海河流域河道外生态需水研究

水土流失是海河流域较为突出的生态环境问题之一。经对比研究发现，植被覆盖度的变化会通过影响洪充量，土壤侵蚀量等因子，进而改变水土流失的状况。从提高植被覆盖度尤其是低覆盖度草地植被的角度出发，定量研究了为改善流域水土流失状况河道外生态需水的具体数额，得出海河流域现状年河道外生态耗水（降水）385亿m^3。另外，为改善河道外生态环境状况将低覆盖度草地提高地提高至中等覆盖度水平，则需要增加生态需水12．5亿m^3。     

添加剂组成对通用内燃机油性能的影响

通过相关模拟试验，分析研究了添加剂组成对通用内燃机油的抗磨性能，抗氧化性能以及清净分散性能的影响。     

建筑墙体表面传热系数辨识研究

对实验房间南向墙体内表面中心区域的换热过程进行实验，发现当风速在0－5．5m/s之间时，表面传热系数在8－18W（m^2.K）之间波动，而风向对墙体表面传热系数影响不大；用辅助变量法分析墙体表面传热过程，并结合实验推导出墙体表面传热系数。模型的预测结果与实测结果吻合良好。     

复合形法优化内河航道重力式护岸

采用复合形优化法,结合《港口及航道护岸工程设计与施工规范》中推荐的抗滑、抗倾稳定的分项系数计算方法,并考虑了内河航道船形波等作用的影响效应,对重力式护岸断面进行了优化。     

Effects of Surface Concentration on Drying Behavior of Carbohydrate Solutions

As the surface properties of the drying materials are very important not only for the drying rate but also for the quality change during drying, the effects of surface concentration on the drying behavior of liquid foods (sugar solutions) were investigated by isothermal drying experiments and by numerical calculation experiments. The isothermal drying experiments with gelled sugar solution systems (sucrose and maltodextrin) were carried out at various relative humidity (RH) values (RH = 0 to 84%). Separate experiments were carried out for determination of the desorption isotherms.

The isothermal drying curves of sugar solutions at RH = 0 to 51% were very similar. Numerical simulations also showed that the drying curves of these sugars at the surface concentration = 0 and 0.1 are almost the same, although the concentration distributions are different.

When a small amount of gelatin was added to sugar solutions, the drying rate decreased remarkably as the gelatin might form a thin film (skin) near the surface, and consequently the retention of ethanol increased.     

富氧燃烧技术在梭式窑中的应用

研究了富氧燃烧技术对梭式窑烧成的影响.研究结果表明,随着氧浓度从21%-30%的逐渐增加,CO总浓度和NO总浓度都先明显下降,后缓慢上升;节能效果在初始段较为明显,而后效果不明显;而实际烟气量与氧浓度成反比,与过剩空气系数成正比.     

海底管道系统失效故障树的建立及定性分析

受自然环境、管道腐蚀、第三方破坏及管理不善等因素的影响,海底管道系统在铺设及运行过程中常常会失效。文中以海底管道穿孔、凝管、断裂和设备故障等主要失效形式为顶事件建立了海底管道系统失效故障树,通过系统的定性分析得到了海底管道系统失效故障树的37个一阶最小割集,进而确定了影响海底管道系统失效的4项主要因素,并针对这些主要因素提出了相应的解决问题的措施。     

高温和低张应力引起的非平衡晶界偏聚动力学(Ⅱ)--实验结果的动力学模拟

以文献[1]建立的张应力引起的非平衡晶界偏聚动力学方程模拟了Shinoda T等的磷在钢中的应力时效实验结果和Misra R D K的硫在钢中的应力时效实验结果，模拟结果与实验结果互相吻合。通过模拟发现，张应力使磷-空位复合体以及硫-空位复合体在钢中的扩散系数均增加3个数量级，且磷原子和硫原子的扩散系数分别降低3个和5个数量级。     

S135钻杆钢在钻井液中的氧腐蚀行为

基于系统的理论分析和现场腐蚀产物的XRD分析,揭示了S135钻杆钢在3%NaCl溶液中的氧腐蚀机理。为研究腐蚀因素与腐蚀速率的关系,通过室内高压釜动态模拟实验,分别研究了钻井液中含氧量、钻井液温度、钻井液流速和钻井液盐浓度对S135钻杆钢的氧腐蚀速率影响规律。实验研究结果表明(1)3%NaCl盐水钻井液对S135钻杆钢的腐蚀主要是氧去极化作用所致;(2)钻井液含氧量和钻井液流速的增加会加快钻杆钢的氧腐蚀速率,而钻井液温度和含盐量对钻杆钢的氧腐蚀速率具有双重作用。     

Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests

The goal of this research was to compare narrowband hyperspectral Hyperion data with broadband hyperspatial IKONOS data and advanced multispectral Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data through modeling and classifying complex rainforest vegetation. For this purpose, Hyperion, ALI, IKONOS, and ETM+ data were acquired for southern Cameroon, a region considered to be a representative area for tropical moist evergreen and semi-deciduous forests. Field data, collected in near-real time to coincide with satellite sensor overpass, were used to (1) quantify and model the biomass of tree, shrub, and weed species; and (2) characterize forest land use/land cover (LULC) classes.The study established that even the most advanced broadband sensors (i.e., ETM+, IKONOS, and ALI) had serious limitations in modeling biomass and in classifying forest LULC classes. The broadband models explained only 13-60% of the variability in biomass across primary forests, secondary forests, and fallows. The overall accuracies were between 42% and 51% for classifying nine complex rainforest LULC classes using the broadband data of these sensors. Within individual vegetation types (e.g., primary or secondary forest), the overall accuracies increased slightly, but followed a similar trend. Among the broadband sensors, ALI sensor performed better than the IKONOS and ETM+ sensors.When compared to the three broadband sensors, Hyperion narrowband data produced (1) models that explained 36-83% more of the variability in rainforest biomass, and (2) LULC classifications with 45-52% higher overall accuracies. Twenty-three Hyperion narrowbands that were most sensitive in modeling forest biomass and in classifying forest LULC classes were identified and discussed.