长埔——西岭锡矿资源定量评价模型

本文以长埔——西岭锡矿带的76个矿床为基础从中选取17个已知成型矿床,分别用矢量长度法和最优分割法进行地质变量的优化选择与储量等级规模的划分;采用特征分析与逻辑信息法建立锡矿资源半定量和定量评价广义模型;并对该区59个矿化点进行含矿性及可能矿床规模的定量预测评价,筛选出6个找矿靶区。     

概率火灾安全分析方法研究

为分析和评估火灾对设备、建筑物等敏感目标结构安全的影响,结合化工定量风险评估方法和气体爆炸概率安全分析方法,提出概率火灾安全分析策略和实施流程.该方法包括火灾危害辨识、泄漏速率计算、火灾后果模拟、频率分析、绘制频率超越热载荷曲线、结构响应分析等关键步骤.以某柴油罐区为例,通过频率分析和火灾模拟,绘制出频率超越热载荷曲线,假定火灾风险可接受准则为10 -4/a,求得对应的可信热载荷为21 kW/m2,并以此值作为结构热响应分析的输入参数.火灾概率安全分析方法侧重于描述火灾热辐射强度及其对应的发生可能性,判定敏感目标遭遇的可信火灾热载荷强度和结构热响应行为,评估消防减灾措施效果,确保结构完整性和可用性,不评价工艺系统潜在火灾风险的高低.     

Preventing the Spread of Invasive Species: Economic Benefits of Intervention Guided by Ecological Predictions

Abstract:  Preventing the invasion of freshwater aquatic species is the surest way to reduce their impacts, but it is also often expensive. Hence, the most efficient prevention programs will rely on accurate predictions of sites most at risk of becoming invaded and concentrate resources at those sites. Using data from Vilas County, Wisconsin (U.S.A.), collected in the 1970s, we constructed a predictive occurrence model for rusty crayfish ( Orconectes rusticus ) and applied it to an independent data set of 48 Vilas County lakes to predict which of these were most likely to become invaded between 1975 and 2005. We nested this invasion model within an economic framework to determine whether targeted management, derived from our quantitative predictions of likely invasion sites, would increase the economic value of lakes in the independent data set. Although the optimum expenditure on lake protection was high, protecting lakes at this level would have produced net economic benefits of at least $6 million over the last 30 years. We did not attempt to determine the value of nonmarket benefits of protection; thus, our results are likely to underestimate the total benefits from preventing invasions. Our results demonstrate that although few data are available early in an invasion, these data may be sufficient to support targeted, effective, and economically rational management. In addition, our results show that ecological predictions are becoming sufficiently accurate that their application in management can produce net economic benefits.     

基于速率倒数法的滑坡时间概率预测∗

在滑坡时间预测中,基于变形监测数据的速率倒数法受到了广泛重视。在该方法的使用过程中,存在模型参数难以同时标定、难以考虑预测时间的不确定性的难题。针对上述不足,提出了一种两阶段速率倒数模型的标定方法。基于该方法可以对模型参数进行同时标定,同时可对滑坡时间进行概率预测。结合10个滑坡案例比较了不同模型假设对滑坡时间预测的影响。结果表明,考虑滑坡时间的不确定性后,预测滑坡时间与实际观测滑坡时间更为符合。考虑速率倒数模型的非线性后,拟合最优模型与实测数据的拟合度更好;但从预测效果而言,线性模型预测结果与滑坡实际发生时间符合的程度更高。     

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。     

基于风险指引的核电厂设计改进评价研究

核电厂概率安全评价(PSA)可以论证核电厂的风险满足安全目标,也是对运行核电厂进行风险管理的有效工具,例如核电厂的在役检查、安全分级、技术规格书优化等。核电厂的风险指引管理是在确定论的基础上,充分利用概率安全评价的结果进行风险影响评价,以此来论证决策的合理性。核电厂的重要设计改进通常基于传统的工程分析结果,没有分析其对核电厂整体风险的影响。重点探讨风险指引决策的基本原则以及方法,以核电厂设计改进实例探讨如何在分析时引入风险指引方法,并提出相关建议。     

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。     

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.     

基于PCA-PNN的采空区多源指标危险性辨识

为了提高采空区多源指标危险性辨识的预测精度,基于主成分分析(PCA)和概率神经网络(PNN),提出1种采空区多源指标危险性辨识方法。将影响华东某地区矿山采空区危险性辨识的9项因素作为主要影响因素,并以96个实测采空区为例进行分级。研究结果表明：与朴素贝叶斯、随机森林和AdaBoost 3种机器学习算法相比,PNN在测试集上表现更好,对实际工程具有良好的指导意义和应用价值。