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.     

基于信息熵—集对分析的煤矿隐患排查治理风险评估模型

以煤矿安全隐患排查治理风险为研究对象，分析隐患排查闭环管理全过程，并基于此建立了隐患排查治理能力纵向评估指标体系，融合熵值法和集对分析理论，建立了煤矿安全隐患排查治理风险纵向评估模型，为企业更好地了解自身隐患排查治理能力及变化发展趋势提供参考，最后进行了实例分析。     

非平稳条件下基于贝叶斯网络的内涝风险评估和管理方法

受非平稳条件因素(如气候变化、城市化)的影响,近几年内涝灾害频发。以Z市某地块为研究区域,借助地理信息系统(ArcGIS)和暴雨雨洪管理模型(SWMM)实现研究区排水管网的水动力模拟。在不同降雨情境下,比较分析现状系统及不同改造方案下的系统溢流量等信息,计算内涝风险指数。采用贝叶斯网络分析工具(Bayes Server)对引发内涝风险的主要因素进行推理、识别和分析,进而构建内涝风险评估模型。该模型便于决策者根据设计需求,结合各因素的不确定性范围和发生概率值,综合选取最适合的改造措施,优化市政排水防涝规划,为市政基础设施建设提供了依据。     

Economic effects of regulating the seismic strengthening of older buildings

The marked increase in the awareness of earthquake risk following the Canterbury earthquakes in New Zealand offered a unique opportunity to investigate the economic effect of disaster-mitigation regulations on the commercial building stock. A difference-in-differences (DD) framework was used to determine whether earthquake risk has been capitalized into the property prices of buildings constructed prior to 1976, as a response to the national policy requiring assessment and strengthening (or demolition) of the existing earthquake-prone building stock. A negative externality is found in the policy announcement on affected (pre-1970s) office and retail buildings which caused office buildings to suffer a 12.5% stigma discount. However, retail properties were less impacted suffering a 2.3% stigma loss. The value of the commercial building stock has been affected by the policy. These findings provide policy-makers with timely evidence as to the economic effects of New Zealand’s earthquake-prone buildings policy. Facing losses in property value and financial responsibility for retrofitting their assets, building owners will be looking for a workable set of regulatory and non-regulatory incentives to encourage disaster risk management and protect the built environment.     

改进Elman神经网络在短期热负荷预测中的应用

热电厂的短期热负荷预测在城市集中供暖中起着至关重要的作用,直接影响热电厂的经济效益和热能利用率。电厂的短期热负荷一般采用神经网络预测模型进行预测,而BP神经网络应用最为广泛。Elman神经网络算法在BP神经网络基础上加入了承接层,作为一步延时算子,实现记忆能力,使系统具备适应时变能力,增强系统全局稳定性。但Elman神经网络算法模型的构造依然需要大量样本的支撑,而且输入层的变量多,导致预测时间依然很长,收敛速度慢。该文在Elman神经网络预测前,进行了相关系数预处理和对样本中异常值的平均化预处理,通过数据归一化运算,使Elman神经网络输入层变量大幅减少。仿真实验表明,改进的Elman神经网络算法使预测模型快速寻优,减少预测时间的同时明显提高预测精度。     

Probabilistic seismic damage assessment of reinforced concrete buildings considering directionality effects

Most of buildings and structures are usually projected according to two main axes. However, the geographical position of these buildings varies randomly. Such random distributions of the azimuthal positions of structures, in most of the cities, generally, are not accounted for when assessing their seismic risk; certainly, the direction of the seismic loads is another highly random variable. Moreover, an additional important source of uncertainty is related to the structural response, mainly due to the random character of the mechanical properties. There is a consensus that uncertainties must be considered for adequately assessing the seismic risk of structures, but these directionality effects have not been deeply explored so far. In this article, the influence of the high uncertainty involved in these input variables on the expected seismic damage is analysed. Thus, an actual earthquake, which affected the southern part of Spain, is studied. Notably, damages on a group of affected buildings, located close to the epicentre, are analysed and discussed in detail. The results show that the influence of the random azimuthal position of structures is an important source of uncertainty and that it should be taken into account when estimating the expected seismic risk in urban areas.     

Health risk assessment of chlorpyrifos inhalation exposure among chilli-growing farmers in Na-Krasaeng Sub-District,Det Udom District,Ubon Ratchathani Province,Thailand

The paper reports a health risk assessment of pesticide exposure among chilli-growing farmers living in Na-Krasaeng Sub-District, Det Udom District, Ubon Ratchathani Province, Thailand. Personal air samples were collected from 46 participants spraying pesticide. These samples were analysed to investigate the farmers’ exposure by inhalation of the organophosphate, chlorpyrifos, which is the predominant pesticide used in the study area. The potential health risk of the farmers through inhalation was estimated by calculating the Hazard Quotient (HQ). The results showed that chlorpyrifos concentrations in inhaled air samples from the farmers ranged from less than the limit of detection, <LOD, to 0.041 mg/m3 with an average of 0.0072 mg/m3. Average daily doses (ADD) of exposure were calculated to be in the range 0–0.007 mg/kg/day with a mean value of 0.0014 mg/kg/day. The estimated risk quotient was 0 to 2.35 and the mean value was 0.84. Accordingly, the chilli-growing farmers were not considered to be a population at risk (mean value of HQ ≤ 1). But, the estimated risk of 17.38% of the study population was higher than the acceptable level (HQ > 1). This indicated that some participants were considered as an individual risk which should be of concern.     

压裂水平井产能预测方法研究进展

水平井压裂技术在低渗透及非常规储层中得到了广泛应用,压裂后水平井的产能预测关系到油田开发方案的制定,因此,国内外学者对压后渗流模型的建立和求解方法做出了不懈的努力。本文详细回顾了国内外学者所建压裂水平井产能预测模型及求解方法,指出了不同模型和求解方法的优缺点,并展望了压裂水平井产能模型的发展方向。