基于ANSYS的可靠度分析方法及应用

通过对可靠度分析的概述理解到现代工程分析中实体模型不确定因素众多,进而带来分析的不准确性。基于有限元分析软件ANSYS提供的概率设计系统(PDS)的概率分析功能,使对结构的概率分析非常容易。根据结构的失效模式来确定结构功能函数,由此建立结构极限状态方程,再运用结构可靠度分析中的蒙特卡洛法(MCS法)利用结构的失效频率来估算其失效概率。在本文中提出了利用ANSYS的概率分析功能结合MCS法进行结构的可靠性分析的方法,并通过一个实例具体说明了利用ANSYS的概率分析功能实现结构的可靠性分析的可行性。     

故障树法和改进PSO-PNN网络的电梯故障诊断模型

针对电梯故障问题,提出一种将故障树分析法、改进的粒子群优化算法和概率神经网络相结合的方法用于电梯的故障诊断。以电梯的安全回路系统为例,用故障树法对回路进行分析,获得训练样本与故障类型;使用粒子群算法对概率神经网络的平滑因子进行优化,在优化过程中,针对粒子群算法存在易陷入局部最优的缺陷,提出对惯性权重的改进策略;采用相对误差对诊断效果做出评估,并与传统的概率神经网络和基本粒子群算法优化的概率神经网络在各种故障类型输出和最大相对误差等方面进行比较,结果表明:该模型能够有效诊断电梯故障。     

A Probabilistic,Parcel‐Level Inundation Prediction Tool for Medium‐Range Flood Forecasting in Large Lake Systems

This study contributes a bathtub‐style inundation prediction model with abstractions of coastal processes (i.e., storm surge and wave runup) for flood forecasting at medium‐range (weekly to monthly) timescales along the coastline of large lakes. Uncertainty from multiple data sources are propagated through the model to establish probabilistic bounds of inundation, providing a conservative measure of risk. The model is developed in a case study of the New York Lake Ontario shoreline, which has experienced two record‐setting floods over the course of three years (2017–2019). Predictions are developed at a parcel‐level and are validated using inundation accounts from an online survey and flyover imagery taken during the recent flood events. Model predictions are compared against a baseline, deterministic model that accounts for the same processes but does not propagate forward data uncertainties. Results suggest that a probabilistic approach helps capture observed instances of inundation that would otherwise be missed by a deterministic inundation model. However, downward biases are still present in probabilistic predictions, especially for parcels impacted by wave runup. The goal of the tool is to provide community planners and property owners with a conservative, parcel‐level assessment of flood risk to help inform short‐term emergency response and better prepare for future flood events.     

USE OF CLIMATE PREDICTIONS TO DECIDE A WATER MANAGEMENT PROBLEM1

ABSTRACT: Seasonal precipitation predictions were utilized in a water management decision with major economic, societal, and political ramifications. A summer (1984) drought had created a situation calling for possible fall season use of state waters from two major multipurpose reservoirs with an ensuing effect on water price negotiations. Choices facing management and use of water from the reservoirs were to invoke expensive water restrictions with a 33 percent chance of being right, do nothing (66 percent chance of wrong outcome), or use the precipitation predictors (for above normal fall rain) having a 50 percent chance of error. Hydrologists chose to follow the precipitation predictions, which proved to be accurate for the fall of 1984, helping to reveal the long-term value of using well understood climate predictions in water management.     

基于GIS的2.5维场地地震液化势概率评价

用具有概率意义的饱和砂土抗液化强度经验公式对2.5维工程场地进行了地震液化势概率评价,通过Kriging法对目标场地区域进行空间插值,可以对大区域工程场地的液化深度和液化范围进行分析评价;采用不规则三角网表面和四面体综合法共同描述地质体模型,在GIS的3维分析模块支持下建立了液化势可视化模型。研究表明:Kriging法通过已勘测点的土层地震液化势来估计未勘测点的土层地震液化势,能够较好地区划出场地地震液化势的空间分布特征,并对待估点进行预测;利用GIS的3维分析模块,实现2.5维场地地震液化势可视化模型的建立是一条有效的技术路线。     

太湖梅梁湾、贡湖湾和胥口湾水体PAHs的生态风险评价

基于太湖梅梁湾、贡湖湾和胥口湾水体∑PAH8的等效浓度和ΣPAH8对水生生物的无观察效应浓度（NOECs）,分别采用商值法、概率密度函数重叠面积法、安全阈值法和商值概率分布法评价水体∑PAH8对水生生物的生态风险,同时进行方法学比较.商值法评价结果表明∑PAH8对水生生物的生态风险表现为大型蚤（Daphina magn...     

Risk assessment of rare events

Rare events often result in large impacts and are hard to predict. Risk analysis of such events is a challenging task because there are few directly relevant data to form a basis for probabilistic risk assessment. Due to the scarcity of data, the probability estimation of a rare event often uses precursor data. Precursor-based methods have been widely used in probability estimation of rare events. However, few attempts have been made to estimate consequences of rare events using their precursors. This paper proposes a holistic precursor-based risk assessment framework for rare events. The Hierarchical Bayesian Approach (HBA) using hyper-priors to represent prior parameters is applied to probability estimation in the proposed framework. Accident precursor data are utilized from an information theory perspective to seek the most informative precursor upon which the consequence of a rare event is estimated. Combining the estimated probability and consequence gives a reasonable assessment of risk. The assessed risk is updated as new information becomes available to produce a dynamic risk profile. The applicability of the methodology is tested through a case study of an offshore blowout accident. The proposed framework provides a rational way to develop the dynamic risk profile of a rare event for its prevention and control.     

Probabilistic ecological risk assessment for three chlorophenols in surface waters of China

Individual and combined assessment of risks of adverse effects to aquatic ecosystems of three chlorophenols (CPs), including 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TCP) and pentachlorophenol (PCP), were conducted. A probabilistic approach based on the concentrations of CPs in surface waters of China was used to determine the likelihood of adverse effects. The potential risk of CPs in surface waters of China was determined to be of concern, especially PCP and mixtures of CPs. The risks of adverse effects were examined as the joint probabilities of exposure and response. The joint probability for PCP was 0.271 in the worst case and 0.111 in the median case, respectively. Based on the cumulative probability, 5% of aquatic organisms included in the assessment would be affected 21.36% of the time in the worst case and 5.99% of the time in median case, respectively. For the mixtures of CPs, the joint probability were 0.171 in the worst case and 0.503 in median case, respectively and 5% of species would be affected 49.83% of the time for the worst case and 12.72% in the median case, respectively. Risks of effects of the individual CPs, 2,4-DCP and 2,4,6-TCP were deemed to be acceptable with a overlapping probability of < 0.1 with 5% of species being affected less than 4% of the time.     

The potential of statistical state space models in urban ozone forecasting

State space models for tropospheric urban ozone prediction are introduced and compared with linear regression models. The linear and non-linear state space models make accurate short-term predictions of the ozone dynamics. The average prediction error one hour in advance is 7 μg/m³ and increases logarithmically with time until it reaches 26 μg/m³ after 30 days. For a given sequence of solar radiation inputs, predictions converge exponentially with a time scale of 8 hours, so that the model is insensitive to perturbations of more than 150 μg/m³ O₃. The slow increase of the prediction error in addition to the uniqueness of the prediction are encouraging for applications of state space models in forecasting ozone levels when coupled with a model that predicts total radiation. Since a radiation prediction model will be more accurate during cloud-free conditions, in addition to the fact that the state space models perform better during the summer months, state space models are suitable for applications in sunny environments.     

VOCs污染场地风险管理策略的筛选及评估

以某VOCs(volatile organic compounds,挥发性有机化合物)污染场地为例,结合实地调查,将健康风险评估用于场地风险管理策略的筛选. 结果表明:①该场地不同深度土壤均受到氯仿、二氯甲烷和苯的污染,污染物垂向迁移特征明显,最大迁移深度达25.8 m,其中深度≤15.0 m的土壤污染较重. ②基于保守的通用场地概念模型对将其规划为居住用地时的健康风险进行评估显示,氯仿、二氯甲烷和苯的致癌风险分别达6.0×10-2、2.9×10-4、7.4×10-5,均超过可接受风险水平(1.0×10-6),三者修复目标分别为0.22、12.00和0.64 mg/kg. 如采取策略一,即将场地内超过修复目标的土壤进行清除,需修复的土壤深度达24.0 m,修复土方量为33.4×104 m3. ③结合污染物垂向分布及场地未来地下空间开发规划,提出策略二,即对0~15.0 m深度范围内重污染土壤进行清除异位修复、>15 m深度范围内土壤采取工程控制措施. 实施策略二后的风险评估结果显示,虽然>15.0 m深度范围内土壤中依然存在w(氯仿)超过修复目标的采样点,但致癌风险(8.3×10-8)远低于可接受水平;概率风险评估显示,该风险值对应的累计频率为99.5%,考虑各参数取值的不确定性后,风险模拟结果最大值也仅为1.06×10-7. 可见,策略二足够保守,能够保障未来居民的身体健康;与策略一相比,策略二可减少修复土方量6.4×104 m3,因此更具经济性,为风险管理策略的优选方案.