吊水壶尾矿坝渗流特性三维有限元分析

本文结合工程实例,以吊水壶尾矿坝为背景,建立现状尾矿坝三维模型,利用三维有限元法反演分析现状尾矿坝的渗流场,将计算结果与勘察的浸润面对比分析,验证模型的可靠性和合理性。基于此模型建立加高后的尾矿坝三维模型,计算正常蓄水位和设计洪水位两种工况下的渗流场,分析坝体浸润面埋深、滩长、渗流坡降等,结果表明,不设排渗措施时,尾矿坝干滩长度、浸润面埋深均能满足规范要求,而且尖流性态良好,满足渗透稳定。提出该尾矿坎可通过加高工程来进行渗流控制的建议。     

基于最佳范化能力的BP网络隐节点数反比关系式的环境预测模型

网络结构和样本集复杂性是影响BP网络泛化能力的两个最重要因素.对一个给定的训练样本集,为了构造一个与样本集复杂性相匹配的网络结构,使BP网络具有最佳泛化能力,在分析BP网络的泛化能力（用检测误差E₂表示）与网络结构和样本集复杂性之间关系的基础上,建立了含参数的BP网络检测误差E₂与网络隐节点数H、样本的因子数n、样本数N和样本集的复相关系数R之间的一般关系表达式,并提出了用于定量描述样本集复杂性的"广义"复相关系数R_n的新概念.借助于222个复杂函数的模拟仿真实验,应用免疫进化算法,对表达式中的参数进行优化,得到参数优化后的网络检测误差E₂的定量解析表达式;依据误差理论和灵敏度概念,对优化得到的最小检测误差E₂₀的表达式进行了可靠性论证.在此基础上导出了具有最佳泛化能力的BP网络隐节点数H₀与"广义"复相关系数R_n之间满足的H₀-R_n反比关系式.分别用满足H₀-R_n反比关系式的隐节点数和6个经验公式的隐节点数构造的BP网络用于100个模拟检测函数进行仿真实验,发现前者构造的BP网络具有最佳泛化能力（即最小检测误差）的函数个数达到76个,远远多于后者构造的BP网络具有最佳泛化能力的函数个数;还将二者构造的BP网络用于环境预测的7个具体实例,进行预测效果比较,结果表明,前者预测的相对误差绝对值的平均值和最大值小于或远小于后者的相应值.从而验证了由H₀-R_n反比关系式得出的BP网络隐节点数计算公式的可行性和实用性,为具有最佳泛化能力的BP网络的结构设计指出了新途径.     

Do microbial processes regulate the stability of a coral atoll's enclosed pelagic ecosystem?

Complex marine ecosystems contain multiple feedback cycles that can cause unexpected responses to perturbations. To better predict these responses, complicated models are increasingly being developed to enable the study of feedback cycles. However, the sparseness of ecological data often limits the direct empirical parameterization of all model parameters. Here we use a Bayesian inverse analysis approach to synthesize empirical data and ecological theory derived from published studies of a coral atoll's enclosed pelagic ecosystem (Takapoto Atoll, French Polynesia). We then use the estimates of flux magnitudes to parameterize probabilistic compartment models with two forms of heterotrophic consumption: (1) “bottom-up” donor-controlled heterotrophic consumption and (2) “top-down” mass-action heterotrophic consumption. We explore how the flux magnitudes affect the ecosystem's stability properties of resilience, reactivity, and resistance under both assumptions for heterotrophic consumption. The models suggest that the microbial uptake of dissolved organic carbon (DOC) regulates the long term rate of return to steady state following a temporary or pulse perturbation (resilience), and the cycling of carbon between abiotic pools and heterotrophic compartments regulates the short-term response (reactivity). In the bottom-up process model, the sensitivity of steady state masses following a sustained or press perturbation (resistance) is highest for the DOC pool following a sustained change to the microbial uptake rate of DOC. Further, a change in the microbial uptake of DOC propagates through the ecosystem and affects the steady state values of zooplankton. The analysis suggests that the food web is highly dependent on the recycling between the abiotic and biotic carbon pools, particularly as mediated by the microbial consumption of DOC, and this recycling determines how the ecosystem responds to perturbations.     

非离子型聚丙烯酰胺絮凝剂的制备及其絮凝性能

以丙烯酰胺（AM）和烷基酚聚醚（APAP）为单体,采用反相乳液聚合法制备了流动性好的非离子型聚丙烯酰胺絮凝剂（PAM-APAP）。考察了乳化剂和引发剂的种类、单体总质量分数、单体配比和反应温度等因素对聚合反应的影响。实验结果表明,制备PAM-APAP的最佳工艺条件为：单体总质量分数35%、m（AM）∶m（APAP）=9.0∶1.0、Span80+Tween80复配乳化剂加入量为油水总质量的7%、m（Span80）∶m（Tween80）=7.0∶1.5、V50加入量为单体总质量的1.5‰、反应温度50℃。PAM-APAP具有较好的絮凝效果,与其他絮凝剂相比用量较少,在加入量为100mg/L时,对聚合物驱油中产生的含聚合物污水的浊度去除率为87.9%,去油率为89.5%,且絮体不黏壁。     

Optimization-Based Atmospheric Plume Source Identification

This work applies optimization and an Eulerian inversion approach presented by Bagtzoglou and Baun in 2005 in order to reconstruct contaminant plume time histories and to identify the likely source of atmospheric contamination using data from a real test site for the first time. Present-day distribution of an atmospheric contaminant plume as well as data points reflecting the plume history allow the reconstruction and provide the plume velocity, distribution, and probable source. The method was tested to a hypothetical case and with data from the Forest Atmosphere Transfer and Storage (FACTS) experiment in the Duke experimental forest site. In the scenarios presented herein, as well as in numerous cases tested for verification purposes, the model conserved mass, successfully located the peak of the plume, and managed to capture the motion of the plume well but underestimated the contaminant peak.     

Inverse modeling of Asian Rn flux using surface air Rn concentration

When used with an atmospheric transport model, the ²²²Rn flux distribution estimated in our previous study using soil transport theory caused underestimation of atmospheric ²²²Rn concentrations as compared with measurements in East Asia. In this study, we applied a Bayesian synthesis inverse method to produce revised estimates of the annual ²²²Rn flux density in Asia by using atmospheric ²²²Rn concentrations measured at seven sites in East Asia. The Bayesian synthesis inverse method requires a prior estimate of the flux distribution and its uncertainties. The atmospheric transport model MM5/HIRAT and our previous estimate of the ²²²Rn flux distribution as the prior value were used to generate new flux estimates for the eastern half of the Eurasian continent dividing into 10 regions.The ²²²Rn flux densities estimated using the Bayesian inversion technique were generally higher than the prior flux densities. The area-weighted average ²²²Rn flux density for Asia was estimated to be 33.0 mBq m⁻² s⁻¹, which is substantially higher than the prior value (16.7 mBq m⁻² s⁻¹). The estimated ²²²Rn flux densities decrease with increasing latitude as follows: Southeast Asia (36.7 mBq m⁻² s⁻¹); East Asia (28.6 mBq m⁻² s⁻¹) including China, Korean Peninsula and Japan; and Siberia (14.1 mBq m⁻² s⁻¹). Increase of the newly estimated fluxes in Southeast Asia, China, Japan, and the southern part of Eastern Siberia from the prior ones contributed most significantly to improved agreement of the model-calculated concentrations with the atmospheric measurements. The sensitivity analysis of prior flux errors and effects of locally exhaled ²²²Rn showed that the estimated fluxes in Northern and Central China, Korea, Japan, and the southern part of Eastern Siberia were robust, but that in Central Asia had a large uncertainty.     

淀粉-g-丙烯酸/凹凸棒土复合物制备及其吸附废水中NH_4~＋-N性能

采用反相乳液聚合法以凹凸棒土为原料,合成了新型NH4＋-N吸附剂淀粉-g-丙烯酸/凹凸棒土,并进行了氨氮吸附对比实验。结果表明：凹凸棒土氨氮单位吸附量为4.243 mg/g;淀粉-g-丙烯酸/凹凸棒土氨氮单位吸附量为5.301 mg/g,吸附能力比未改性的凹凸棒土提高了25%。淀粉-g-丙烯酸/凹凸棒土的氨氮吸附过程比凹凸棒土更符合Freundlich等温吸附模型。随着pH、温度的升高,凹凸棒土和淀粉-g-丙烯酸/凹凸棒土对NH4＋-N吸附量逐渐增大。     

反相气相色谱法研究CPC-膨润土对VOCs的吸附作用

运用反相气相色谱法研究了20种VOCs在CPC-膨润土上的吸附平衡及吸附热．结果表明，CPC-膨润土对VOCs的吸附有较强选择性，吸附能力与有机物的分子量、分子结构、饱和蒸气压等物理化学性质有关，对苯系物和分子量较大的酯类和酮类等吸附能力较强．温度较低时，CPC-膨润土对VOCs的吸附能力较强，吸附热较大；吸附热与VOCs的沸点蒸发热相当，但比活性炭等常规吸附剂对VOCs的吸附热小。     

基于模拟-优化方法的地下水污染源溯源辨识

以抚顺市某煤矸石堆放场为研究区,根据研究区的实际条件建立地下水污染质运移模拟模型,预测地下水污染质未来时空变化特征.基于正演预报结果构建了假想例子,应用模拟-优化方法对地下水污染源源强及场地的渗透系数进行反演识别.为减小优化模型反复调用模拟模型所产生的计算负荷,分别采用Kriging方法和BP神经网络方法建立了模拟模型的替代模型.最后运用模拟退火法求解优化模型,得到反演识别结果.研究表明：应用Kriging方法建立的替代模型输出结果的平均相对误差为0.3%;应用BP神经网络方法建立替代模型的输出结果平均相对误差为1.5%,应用两种替代模型对污染源源强识别的相对误差均小于0.5%,对场地两个参数分区渗透系数识别的相对误差均不大于5%.综上,应用Kriging方法建立的替代模型精度高于BP神经网络方法,利用基于两种替代模型的模拟-优化方法对污染源源强和渗透系数进行同步识别精度可以满足实际需求,是有效可行的.     

MODELING GROUND WATER FLOW USING FLUX BOUNDARY CONDITIONS1

ABSTRACT: Determination of the boundary conditions for modeling ground water flow is a critical point especially in regional models. Normally the regional models require model areas that are greater than the given area of interest. This work focuses on the prediction of hydraulic heads in regional models using flux boundary conditions. The model uses flux boundary conditions that were estimated using a radial flow analog and Darcy's law. The regional model that is presented uses no parameter identification (inverse estimation) procedures. In the present work, the Houston area was used. The simulation of the hydrological conditions of the Chicot and Evangeline Aquifers that underlie the Houston area were made using the available information about the geological profile in the Houston region and the current information about the existing production wells. The regional model works as a forward problem. The system parameters such as hydraulic conductivity, specific storage, and hydrological stresses were specified, and the model predicts the hydraulic head. Actual data from piezometers operated by the U.S. Geological Survey (USGS) in many places throughout Houston were used as initial conditions. Some piezometric head data were generated using the regional variable theory called kriging to supply head estimates in areas where data were unavailable. The Modular Three Dimensional Finite Difference Groundwater Flow Model developed by the USGS was used to predict the hydraulic heads. The predicted ground water heads are compared to the actual data. The results show that the model performs well for locations where data were available.