风险矩阵法在A水泥工厂风险分级的应用初探

本文介绍“风险矩阵法”进行风险分级工作的基本思路，结合水泥厂的生产特点通过危险有害因素辨识，获得危险源分布情况，采用风险矩阵法对风险进行评估，按风险值将风险等级划分为重大风险、较大风险、一般风险和低风险，为水泥生产企业的安全风险分级工作提供参考。     

地表径流速度对城市内涝影响规律

为分析地表径流速度对城市内涝的影响,采用一维地下排水管网与二维城区地形的动态耦合模型,选取大连市某排水区块作为研究区域,设置4种地表径流速度10种设计降雨场景,模拟分析在不同重现期设计降雨及不同地表径流速度下研究区的内涝积水特性。结果表明:随着地表径流速度降低,管道排水压力变小,管道排水达标率最高可提升48.05%,且降雨重现期越短,地表径流流速对管道排水压力的削减效果越明显;地表径流流速对检查井溢流量影响显著,随着地表径流速度降低,检查井溢流量峰值最高可减小2 750 m~3,峰现时间最长可滞后56 min,同时随着降雨重现期增长,地表径流流速对检查井溢流量的削减效果减弱;研究区低、高风险区淹没面积随地表径流速度降低,最高可分别减小1.64万、8.37万m~2,但中风险区淹没面积变化反复。     

一种基于实时几何测距的船桥主动防撞方法

本文提出一种基于实时几何测距的船桥主动防撞方法。该方法对船的改动量甚微,仅需维持多项距离矩阵,通过告警逻辑矩阵进行展示与告警,能起到很好的船桥防撞提示效果。     

水电站大型竖井施工安全风险控制措施研究

竖井是大型水电工程中广泛采用的重要建筑物,但竖井的传统施工方法存在施工程序复杂、人工劳动强度大、施工效率不高等特点,同时还存在较大的安全风险。通过对杨房沟水电站大型竖井施工过程的研究,总结出精细化控制爆破、小溜渣井施工方式,同时也设计了一套用于运输的综合提升系统。采用上述创新方法不仅减少了繁琐的施工程序,降低了安全施工风险,而且大量采用机械化手段进一步提高了施工效率,确保了该工程竖井施工的安全风险可控。相关措施可为类似工程的竖井施工提供较好的借鉴作用。     

辉县部分景区地质灾害危险性评估及防治措施研究

为了给辉县景区减灾防灾提供地质依据,根据实际工程概况,研究了辉县部分景区地质灾害危险性预测评估及防治措施,预测评估了工程建设中、建设后可能引发或加剧地质灾害危险性,建设工程自身可能遭受已存在地质灾害危险性;评估了地质灾害危险性综合分区以及根据地质灾害危险性、防治难度和防治效益,对评估区适宜性作出评价,提出了防治地质灾害的措施和建议。     

Selection of risk response actions with consideration of secondary risks

Secondary risk in project risk management refers to the risk that arises as a direct result of implementing a risk response action (RRA). It is important for project managers (PMs) to consider the effects caused by the secondary risks in the process of RRA selection. The purpose of this paper is to propose an optimization method to address the problem of selecting risk response actions (RRAs) with consideration of secondary risk which is seldom considered in the existing studies. The optimization model aims to minimize the total risk costs with time constraint being placed on the project makespan. By solving the model, an optimal set of RRAs along with the earliest start time for each activity can both be obtained. The results show that secondary risk plays an important role in the process of RRA selection. Project managers should allocate more budget for responding the project risk when the secondary risk is considered, and consider all factors relating to both time and cost so as to select appropriate RRAs to mitigate primary risk and secondary risk.     

基于负荷预测的0.4 kV配网低电压风险评估方法

我国现阶段的配电网网架结构依然十分薄弱,智能化水平低,缺乏先进的检测技术和高效的运维模式。在现阶段低压电气信息不开源的情况下,为解决0.4 kV配网无差别运维效率低的问题,文章分析了适用于低压配网状态评估的评价维度,并基于负荷预测结果提出了低压台区低电压风险评估方法,引入了微增容量所引起的压降比,实现对低电压风险的定期管控。该文对于优化低压配电网运维资源配置、指导低压配网差异化运维模式的建立,以及提高低压配电网运维整治效率具有一定的参考价值。     

Stochastic collocation-based nonlinear analysis of concrete bridges with uncertain parameters

This paper focuses on the stochastic response of concrete bridges considering uncertainty in bearing and abutment stiffness. A multi-span simply supported bridge with concrete girders is selected. A 3D-dimensional model is prepared, and nonlinear response history analyses are performed. For the numerical dynamic simulation, the non-sampling stochastic method based on generalized polynomial chaos (gPC) expansion is utilised. The uncertain parameters include the vertical and shear stiffness of bearings and the lateral stiffness of abutments are presented by the truncated gPC expansions. Furthermore, the system response such as base shear, acceleration, velocity and displacement in different columns is presented by gPC expansion with unknown deterministic coefficients. The stochastic Galerkin projection is employed to calculate a set of deterministic equations. A non-intrusive solution, as a set of collocation points, determines the unknown gPC coefficients of the system response and the results are compared with Monte Carlo simulations. The key advantage of spectral discretization is the combination of the mentioned method with the spatial discretization, e.g. finite element model. This study also emphasises the accuracy in results and time efficiency of the proposed non-sampling method for uncertainty quantification of stochastic systems comparing to sampling procedure (e.g. Monte Carlo simulation).     

Supply chain network design under the risk of uncertain disruptions

Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.