Analyzing the factors affecting environmental risks of projects using a hybrid approach of DEMATEL‐ANP,artificial neural network: A case study

The increasing growth of the economy in each country necessitates a great amount of investment in infrastructure. The belief that projects involve various uncertainties, such as technical skills, management quality, and the like, indicates that most projects fail to achieve their aims, interests, costs, as well as their timeframes and space requirements. As the environment can pose significant uncertainty to any project, environmental risks should be deeply studied by project management departments. This study intends to analyze as a case the environmental risk management system within a consulting firm. From this analysis, each aspect of a project's environmental risk management is ranked using a fuzzy analytical network process (ANP), a neural network algorithm, and a decision‐making trial and evaluation laboratory (DEMATEL) methodology. From the organizational aspect, budget risk is the most significant. From the technical aspect, the risk of regulations is the most important one. Finally, the risk of project failure from poor communication is another identified main risk in this research. By studying high‐ranking items in this hierarchy, it can be understood that these criteria exist in different aspects; therefore, all aspects of the risk should be taken into account to cover and assess risk. A neural network algorithm for validating and reassessment of ranking is employed. Results of this application showed that, based on Spearman's rank correlation method, two different approaches resulted in similar rankings. Finally, some practical implications for responding to the most highly ranked risks are proposed.     

Spatial Convergence in Major Dissolved Ion Concentrations and Implications of Headwater Mining for Downstream Water Quality

Spatial patterns in major dissolved solute concentrations were examined to better understand impact of surface coal mining in headwaters on downstream water chemistry. Sixty sites were sampled seasonally from 2012 to 2014 in an eastern Kentucky watershed. Watershed areas (WA) ranged from 1.6 to 400.5 km² and were mostly forested (58%–95%), but some drained as much as 31% surface mining. Measures of total dissolved solutes and most component ions were positively correlated with mining. Analytes showed strong convergent spatial patterns with high variability in headwaters (<15 km² WA) that stabilized downstream (WA > 75 km²), indicating hydrologic mixing primarily controls downstream values. Mean headwater solute concentrations were a good predictor of downstream values, with % differences ranging from 0.55% (Na⁺) to 28.78% (Mg²⁺). In a mined scenario where all headwaters had impacts, downstream solute concentrations roughly doubled. Alternatively, if mining impacts to headwaters were minimized, downstream solute concentrations better approximated the 300 μS/cm conductivity criterion deemed protective of aquatic life. Temporal variability also had convergent spatial patterns and mined streams were less variable due to unnaturally stable hydrology. The highly conserved nature of dissolved solutes from mining activities and lack of viable treatment options suggest forested, unmined watersheds would provide dilution that would be protective of downstream aquatic life.     

汶川地震十年国际研究的合作与主题态势

为全面认识国际汶川地震研究的合作与主题态势,利用科睿唯安Web of Science数据库采集了3 158篇汶川地震研究论文,使用科学计量学方法对国际汶川地震研究的国家/地区、机构和作者合作网络进行了分析。采用关键词词频和共词分析的方法,对国际汶川地震研究热点、主题类团和新兴主题进行了研究。研究结果表明:关于汶川地震的研究从2008—2009年开始显著增长,之后保持平稳;我国产出量第一,且在汶川地震研究合作中处于国家/地区的核心,与美国、日本和英格兰合作密切;机构层面上,中国科学院和中国地震局位于核心位置;徐锡伟和黄润秋是汶川地震研究中的代表作者;国际汶川地震热点主题涉及了滑坡、泥石流、芦山地震、创伤后应激障碍、地理信息系统、遥感等方面,并围绕高频关键词形成了“地震对人心理的影响（例如PTSD）”、“地理信息系统和遥感技术在汶川地震中应用”、“汶川地震引起的地质灾害和数值分析”以及“龙门山断裂带与汶川和芦山地震”4大主题聚类,其中“地震对人心理的影响（例如PTSD）”和“龙门山断裂带与汶川和芦山地震”是目前活跃的主题聚类。     

基于贝叶斯网络的城市地下燃气管网动态风险分析

为研究城市燃气管网风险的动态性,针对传统风险分析方法的局限性,提出基于贝叶斯网络的燃气管网动态风险分析方法。构建燃气管网失效蝴蝶结模型并将其转化为贝叶斯网络模型;在事故发生状态下更新事件失效概率,识别出关键因素;根据异常事件数据和贝叶斯理论,对基本事件失效概率进行实时动态改变;随之更新管网失效及各后果发生的概率,从而实现管网的动态风险分析。研究结果表明:该方法克服了传统风险分析方法的不足,可动态反映燃气管网失效和事故后果发生概率随时间变化的特征,能够为城市地下燃气管网的风险分析与事故预防提供参考。     

燃气管线相邻地下空间安全监测方法及其应用研究

城市燃气管线泄漏极易导致火灾爆炸等重大安全事故,严重威胁城市安全。通过监测预警技术,快速准确地发现泄漏,防止可燃气体聚集,是保障燃气管线安全运行的重要手段。提出了一种燃气管线相邻地下空间安全监测预警方法,构建了风险识别、预测预警、分析推演和决策支持一体化安全监测系统,并应用于合肥市2.5 km燃气管线及其相邻空间高风险区域。结果表明,提出的燃气管线相邻地下空间安全监测方法可用于燃气管线泄漏监测预警,以减少或避免燃气泄漏引发的火灾爆炸事故。     

斜拉索跨越管桥安全状况评定方法研究

为有效地了解油气长输管道中斜拉索跨越管桥的安全状况,保障管道正常运行,建立一种斜拉索跨越管桥安全状况评定方法。在工程实际的基础上,借鉴《公路桥梁技术状况评定标准》斜拉桥技术状况评定思想,针对跨越油气管道自身特点,构建斜拉索跨越管桥安全状况评定指标体系。结合网络层次分析法和熵权法,计算指标的组合权重。根据指标评分,求得斜拉索管桥的安全状况分值,确定安全状况评定等级。结果表明:管桥系指标对斜拉索跨越管桥安全状况的影响程度最大,应作为安全保护工作的重点;实例分析中,斜拉索跨越管桥安全状况评定等级为3级,其中锚固墩安全状况较差,管道管理方应结合现场检测及安全状况评定结果,及时采取有效的治理措施。     

区域应急响应方案柔性生成方法研究

针对目前应急响应方案存在无法适应区域特征的问题,从柔性的角度出发,提出具有区域针对性的应急响应方案生成方法。通过分析区域应急需求,总结方案中的柔性要素;采用层次网络的方式对应急响应方案进行建模,提出要素和要素之间关系的确定方法,并分共性和个性2部分表示应急响应方案柔性生成框架;模拟地震灾害情景,实现柔性应急响应方案生成方法的案例验证,结果表明:该方法可以反映区域特点,高效有序并有针对性地完成有关突发事件的应对工作。     

基于IPSO-BP的受损钢结构改造施工安全预警评估研究

为研究受损钢结构改造施工安全预警状况,建立受损情况下钢结构改造施工安全预警指标体系,并针对BP神经网络算法易陷入局部最优的问题,提出了用改进粒子群算法（IPSO）对BP神经网络权重及阈值进行调整的IPSO-BP安全预警评估模型。通过分析某单层重钢厂房受损现状,针对其结构损伤情况和已构建的安全控制指标体系进行数值模拟分析。研究结果表明:与传统的BP模型相比,IPSO-BP模型具有更好的预测能力,构建的安全预警指标体系及预警模型可以很好地对受损钢结构改造施工过程安全状况进行综合评估,对受损钢结构改造施工安全控制具有一定的参考价值。     

基于改进PSO-BPNN的输油管道内腐蚀速率研究

为解决输油管道易腐蚀,且腐蚀程度难以测量的问题,提出使用改进的粒子群算法（PSO）优化误差反向传播神经网络（BPNN）对输油管道内腐蚀速率进行预测。改进的PSO算法提升了自身搜索到全局最优的能力,可为BPNN提供最优初始权值和阈值,从而有效避免BPNN易陷入局部最优的问题发生。以某条输油管线为例,分别运用标准的BPNN模型、PSO-BPNN以及改进的PSO-BPNN对该管线内腐蚀速率进行预测。结果表明:基于改进的PSO-BPNN的预测结果平均相对误差为5.57%,预测精度较BPNN和PSO-BPNN有明显提升。使用改进的PSO-BPNN预测输油管道的腐蚀速率可为管道的检测维修提供可靠的理论和技术支撑。     

Resilience-based optimal firefighting to prevent domino effects in process plants

Domino effects triggered by fire can cause extremely severe damages to the chemical and process plants. In the need of a more effective prevention of fire domino effects, the present study focuses on firefighting which has received less attention compared to passive and active fire protection systems. Considering both the vulnerability and recoverability phases during fire domino effects, we have introduced a methodology for optimal identification of firefighting strategies so as to increase the resiliency of process plants in dealing with fire escalation scenarios. The area above the resilience curve (AARC), which is equal to the accumulation of loss of resilience over time, was considered as the metric to identify the optimal firefighting strategies. In other words, the strategy leading to the lowest AARC can be selected as the optimal strategy from a resiliency perspective.