基于VMAS四川省在用点燃式轻型车尾气污染削减预测

针对四川省在用车辆尾气污染情况开展了详细的调查研究,结果表明四川省机动车尾气污染中约71.3%的CO、68.6%的HC、95.3%的NOx和99.2%的PM均来自于汽车尾气。同时分析得出简易瞬态工况法是在用车辆尾气排放控制的有效控制方法,有利于四川省大气环境质量的改善,经预测采用简易瞬态工况法以及简易瞬态工况法排放标准后可使四川省在用点燃式轻型车尾气排放的CO削减约28.76%~50.48%,HC+NOx削减约1.53%~23.24%。     

四川西南部山区风电场工程水土流失预测浅析

本文介绍了凉山州长海子风电场工程水土流失预测范围与时段、内容与方法。通过采用类比工程法进行预测,得到了水土流失预测结果,确定了风电场水土流失重点区域为交通设施区、弃渣场区,水土流失主要时段为施工期。据此预测结果,为工程在建设过程中提出了水土保持设计建议。     

风蚀性粒子降尘浓度的动力学预报模式

为探求开放源露天煤尘在自然风力作用下的扩散情况,本研究采用空气动力学的数值计算方法,以离散相拉格朗日随机轨道为计算模型,预测了原煤、大矿、水洗和精煤4类煤种料堆的降尘浓度分布,并采用风洞试验对结果进行了对比验证.结果表明:动力学模式对风蚀粒子的预报误差在±25%,其中原煤种的预报度最高,误差10%.动力学模式与高斯沉降模式相比,高斯模式对尘源处的降尘浓度预报误差过大,动力学预报模式是基于颗粒群的运动轨迹的行为预报,能准确地描述粗大颗粒的跃移运动状态,对于满足Rosin-Rammler粒径分布的固体粒子降尘浓度的预报良好.     

水电工程施工阶段应急管理系统脆弱性评价

为有效评估水电工程施工阶段应急管理系统应急能力并发现系统中的薄弱环节,提出一种应急管理系统脆弱性评价方法。首先,引入脆弱性理论,将应急管理系统的脆弱性分为暴露性、适应性和恢复性3部分;然后,根据水电工程施工阶段应急管理系统的特点构建了进攻性和防御性指标体系,并运用ANP（网络层次分析法）计算各指标权重,结合灰色聚类分析得到各防御性指标和系统整体的脆弱性系数,从而判断水电工程施工阶段应急管理系统脆弱性等级;最后,运用该模型对国内某水电站工程应急管理系统进行评价,在定量计算的基础上得到该应急系统的脆弱性等级,结果表明该系统脆弱性等级处于中等状态,并发现其薄弱环节,为完善水电工程施工阶段应急管理系统的建设提供支撑。     

基于微震监测的岩体失稳智能预报

岩体稳定性预报是微震监测工作的重要组成部分。探讨微震活动性参数变化作为岩体稳定性预测的可行性,结合用沙坝矿实际生产过程中观测到的现象,提出微震监测岩体失稳预报的一般模式。根据b值在岩体失稳前先增大后减小的趋势作为危险预警初始条件;并将能量指数、施密特数急剧下降以及累积视体积增加的时间段作为岩体失稳的预警期,将事件数的急剧下降作为危险的临界状态。用沙坝矿根据这一原理建立的岩体失稳预报模式可以达到采场失稳的智能预报,解决了人工判别预警期过程中效率低的难题,保障矿山的生产工作。     

Evaluation of the k-nearest neighbor method for forecasting the influent characteristics of wastewater treatment plant

The k-nearest neighbor (k-NN) method was evaluated to predict the influent flow rate and four water qualities, namely chemical oxygen demand (COD), suspended solid (SS), total nitrogen (T-N) and total phosphorus (T-P) at a wastewater treatment plant (WWTP). The search range and approach for determining the number of nearest neighbors (NNs) under dry and wet weather conditions were initially optimized based on the root mean square error (RMSE). The optimum search range for considering data size was one year. The square root-based (SR) approach was superior to the distance factor-based (DF) approach in determining the appropriate number of NNs. However, the results for both approaches varied slightly depending on the water quality and the weather conditions. The influent flow rate was accurately predicted within one standard deviation of measured values. Influent water qualities were well predicted with the mean absolute percentage error (MAPE) under both wet and dry weather conditions. For the seven-day prediction, the difference in predictive accuracy was less than 5% in dry weather conditions and slightly worse in wet weather conditions. Overall, the k-NN method was verified to be useful for predicting WWTP influent characteristics.     

白云岩单轴压缩试验声发射特性研究

在单轴压缩条件下,进行白云岩破坏全过程的声发射试验研究,得到应力、声发射特性与时间的关系,并研究了岩体的Kaiser效应。结果表明:（1）岩石单轴压缩破坏过程中并不是所有试验岩样有具有典型的声发射特征阶段,部分岩样AE曲线中可以找到Kaiser效应特征点,但是多数岩样的Kaiser效应特征点不明显;（2）岩样的AE现象在应力达到峰值前会经过一个平静期,而在岩石发生破坏直至彻底破坏阶段,AE现象明显增加,这个先平静后剧增的过程可以作为预报岩爆发生的一种警示信号;（3）大多数岩样都在AE能量达到最大时发生彻底破坏。     

基于AHP-GCE的固体火箭发动机水射流清理系统安全评价

针对固体火箭发动机水射流清理系统中诸多危险因素所呈现出的复杂性和不确定性,根据水射流清理固体推进剂装药的作业流程,利用层次分析法建立了其安全评价的指标体系,进而采用灰色综合评价法对固体火箭发动机水射流清理系统进行了安全评价。评价结果表明,固体火箭发动机水射流清理系统的综合评价值为31126,处于较高危险状况,需要对其中的危险因素加强防控;水射流清理平台的综合评价值为32417,高于整体综合评价值,因而需要在风险防控中予以着重关注;评价结果与实际情况吻合良好。     

The humanitarian response costs of climate change

This research attempts to improve understanding of how climate change may affect international humanitarian spending, using existing international databases that track disaster occurrence and humanitarian costs. A range of potential impact scenarios is developed employing four distinct methodological approaches. The findings indicate that climate change will have a significant impact on humanitarian costs and the increase could range from a 32 per cent increase (taking into account only changes in frequency of disasters) to upwards of a 1,600 per cent increase when other criteria, such as intensity, are also taken into account. The paper further highlights that extreme weather events do not occur in isolation and the increasing interconnectedness of world economic and political systems has made disasters more complex and destructive. It makes a number of recommendations, including the need for more rigorous and systematic collection of disaster-related data and more constructive interaction between the humanitarian and climate change communities on future research, planning and action.     

有机污染物生物降解性预测模型

生物降解性是评估污染物环境持久性的重要依据,也是化学品是否获准生产及进入市场的评价指标。采用17位生物降解领域专家评估的生物降解等级数据,通过功能树(FT)算法建立了包含15个分子结构参数的初级生物降解和最终生物降解预测模型。外部验证结果表明,模型具有较好的预测准确性,初级生物降解性加权准确度(weighted accuracy,WA):训练集WA=84.1%,验证集WA=78.9%;最终生物降解性WA:训练集WA=91.0%;验证集WA=83.6%。预测正确性对化合物的杠杆值作图,表征了生物降解性模型的应用域。