基于Monte-Carlo随机有限元的火灾可靠性研究--以混凝土简支梁为例

通过对建筑火灾的背景分析和研究现状的回顾,指出了进行建筑火灾可靠性研究的必要性.介绍了蒙特卡罗随机有限元计算的基本原理、随机数的产生办法和模拟次数的确定,最后作者采用通用有限元程序ANSYS计算了混凝土简支梁在不同温度、保护层厚度和荷载下的火灾可靠性.     

Taking account of the role of safety on vehicle choice using a new generation of discrete choice models

In attitudinal studies safety often appears as an important attribute desired by consumers when buying a new car (Ben-Akiva and Lerman, 1985). However, economic models of vehicle choice usually neglect the role of safety. On the one hand, to capture the qualitative nature of safety and variables related to safety one should consider safety as an underlying construct in a context of latent variable models. The problem is that psychometric models that make use of latent variables do not necessarily provide a complete understanding of agent behavior and may lead to poor predictive power. On the other hand, discrete choice models - although a powerful tool to explain decision making based on utility maximization behavior - fail to include qualitative factors as explanatory variables of the decision process.In this paper, we explore how to model safety through a new generation of discrete choice models which simultaneously consider both a standard discrete choice model and latent causal variables. Using stated preference data concerning purchase intentions of low-emission vehicles in Canada, we test a hybrid choice model to explain consumers’ preferences for safety. Based on the results as well as on the hybrid choice modeling approach, we outline a general framework for the correct modeling of the adoption of safer vehicles and appreciation of safety equipment.     

基于潜变量回归模型的城市火灾风险评估

为评估城市火灾风险等级,针对城市火灾发生的可能性与严重性2个基本问题,建立评估指标体系,提出一种基于潜变量回归的评估模型,并给出无须迭代的确定性算法。该模型和算法无需事先指定风险等级评估分数的训练样本,不必事先指定指标汇总的加权系数,利用合理的配方约束,完成潜变量回归,实现城市火灾风险按地区或者按行业的等级评估,利用现成的软件计算,同样适用于其他具有类似数据结构的评估问题。     

Planning Agricultural Water Resources System Associated With Fuzzy and Random Features1

Li, Y.P. and G.H. Huang, 2011. Planning Agricultural Water Resources System Associated With Fuzzy and Random Features. Journal of the American Water Resources Association (JAWRA) 47(4):841‐860. DOI: 10.1111/j.1752‐1688.2011.00558.x Abstract: More and more regions where demand outstrips water resources availability have suffered from chronic severe shortages. It is particularly aggravated for agricultural irrigation systems where more water is necessary to support the rapidly increasing population and speedily developing economy. In this study, a two‐stage fuzzy‐stochastic programming (TFSP) method is developed for planning agricultural water resources management system in more efficient and sustainable ways. The developed method can address uncertain parameters described as probability distributions and fuzzy sets. It can also be used for analyzing various policy scenarios that are associated with different levels of economic consequences since penalties are exercised with recourse actions against any infeasibility. The developed method is applied to agricultural water‐resources management planning of the Zhangweinan River Basin, China. Solutions under various α‐cut levels and fuzzy dominance indices can be generated by solving a series of deterministic submodels, which can help determine optimized crop‐target values that could hedge appropriately against future available water levels. The results are helpful for water resources managers in not only making decisions of crop irrigation but also gaining insight into the tradeoffs between economic objective and system‐failure risk.     

The Regionalization of National‐Scale SPARROW Models for Stream Nutrients1

Schwarz, Gregory E., Richard B. Alexander, Richard A. Smith, and Stephen D. Preston, 2011. The Regionalization of National‐Scale SPARROW Models for Stream Nutrients. Journal of the American Water Resources Association (JAWRA) 47(5):1151‐1172. DOI: 10.1111/j.1752‐1688.2011.00581.x Abstract: This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national‐scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national‐scale and regional‐scale information to estimate a hybrid model that imposes cross‐region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.     

湖泊水体富营养化评价的随机模拟与三角模糊数耦合模型

根据湖泊水环境系统的不确定性,建立了基于随机模拟和三角模糊数的湖泊水体富营养化评价耦合模型,采用三角模糊数表征各营养因子监测值,运用随机模拟方法模拟三角模糊数,得到各变量的随机模拟序列,由综合营养状态指数法确定湖泊的营养等级概率水平。以宁夏沙湖为例,运用此耦合模型对水体的富营养化程度进行评价。结果表明:该方法将水体富营养评价中水环境状态的不确定性以确定性方法融入评价模型,直观表征了水体在各营养状态隶属度的复杂性,评价结果更加全面、合理。     

碳交易政策下的物流与制造业联动减排随机演化博弈

考虑外部环境的不确定性,构建由地方政府、制造商与物流企业构建的三方随机演化模型,对模型的稳定性进行讨论得到稳态条件,结合数值仿真方法对博弈主体策略演化进行研究.结果表明：规制成本与上级政府的倒查机制是影响地方政府策略选择的重要因素,较高的碳交易价格将促进博弈系统向（积极规制,绿色生产,绿色运输）理想策略集演化,理想策略集下初始策略选择概率的改变一定程度上影响了主体演化的速率,即便制造商在博弈初期的绿色生产策略选择概率为0.1,仍能以最快的演化速率向绿色生产稳定策略收敛.联动发展下制造商的绿色生产策略将带动物流企业选择绿色运输策略,物流企业对碳交易价格与碳配额的敏感性要大于制造商,物流企业向绿色运输演化速率与碳配额成负相关,与碳交易价格成正相关.碳交易财政收入的增加促进了地方政府的积极规制行为,但当财政收入系数增加至0.3时可能导致物流企业的策略选择不稳定.伴随着随机干扰强度的升高,制造商保持了最高的稳定性,在情形一、二中的波动幅度分别为0.4667~1与0.5618~1,而物流企业的策略选择波动性最强,在情形一、二中得波动幅度分别为0.3856~1与0.4616~1,且在演化初期长期处在不稳定状态.     

GROUND WATER DROUGHT MANAGEMENT BY A FEEDFORWARD CONTROL METHOD1

ABSTRACT: Management of a regional ground water system to mitigate drought problems at the multi‐layered aquifer system in Collier County, Florida, is the main topic. This paper developed a feedforward control system that consists of system and control equations. The system equation, which forecasts ground water levels using the current measurements, was built based on the Kalman filter algorithm associated with a stochastic time series model. The role of the control equation is to estimate the pumping reduction rate during an anticipated drought. The control equation was built based on the empirical relationship between the change in ground water levels and the corresponding pumping requirement. The control system starts with forecasting one‐month‐ahead ground water head at each control point. The forecasted head is in turn used to calculate the deviation of ground water heads from the monthly target specified by a 2‐in‐10‐year frequency. When the forecasted water level is lower than the target, the control system computes spatially‐varied pumping reduction rates as a recommendation for ground water users. The proposed control system was tested using hypothetical droughts. The simulation result revealed that the estimated pumping reduction rates are highly variable in space, strongly supporting the idea of spatial forecasting and controlling of ground water levels as opposed to a lumped water use restriction method used previously in the model area.     

DROUGHT INDICATORS AND TRIGGERS: A STOCHASTIC APPROACH TO EVALUATION1

ABSTRACT: Drought management depends on indicators to detect drought conditions, and triggers to activate drought responses. But determining those indicators and triggers presents challenges. Indicators often lack spatial and temporal transferability, comparability among scales, and relevance to critical drought impacts. Triggers often lack statistical integrity, consistency among drought categories, and correspondence with desired management goals. This article presents an approach for developing and evaluating drought indicators and triggers, using a probabilistic framework that offers comparability, consistency, and applicability. From that, a multistate Markov model investigates the stochastic behavior of indicators and triggers, including transitioning, duration, and frequency within drought categories. This model is applied to the analysis of drought in the Apalachicola‐Chattahoochee‐Flint River Basin in the southeastern United States, using indicators of the Standardized Precipitation Index (for 3, 6, 9, and 12 months), the Palmer Drought Severity Index, and the Palmer Hydrologic Drought Index. The analysis revealed differences among the performance of indicators and their trigger thresholds, which can influence drought responses. Results contribute to improved understanding of drought phenomena, statistical methods for indicators and triggers, and insights for drought management.