生物转盘动力学分析与数学模式探讨

通过对生产性四级生物转 盘进出水中主要污染指标及生物膜特性指标的分析测定，进行了ＢＯＤ５、ＣＯＤ和挥发酚等污染指标在转盘系统中的降解反应动力学分析，确定了上述污染指标的降解反应级数、反应速率常数及动力８学方程式，为寻求能够揭示转盘净化反应实质及其影响因素且简便实用的设计计算公式，根据物料平衡原理和莫诺（Ｍｏｎｏｄ）关系式推导出了能够揭示转 盘净化反应实质及其影响因素且简便实用的设计计算公式，根据关     

GEOLOGIC INFERENCE FROM “FLOW NET” TRANSMISSIVITY DETERMINATION: THREE CASE STUDIES1

A graphical inverse method for determining the regional transmissivity distribution was applied to three field problems. The study areas were the Hanford Site, Washington; the Rocky Mountain Arsenal, Colorado; and the Nevada Test Site, Nevada. This method can aid in flow system conceptualization by revealing the location of bedrock controls for groundwater flow. It is a valuable tool for aiding the hydrogeologist in asking questions about the nature of trends in the pattern of transmissivity values. Quantitative estimates of regional transmissivities can be used as starting points for further parameter refinement. Sensitivity analysis using Monte Carlo simulation shows that quantitative estimates of transmissivity can be obtained when measurement error in the hydraulic head does not cause a large error in the hydraulic gradient.     

PARAMETRIC ESTIMATION OF COVARIANCES OF REGIONALIZED VARIABLES1

ABSTRACT: The usefulness of stochastic models in describing the spatial variability of hydrogeologic quantities, such as permeability, storativity, piezometric head, seepage velocity, and solute concentrations is now widely recognized. In practice, these quantities are represented as the sum of a well-structured component, or drift, and a more erratic fluctuation component which is described statistically through its covariance function. This paper reviews some of the most recent and most promising methods for the estimation of parameters of these covariances from existing data. They are maximum likelihood, restricted maximum likelihood, minimum-variance unbiased quadratic estimation, and minimum-norm (weighted least squares) estimation. The applicability of such methods to conditional and unconditional probability problems is discussed.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.     

An Analysis of the Wind Energy Potential of Elazig,Turkey

Abstract

In this study, the wind energy potential of Elazig is statistically analyzed based on hourly measured wind speed data over the five-year period from 1998 to 2002. The probability density distributions are derived from cumulative distribution functions. Two probability density functions are fitted to the measured probability distribution on a yearly basis. The wind energy potential of the location is studied based on the Weibull and Rayleigh distributions. It was found that the numerical values of both Weibull parameters (k and c) for Elazig vary over a wide range. The yearly values of k range from 1.653 to 1.878 with an average value of 1.819, while those of c are in the range of 2.757–2.994 m/s with an average value of 2.824 m/s. In addition, yearly mean wind speed and mean power density of Elazig is found as 2.79 m/s and 38.76 W/m², respectively. The wind speed distributions are represented by Weibull distribution and also by Rayleigh distribution, with a special case of the Weibull distribution for k = 2. As a result, the Rayleigh distribution is found to be suitable to represent the actual probability of wind speed data for Elazig.     

时变参数模型用于滑坡位移量预测的研究

滑坡的位移量发展受地质条件、气候环境以及人类活动等多种因素的影响,变化复杂,通常难以用固定参数的数学模型准确表达。时变参数模型的模型参数随时间变化,能够描述更为复杂的函数关系。将时变参数模型应用于滑坡位移量预测,通过对比发现,时变参数模型有望提高滑坡位移量的预测精度。     

城郊排水沟渠溶质传输的暂态存储影响及参数灵敏性

选择Na Cl为示踪剂,于2013年9~10月在合肥城郊的关镇河支渠开展5次瞬时投加示踪实验.从暂态存储、侧向补给和对流-扩散等作用机制层面,设置4种模拟情景,解析暂态存储作用对于排水沟渠溶质传输规律的影响,并对OTIS模型参数进行灵敏性分析.结果表明,暂态存储对于主流区Cl-模拟浓度穿透曲线(BTCs)峰值大小影响很大,相对偏差高达24.23%~117.26%,显著高于对峰值出现时间的影响,且暂态存储影响显著超过了侧向补给作用;由相关性分析,主流区Cl-模拟浓度BTCs峰值大小和出现时间的相对偏差与As/A具有极显著相关性;4个主要参数的灵敏度排序为AAsαD.     

防空导弹的综合环境可靠性试验剖面研究

为有效地进行防空导弹综合环境可靠性试验,根据试验剖面的模拟真实性、应力适当性和试验可操作性的要求,确定以防空导弹随战车值勤和空中飞行为主要试验阶段。主要研究了地面和空中2种试验环境中温度应力、湿度、振动应力和电应力等环境参数的确定,并给出了相应的原则或计算公式。最后讨论了如何确定试验时间的问题,并绘出了综合环境可靠性试验剖面图。     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.