高温条件下高速碰撞试验技术研究

目的建立高温条件下结构的高速碰撞试验技术。方法基于理论和试验方法,研究影响试样加热/保温、碰靶速度和姿态的关键因素,利用次口径发射技术和电炉技术实现试样的加热、保温和加速。采用间接方法测试试样碰靶时的温度,联合应用次口径发射技术和靶体,控制试样的碰靶姿态,并利用高速摄影技术对其进行测试。通过薄壁圆柱筒的高温高速碰靶验证高温试验技术的有效性。结果建立了加热、加速和姿态控制一体化的高温高速碰撞试验技术,获得了不同尺寸薄壁圆柱筒不同姿态碰靶时的高温冲击动力学响应。正碰时,撞击端镦粗,尾端收缩,尾端的凹陷大于碰撞端的变形;侧碰时,圆筒呈马鞍状;角碰时的变形为楔形。随着圆筒的强度和刚度的降低,圆筒的变形增加,整体发生坍塌,出现大量的皱褶。结论建立的试验技术切实有效,可以用于高温条件下结构高速碰撞效应的研究。     

Modeling photocatalytic destruction of the organic contaminants in continuous stir flow reactor

Thin-film technique is becoming an industry standard for the preparation of TiO₂-based photocatalyst for organic destruction. The catalyst provides several advantages over the conventional powder TiO₂ in the treatment of wastewater and groundwater. In this study, a continuous stir flow reactor model is developed capable of describing the photocatalytic process. The model incorporates the following fundamental mechanisms: adsorption, diffusion, liquid-film transfer, UV attenuation, and photocatalytic reaction. All of the simulation results indicate that there exists a highly nonlinear relation between each of these parameters and the destruction rate. Various incident light intensities also are incorporated to simulate the energy efficiency. The simulations illustrate that the photocatalytic model can be used to elucidate the effect of process variables. It is also possible to “custom-design” a catalyst for the treatment of a particular waste stream.     

熔池高度对双辊薄带凝固组织影响的模拟预测

在已建立的理论数学模型的基础上,以1Cr18Ni9Ti不锈钢为研究对象,模拟预测了薄带厚度保持不变条件下熔池高度对薄带凝固组织的影响。研究结果表明:随着熔池高度增加,1Cr18Ni9Ti不锈钢双辊薄带凝固组织中柱状晶区比例首先增大,然后又逐渐减小。而柱状枝晶取向度和枝晶间距则随着熔池高度的增加而增大,但在较低的熔池高度条件下,柱状枝晶间距在凝固结束时有突然增大的趋势。     

重庆市主城区空气污染成因分析及改善大气扩散条件的措施建议

盆地地形导致的城区内小以厚度大，强逆温层出现频率高等大气不利扩散条件是造成重庆市主城区空气污染的重要原因，建议城市布局要符合空气动力学原理并通过工程措施改善城区大气扩散条件。     

A Conceptual Framework for Selecting and Analyzing Stressor Data to Study Species Richness at Large Spatial Scales

/ In this paper we develop a conceptual framework for selectingstressor data and analyzing their relationship to geographic patterns ofspecies richness at large spatial scales. Aspects of climate and topography,which are not stressors per se, have been most strongly linked withgeographic patterns of species richness at large spatial scales (e.g.,continental to global scales). The adverse impact of stressors (e.g., habitatloss, pollution) on species has been demonstrated primarily on much smallerspatial scales. To date, there has been a lack of conceptual developmenton how to use stressor data to study geographic patterns of speciesrichness at large spatial scales.The framework we developed includes four components: (1) clarification of theterms stress and stressor and categorization of factors affecting speciesrichness into three groups-anthropogenic stressors, natural stressors, andnatural covariates; (2) synthesis of the existing hypotheses for explaininggeographic patterns of species richness to identify the scales over whichstressors and natural covariates influence species richness and to providesupporting evidence for these relationships through review of previousstudies; (3) identification of three criteria for selection of stressor andcovariate data sets: (a) inclusion of data sets from each of the threecategories identified in item 1, (b) inclusion of data sets representingdifferent aspects of each category, and (c) to the extent possible, analysisof data quality; and (4) identification of two approaches for examiningscale-dependent relationships among stressors, covariates, and patterns ofspecies richness-scaling-up and regression-tree analyses.Based on this framework, we propose 10 data sets as a minimum data base forexamining the effects of stressors and covariates on species richness atlarge spatial scales. These data sets include land cover, roads, wetlands(numbers and loss), exotic species, livestock grazing, surface water pH,pesticide application, climate (and weather), topography, and streams.KEY WORDS: Anthropogenic impacts; Biodiversity; Environmental gradients;Geographic information systems; Hierarchy     

308 nm光作用下α-Fe2O3表面HNO3的光解

采用紫外可见光谱(UV-Vis)、傅立叶变换红外光谱(FTIR)及离子色谱(IC)技术对HNO3在α-Fe2O3表面暗反应和308nm下光解反应进行了研究.考察了时间、HNO3浓度、相对湿度(RH)等条件对反应的影响.结果表明,随着HNO3浓度、光照时间的增加,HNO3在气相与α-Fe2O3表面光解产物浓度均呈指数增加;HNO3在α-Fe2O3表面光解产生的NO2、NO分别为气相产生的3.27及3.87倍,而无论气相还是表面光解的NO2浓度均约为NO的2倍.随着RH的增加,HNO3光解产生的HONO的浓度随之呈指数增大,其产率从RH 20%时的0.023增加到90%时的0.087.α-Fe2O3的表面效应在HNO3的表面光解反应中起主导作用.     

V_2O_5-TiO_2离子存储电极薄膜的溶胶-凝胶法制备与性能研究

利用无机溶胶-凝胶技术制备了V2O5-（TiO2）x离子存储电极薄膜。采用X射线衍射（XRD）、原子力显微镜（AFM）、Raman光谱、循环伏安法（CV）和紫外-可见光透射光谱分别研究了复合薄膜的微观结构、化学计量、锂离子注入性能以及光学性能。结果表明复合薄膜具有V2O5的层状结构,其c轴方向的结构取向性有所降低;颗粒尺寸和表面粗糙度显著减小;同时TiO2的复合导致薄膜中V2O5的化学计量发生偏移,氧空位数量增多。当x=0.2时,薄膜具有相对较高的离子存储容量及循环稳定性,并且在离子注入/脱出状态均获得相当高的可见光透过性。     

Diffusive gradients in thin films using molecularly imprinted polymer binding gels for in situ measurements of antibiotics in urban wastewaters

• Selective molecularly imprinted polymer (MIP) binding gel was prepared. • MIP-DGT showed excellent uptake performance for antibiotics. • In situ measurement of antibiotics in wastewaters via MIP-DGT was developed. • The MIP-DGT method was robust, reliable, and highly sensitive. Urban wastewater is one of main sources for the introduction of antibiotics into the environment. Monitoring the concentrations of antibiotics in wastewater is necessary for estimating the amount of antibiotics discharged into the environment through urban wastewater treatment systems. In this study, we report a novel diffusive gradient in thin films (DGT) method based on molecularly imprinted polymers (MIPs) for in situ measurement of two typical antibiotics, fluoroquinolones (FQs) and sulfonamides (SAs) in urban wastewater. MIPs show specific adsorption toward their templates and their structural analogs, resulting in the selective uptake of the two target antibiotics during MIP-DGT deployment. The uptake performance of the MIP-DGTs was evaluated in the laboratory and was relatively independent of solution pH (4.0–9.0), ionic strength (1–750 mmol/L), and dissolved organic matter (DOM, 0–20 mg/L). MIP-DGT samplers were tested in the effluent of an urban wastewater treatment plant for field trials, where three SA (sulfamethoxazole, sulfapyridine, and trimethoprim) and one FQ (ofloxacin) antibiotics were detected, with concentrations ranging from 25.50 to 117.58 ng/L, which are consistent with the results measured by grab sampling. The total removal efficiency of the antibiotics was 80.1% by the treatment plant. This study demonstrates that MIP-DGT is an effective tool for in situ monitoring of trace antibiotics in complex urban wastewaters.     

Fe3+掺杂TiO2薄膜的制备及光催化降解甲醛的研究

采用溶胶-凝胶法制备Fe3+掺杂的TiO2薄膜光催化剂,进行甲醛的光催化实验,考察Fe3+掺杂量、薄膜焙烧温度及溶胶体系pH值对光催化性能的影响。结果表明,Fe3+掺杂量为1.0%,焙烧温度500℃1h,加硝酸溶胶体系pH=4时,Fe3+掺杂TiO2薄膜光催化活性最高。     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.