基于有限元法的双层底板立式储罐可靠性分析

针对双层底板结构储罐上层底板变形过大产生强度失效问题的隐患,通过对装满辛烷的储罐结构力学行为进行有限元分析,研究了不同底板支撑结构形式及不同格栅间距情况下,上层底板的挠度变形及储罐的应力分布情况.研究结果表明在双层底板立式储罐的设计过程中应注重罐壁底部位置加强措施.     

Chlorinated and polycyclic aromatic hydrocarbons in riverine and estuarine sediments from Pearl River Delta, China

Spatial distribution of chlorinated hydrocarbons [chlorinated pesticides (CPs) and polychlorinated biphenyls (PCBs)] and polycyclic aromatic hydrocarbons (PAHs) was measured in riverine and estuarine sediment samples from Pearl River Delta, China, collected in 1997. Concentrations of CPs of the riverine sediment samples range from 12 to 158 ng/g, dry weight, while those of PCBs range from 11 to 486 ng/g. The CPs concentrations of the estuarine sediment samples are in the range 6-1658 ng/g, while concentrations of PCBs are in the range 10-339 ng/g. Total PAH concentration ranges from 1168 to 21,329 ng/g in the riverine sediment samples, whereas the PAH concentration ranges from 323 to 14,812 ng/g in the sediment samples of the Estuary. Sediment samples of the Zhujiang River and Macao harbor around the Estuary show the highest concentrations of CPs, PCBs, and PAHs. Possible factors affecting the distribution patterns are also discussed based on the usage history of the chemicals, hydrologic condition, and land erosion due to urbanization processes. The composition of PAHs is investigated and used to assess petrogenic, combustion and naturally derived PAHs of the sediment samples of the Pearl River Delta. In addition, the concentrations of a number of organic compounds of the Pearl River Delta samples indicate that sediments of the Zhujiang river and Macao harbor are most likely to pose biological impairment.     

Fe3O4-TiO2Al吸附剂去除水中氟离子

以实验室制备的Fe3O4-TiO2·nH2O·Al吸附剂处理模拟和实际含氟废水,探讨了吸附剂用量、体系pH、吸附温度和吸附时间等因素对F-吸附效果的影响。结果表明:在初始F-浓度16.1 mg/L,起始pH 8.0,吸附剂投加量5 g/L,室温(约25 ℃)下吸附15 min时,模拟和实际废水的出水F-均可达到3O4-TiO2·nH2O·Al具有一定的实际应用价值。含氟水溶液初始pH对Fe3O4-TiO2·nH2O·Al吸附F-性能影响较大。在pH 介于3.0~5.0 时,吸附容量较大,过高或过低都会导致吸附容量降低。Fe3O4-TiO2·nH2O·Al吸附F-的过程为放热反应,升温不利于F-的吸附。该吸附剂吸附F- 的过程为化学吸附,符合准二级动力学模型,等温线拟合接近Freundlich吸附等温线。     

微机上冲裁CAD系统的开发

此文介绍了一套在微机上开发的冲裁CAD系统。它以Foxbase作为数据库管理系统,Trubo C为编程语言,能进行冲裁件图形输入与显示、工艺性分析、优化单排排样和选择板材规格、冲裁件尺寸识别和模具刃口尺寸计算、冲裁力和压力中心计算、以及凹模周界尺寸计算等。本系统主界面为下拉式菜单界面,全中文提示,人机界面友好,具有较好的可扩充性和容错性。     

丙烯腈生产废水中聚合物的资源化利用

以丙烯腈生产废水中的丙烯腈低聚物为原料制备聚丙烯酰胺。通过正交实验考察了水解反应条件和交联反应条件对反应的影响。FTIR表征结果显示,丙烯腈低聚物中的氰基已完全水解为酰胺基,产物聚丙烯酰胺中含有酰胺基和羧基。实验结果表明,在自来水加入量100 m L、水解反应温度95℃、m(Na OH)∶m(丙烯腈低聚物)=2.0、水解反应时间3 h的最佳水解反应条件,交联反应温度60℃、质量分数37%~40%的甲醛加入量6 m L、交联反应时间2 h的最佳交联反应条件下,处理20 g丙烯腈低聚物,可得到产物聚丙烯酰胺14.50 g,聚丙烯酰胺的水解度为21.1%、相对分子质量为2.7×106。产品性能满足Q/SH 0046—2007《钻井液用聚丙烯酰胺技术要求》中部分水解聚丙烯酰胺的性能要求。     

Geochemistry of tin (Sn) in Chinese coals

Environmental Geochemistry and Health - Based on 1625 data collected from the published literature, the geochemistry of tin (Sn) in Chinese coals, including the abundance, distribution, modes of...     

A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007

This paper provides a performance evaluation of the real-time, CONUS-scale National Air Quality Forecast Capability (NAQFC) that supported, in part, its transition into operational status. This evaluation focuses primarily on discrete forecasts for the maximum 8-h O₃ concentrations covering the 4-month period, June through September, 2007, using measurements obtained from EPA's AIRNow network. Results indicate that the 2007 NAQFC performed as well or better than previous configurations, despite the expansion of the forecast domain into the western half of the nation that is dominated by complex terrain. The mean, domain-wide, season-long correlation was 0.70. When examined over time, the domain-wide correlations exhibit a fairly consistent nature, with values exceeding 0.60 (0.70) over 90% (55%) of the days. The NAQFC systematically over-predicted the 8-h O₃ concentrations, continuing a trend established by earlier NAQFC configurations, though to a lesser degree. The summer-long mean forecast value of 53.2 ppb was 4.2 ppb higher than the observed value, resulting in a domain-wide Normalized Mean Bias (NMB) of 8.7%. Most of the over-prediction is associated with observed concentrations less than 50 ppb. In fact the model tends to under-predict when concentrations exceed 70 ppb. As with the bias, the error associated with the latest configuration was also lower. The summer-long Root Mean Square Error of 13.0 ppb (Normalized Mean Error (NME) = 20.4%) represented marked improvements over earlier forecasts. Examination of the spatial distribution of both the NMB and NME reveals that the NAQFC was generally within 25% for the NME and 25% for the NMB over a majority of the domain. Several areas of poorer performance, where the NMB and NME often exceed 25% and in some cases 50%, were noted. These areas include southern California, where the NAQFC tended to under-predict concentrations (especially on weekends) and the southeast Atlantic and Gulf coasts regions, where the model over-predicted. Subsequent analysis revealed that the incorrect temporal allocation of precursor emissions was likely the source of the under-prediction in southern California, while inaccurate simulation of PBL heights likely contributed to the over-prediction in the coastal regions.     

APPLICATION OF GREY MODEL AND ARTIFICIAL NEURAL NETWORKS TO FLOOD FORECASTING1

The main focus of this study was to compare the Grey model and several artificial neural network (ANN) models for real time flood forecasting, including a comparison of the models for various lead times (ranging from one to six hours). For hydrological applications, the Grey model has the advantage that it can easily be used in forecasting without assuming that forecast storm events exhibit the same stochastic characteristics as the storm events themselves. The major advantage of an ANN in rainfall‐runoff modeling is that there is no requirement for any prior assumptions regarding the processes involved. The Grey model and three ANN models were applied to a 2,509 km² watershed in the Republic of Korea to compare the results for real time flood forecasting with from one to six hours of lead time. The fifth‐order Grey model and the ANN models with the optimal network architectures, represented by ANN1004 (34 input nodes, 21 hidden nodes, and 1 output node), ANN1010 (40 input nodes, 25 hidden nodes, and 1 output node), and ANN1004T (14 input nodes, 21 hidden nodes, and 1 output node), were adopted to evaluate the effects of time lags and differences between area mean and point rainfall. The Grey model and the ANN models, which provided reliable forecasts with one to six hours of lead time, were calibrated and their datasets validated. The results showed that the Grey model and the ANN1010 model achieved the highest level of performance in forecasting runoff for one to six lead hours. The ANN model architectures (ANN1004 and ANN1010) that used point rainfall data performed better than the model that used mean rainfall data (ANN1004T) in the real time forecasting. The selected models thus appear to be a useful tool for flood forecasting in Korea.