汽车排放污染物浓度的预测

为了预测汽车排放污染物的浓度,应用简化的高斯烟团模式得到静风条件下的线源扩散预测模式。并结合高斯烟流扩散模式,建立了预测汽车污染物在任意风向下和年平均浓度的预测模式,考虑车道上存在车辆行驶的强烈机械扰动湍流和把繁忙的公路视为线源两个因素,提出了计算初始扩散参数的方法。然后,运用Turner和Pasquill扩散参数,建立了线源扩散参数的确定方法。该模式应用于预测高速公路沿途汽车污染物的浓度表明,计算值与监测值吻合较好,可用于我国公路环境影响的评价。     

二维多箱模型预测大气环境方法的研究

采用二维多箱模型对石家庄市区大气污染物ＳＯ２进行了计算,分别计算了４个风向的各子箱污染物浓度,然后按其风向频率加权取和得到平均浓度。把计算结果与地面监测值和１９９４－０１中国环境科学研究院的高空航测值进行了比较分析后发现。多箱模型预测大气环境比单箱模型和其它预测方法产生的误差要小。     

Evaluation of the effect of meteorological data resolution on Lagrangian particle dispersion simulations using the ETEX experiment

This paper presents results from a series of numerical experiments designed to evaluate operational long-range dispersion model simulations, and to investigate the effect of different temporal and spatial resolution of meteorological data from numerical weather prediction models on these simulations. Results of Lagrangian particle dispersion simulations of the first tracer release of the European Tracer Experiment (ETEX) are presented and compared with measured tracer concentrations. The use of analyzed data of higher resolution from the European Center for Medium-Range Weather Forecasts (ECMWF) model produced significantly better agreement between the concentrations predicted with the dispersion model and the ETEX measurements than the use of lower resolution Navy Operational Global Atmospheric Prediction System (NOGAPS) forecast data. Numerical experiments were performed in which the ECMWF model data with lower vertical resolution (4 instead of 7 levels below 500 mb), lower temporal resolution (12 h instead of 6 h intervals), and lower horizontal resolution (2.5° instead of 0.5°) were used. Degrading the horizontal or temporal resolution of the ECMWF data resulted in decreased accuracy of the dispersion simulations. These results indicate that flow features resolved by the numerical weather prediction model data at approximately 45 km horizontal grid spacing and 6 h time intervals, but not resolved at 225 km spacing and 12 h intervals, made an important contribution to the long-range dispersion.     

基于灰色关联分析法的林甸县污水泡中重金属和毒性元素污染情况评价

为了探讨人类活动对水体重金属和毒性元素含量的影响,测量了污水泡8个样点的Mn、Fe、Cu、Zn、Cd、Pb等重金属和As、Se等毒性元素质量浓度。在综合考虑各种水质评价方法的基础上,采用灰色关联分析方法对水中重金属和毒性元素污染情况进行了评价。结果显示,水中重金属和毒性元素污染并不严重,8个采样点中有7个样点符合Ⅰ类水体标准,1个样点为Ⅱ类水体。其原因是污水泡附近没有工业区,排出的污水属生活污水,污染并非重金属和毒性元素造成。     

Forecasting the impact of meteorological parameters on air pollutants in Andhra Pradesh using machine learning techniques

In the 21st century, air pollution has emerged as a significant problem all over the globe due to a variety of activities carried out by humans, such as the acceleration of industrialization and urbanization. SO₂, NO₂, and NH₃ are the key components contributing to air pollution. Moreover, these air pollutants have a significant connection to several climatic characteristics, such as the speed of the wind, the relative humidity, the temperature, the amount of precipitation, and the surface pressure. As a result, machine learning (ML) is regarded as a more effective strategy for predicting air quality than more conventional approaches such as probability and statistics, among others. In the research, Decision Tree (DT), Support Vector Regression (SVR), Random Forest (RF), and Multi-Linear Regression (MLR) algorithms are used to make predictions about air quality, and MSE (Mean Squared Error), RMSE (Root Mean Square Error), MAE (Mean Squared error), and R² are used to determine how accurate the predictions are.     

基于T-P模型的高低温环境型煤对甲烷吸附性能预测

为预测深部或浅部煤层不同温度和不同压力条件下的吸附等温线,选用型煤以高低温试验装置为依托,测试了温度为293.15,273.15,253.15 K的吸附等温线。基于T-P模型,利用等温吸附曲线对公式中的参数进行了合理的求解,探讨了一种简单的煤对瓦斯吸附等温线预测方法。研究表明:同一吸附平衡压力下,温度越低,煤的瓦斯吸附量越大;ε－ω吸附特征曲线与温度无关,呈现对数的形式;参数m和拟合度R2满足抛物线的关系,存在拟合效果最好时的参数m值。采用T-P模型预测得到的吸附等温线与实测的吸附等温线无论是趋势还是定量结果均十分吻合,其相对误差不超过5%。     

高层建筑电气火灾隐患因子定量分析方法研究

为了对高层建筑电气火灾隐患排查进行定量化分析,采用解释结构模型构建高层建筑电气火灾隐患因子的复杂逻辑模型;在利用德尔菲法确定隐患因子初始概率的基础上,经过交叉影响分析法求解交叉影响概率矩阵;引入马尔科夫链修正各隐患因子交叉影响后的概率,得到火灾隐患因子的稳态概率矩阵。研究结果表明:各隐患因子的马尔科夫链校正概率比德尔菲法测定的初始概率更加准确,该计算排序结果可明确高层电气火灾隐患排查和管控的重点。     

易自燃厚煤层工作面自然发火CO预测及防治

为了有效预防遗煤自燃,深入研究自然发火初期的CO预测技术。基于回风隅角CO源的理论模型,以Gambit建立相似二维采场模型,数值模拟了采空区自燃“三带”范围,并采用现场束管监测手段对结果进行了验证。利用程序升温实验获得了不同温度段回风隅角CO的极限指标,并与现场实测值对比分析,进而预判采空区遗煤发火程度,为制定有针对性的防治措施提供理论指导。研究结果表明:CO作为低温氧化阶段预测指标对预防遗煤自燃具有重要作用。     

Consequence prediction for dust explosions involving interconnected vessels using computational fluid dynamics modeling

Combustible dust explosions continue to present a significant threat toward operating personnel and pneumatic conveyance equipment in a wide variety of processing industries. Following ignition of suspended fuel within a primary enclosure volume, propagation of flame and pressure fronts toward upstream or downstream interconnected enclosures can result in devastating secondary explosions if not impeded through an appropriate isolation mechanism. In such occurrences, an accelerated flame front may result in flame jet ignition within the secondary vessel, greatly increasing the overall explosion severity. Unlike an isolated deflagration event with quantifiable reduced pressures (vent sizing according to NFPA 68 guidance), oscillation of pressure between primary and secondary process vessels leads to uncertain overpressure effects. Dependent on details of the application such as relative enclosure volumes, relief area, fuel type, suspended concentration, duct size, and duct length, the maximum system pressure in both interconnected vessels can be unpredictable. This study proposes the use of FLame ACceleration Simulator (FLACS) computational fluid dynamics (CFD) modeling to provide reliable consequence predictions for specific case scenarios of dust deflagrations involving interconnected equipment. Required minimum supplement to the originally calculated relief area (A_v) was determined through iterative simulation, allowing for reduced explosion pressures (P_red) to be maintained below theoretical enclosure design strengths (P_es).     

基于不同指标无量纲化方法的岩爆预测模型优选

为研究不同指标无量纲化方法对岩爆等级预测模型精度的影响,提高岩爆预测准确率,选取应力系数、脆性系数和弹性能量指数作为预测指标。基于104组岩爆实例大样本数据,采用统一极差处理法、差异化极差处理法、平均化处理法和归一化处理法4种指标无量钢化方法,对预测指标的原始数据进行处理,建立不同的岩爆预测距离判别模型并进行工程实例应用。研究结果表明:基于平均化处理法的岩爆预测模型的回判准确率高达97.1%;对不同矿山、隧道和水电站的6个工程实例的预测结果符合实际情况,说明其是一种准确率高、方便实用的岩爆预测模型。