardt算法来训练神经网络。这一模型可以模拟专家评价,并准确地按照专家的评定法则进行估算,具有一定的通用性。     

基于河网水系变化的水灾危险性评价——以永定河流域京津段为例

城市化过程中不合理的土地利用导致河道填塞、河网缩减现象普遍，城市水灾增加。基于灾害系统思想，构建了基于河网水系变化的水灾危险性评价体系，并以永定河京津段为例进行了实证分析。结果表明：（1）近40年来研究区水系结构简单化趋势明显，河道长度减少了20．5％，条数减少了36．4％，水系调蓄能力下降，在同样的致灾强度下水灾危险性加大；（2）在假设暴雨重现期为50年的条件下，经济密度差异决定了水灾潜在危险区的空间格局，居民用地将成为水灾重度危险区；平原段水灾重度危险区占5．7％，中度危险区占33．1％，滨海段重度危险区占13．9％，中度危险区占26．8％。研究结果可为区域综合减灾、水灾预报提供依据。     

基于神经网络方法的城市空气质量日报技术

运用神经网络方法,将城市空气质量状况与大气污染物对空气质量的损害程度相关联,采用了"基于大气污染损害率的API法"评价概念,模拟发布长春市空气质量日报,同时公布次要污染物,并与API法进行同时段比对实验与综合分析。     

基于网络组织视角的粮食产业化模式与优化路径

在全球粮食安全状况严峻以及中国人多地少的形势下,探讨粮食的产业化发展具有重要意义。从网络组织视角出发,梳理了中国粮食产业化模式并提出优化路径。研究表明：粮食产业化发展是一个网络化的成长过程。基于网络主体控制与参与网络的能力、融资形式以及立足或服务的空间尺度,可以将粮食产业化模式划分为“国家调控跨国公司组织模式”“地方主导龙头企业带动模式”“政府主导社会多元主体参与模式”和“市场主导私营企业推动模式”这四类主要模式,分别对应介于市场组织与等级制组织之间的全球—区域—本地网络组织,并以跨国公司、本地龙头企业、产业化联合体、产业园区、产业集群等产业化组织形式呈现。进一步建议从提升网络主体开始,通过优化网络结构、强化网络载体、完善网络治理来指导粮食产业化的高质量发展。     

基于神经网络的喀斯特石漠化预警分析模型研究——以广西都安为例

阐述了人工神经网络的基本工作原理,分析BP算法在神经网络中的应用,并具体介绍了BP算法过程。在此基础上,以都安石漠化预警分析为例,提出了基于神经网络的石漠化预警模型的结构。人工神经网络模型实现了石漠化预警分析,确定石漠化危险性指数,并把分析的结果以专题图的形式来表现,从而验证石漠化预警分析模型的可靠性和可行性。     

汶川地震在江苏的强震动记录及地震影响场

2008年5月12日四川汶川发生M8.0大地震,江苏数字强震动台网固定观测台站、宿迁和溧阳断层观测存放台阵共获取该次地震有效强震动事件45个,计134条加速度记录。本文介绍了这些强震动记录分析处理的基本情况及其时域与频域的一些特点;编写SICalculate谱烈度计算程序和D2InterP二维插值程序,输入所获取的汶川地震26组实测强震动记录数据,得到该次地震在江苏地区的峰值加速度与谱烈度的等值线图,并就区域内地震影响场特征进行了初步研究。     

A transportation network assessment tool for hazardous material cargo routing: Weighing exposure health risks,proximity to vulnerable areas,delay costs and trucking expenses

The inherent risks associated with accidental releases of hazardous materials during transport have drawn attention and concerns in the recent decades. The aim of this study is to propose a tool for evaluation and comparison of the transportation networks which can be used to assess the routing options between origins and destinations of the cargos for their suitability for transporting hazardous material cargos by tanker trucks and to identify routes which provide lower accidental release risks, lower public exposure risks, and offer economical benefits. Each route segment of transportation networks were evaluated using specific criteria which included health risk and cost of delay in case of an accidental release of materials, trucking cost and proximity to vulnerable areas. Since, the health impact of hazardous materials differ depending on the characteristics of the material being transported as well as release quantities and atmospheric conditions; this paper aimed in providing a tool that can be used to estimate the impact radius (for health risks) after accidental release of hazardous materials by taking into account different atmospheric conditions based on the meteorological data and solar elevation angle. The Gaussian air dispersion model paired with ArcGIS using Python programming were employed to estimate the health risk impact zones by considering the meteorological data, and accordingly to analyze road segments for cost impacts (delay and trucking costs), and the proximity to vulnerable areas. The route assessment tool was demonstrated with a case study. The results of this study can efficiently aid decision makers for transportation of hazardous materials.     

Bibliometric analysis of simulated driving research from 1997 to 2016

Objective: The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

Methods: The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

Results: A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

Conclusions: This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.