GROUND WATER SOLUTE TRANSPORT,OPTIMAL REMEDIATION PLANNING,AND DECISION MAKING UNDER UNCERTAINTY1

ABSTRACT: A groundwater quality modeling advisory system has been developed for the U.S. Air Force for use in investigating remediation alternatives for the cleanup of subsurface contamination. The system is capable of accounting for uncertainty, not only in the prediction of solute transport but also in the optimization of the remediation scheme through chance constraints. The system guides users in the selection of appropriate transport models through an algorithm independently tested with machine learning codes. An application to Hill Air Force Base, Utah, is presented for which different pump-and-treat strategies are considered: the results are evaluated in terms of the cumulative distribution of the contaminant concentration for each case and the tradeoff relationship between the cost of remediation and the probability that the remediation strategy exceeds an established maximum allowable contaminant concentration.     

DECISION SUPPORT SYSTEM FOR RESERVOIR OPERATION1

ABSTRACT: A decision support system to determine reservoir releases in an uncertain environment during the dry season was developed. A key characteristic of the decision support system is its recursive procedure that processes observations to obtain the most feasible estimate. The system consists of three components: (1) a hydrologic model; (2) an optimization model, and (3) a fuzzy decision model. This methodology was applied to the operation of the Techi reservoir in central Taiwan. Three criteria (public water supply, irrigation, and hydropower) were taken into account within the operation process. Simulation results show that the decision support system can successfully assist government officials in determining operating policy for the Techi reservoir during the dry season. Also, the system is simple enough to lead to a rapid transfer of theoretical knowledge into practice.     

QUANTIFICATION FOR VISUALIZATION OF TIME TREND1

ABSTRACT: A method for quantifying fluctuations in time-series data was developed and tested to aid the process of visualization. The methodology is based on free-form sliding polynomials and identifies (a) short-period variability about the mean value, (b) a long-term trend or cycle, and (c) random errors residual to these two structured components. Consistent results were obtained for designed synthetic data and natural data from seven sites in Georgia. Statistics of fit of the analytical model for the natural data were not significant on a site-by-site basis. An unexpected finding for the study was obtained when the statistical results for the seven data sets for temperature were pooled. The smoothing model yielded consistent long-term trends even though the individual station results were not significant. Also, the correlation coefficients, while low, showed a statistically significant trend toward higher values toward the northwest and away from the Georgia coast line. This study thus supports the concept that multiple-site, and regionally based, analyses are necessary for the detection of trends. Secondarily, such consistency of results strengthens the conclusion that the proposed smoothing method is an effective procedure in the presence of varying amounts of random content in the natural data sets.     

基于COMSOL的采空区埋管抽采参数优化数值研究

针对回采工作面上隅角瓦斯浓度超限问题,提出了回采工作面采空区埋管抽采的方法。以保德煤矿81307工作面为研究对象,运用数值模拟软件COMSOL模拟采空区无抽采和不同抽采参数条件下工作面内瓦斯分布规律,研究埋管抽采参数对上隅角瓦斯浓度的影响规律,确定最佳的采空区埋管抽采参数。同时进行现场抽采参数优化试验,对瓦斯浓度进行监测,研究结果表明:合适的布置间距、抽采负压和抽采流量能够有效解决上隅角瓦斯超限问题,试验期间内,上隅角瓦斯体积分数最大为0.74%,进风流中瓦斯体积分数最大为0.2%,工作面风流中瓦斯体积分数最大为0.45%,回风流中瓦斯体积分数最大为0.5%,均没有超过安全标准。     

基于元胞自动机的复杂建筑物中人员逃生模型研究

针对复杂建筑物中人群安全疏散问题,在原有的元胞自动机行人流模型基础上,利用不同人员行进速度、不同方向行进速度的差异以及疏散连续性等特征优化该模型,使其在模拟逃生规律和疏散时间方面更加合理、可靠。通过多组人群行进速度测定试验,利用曲线拟合方法,获取不同属性人群向不同高度的台阶行进的速度,并制定台阶等级划分规则,优化人员速度计算方法,结合累积位移量,构建复杂建筑元胞自动机模型。利用Matlab软件建立原有疏散模型及复杂建筑元胞自动机模型,分别模拟某海豚表演馆疏散情况。结果表明,复杂建筑元胞自动机模型的模拟数据与实际演习数据相比,在疏散总时间方面存在5%~8%相对偏差,相比原有疏散模型,在模拟复杂建筑疏散问题中更具说服力。     

不确定条件下的区域能源-大气系统优化模型

以北京市丰台区能源-大气系统为实际案例,结合区间机会约束规划方法,以区间参数和随机参数反映系统的不确定信息,以能源系统总成本最小化为目标函数,以能源供需、热电生产、新能源消费、大气污染物排放等为主要约束条件,建立了区域能源-大气优化模型。通过交互式算法,确定了不同风险水平下的优化方案。研究结果表明:丰台区将建立以天然气为主要能源载体,燃气发电供热为主,新能源发电供热为补充的多元化能源系统。     

关于总量减排未来发展方向的探讨——以济南市COD减排优化为例

自“十一五”实行总量减排以来,国家和地方均投入了大量资金,用于治理工程的建设,减排效果显著.如何在保证经济社会发展的前提下,实现COD等污染的进一步减排,也是一个丞待研究的课题.然而在各类污染物产排量因经济社会发展而急剧增加的背景下,想要彻底解决环境污染问题,仅依靠工程减排措施恐难以为继.以2014年-2030年济南市COD减排优化研究为例,探讨了未来总量减排的发展方向,并在此基础上,提出未来总量减排的建议.     

大型空间桁架天线振动控制及作动器位置优化

目的对在轨大型空间柔性桁架天线结构振动进行主动控制及作动器位置优化。方法采用线性二次型最优控制算法对天线结构进行振动抑制,以系统能量和控制能量的和作为优化性能指标,利用遗传算法对作动器的位置进行优化。结果在优化配置的两个作动器控制作用下,受到激扰的天线结构振动便在10 s内得到良好得抑制,振动幅值减小了一个量级。结论适当地增加作动器数目,恰当地配置作动器的位置能有效抑制柔性天线结构的振动。     

Stormwater Control Measures for Runoff and Water Quality Management in Urban Landscapes

This study develops and tests a novel optimization method for optimally selecting and sizing stormwater control measures (SCMs) in urban landscapes for selected design storms. The developed methodology yields SCMs that capture and retain stormwater via onsite percolation, remove stormwater pollutants, and minimize stormwater control expenditures. The resulting environmental optimization problem involves integer and real variables imbedded in an objective function that is subjected to multiple constraints. This study's methodology aims at practicality and ease of implementation in the solution of the SCM sizing and selection optimization problem while taking into account the main factors that govern stormwater management in urban landscapes. The near‐optimal global solution of the SCM selection and design problem is obtained with nonlinear programming and verified with the average of multiple solutions calculated with multiple runs of an optimization evolutionary algorithm. The developed methodology is illustrated with one stormwater project in the City of Los Angeles, California.     

Prioritizing Stream Barrier Removal to Maximize Connected Aquatic Habitat and Minimize Water Scarcity

Instream barriers, such as dams, culverts, and diversions, alter hydrologic processes and aquatic habitat. Removing uneconomical and aging instream barriers is increasingly used for river restoration. Historically, selection of barrier removal projects used score‐and‐rank techniques, ignoring cumulative change and the spatial structure of stream networks. Likewise, most water supply models prioritize either human water uses or aquatic habitat, failing to incorporate both human and environmental water use benefits. Here, a dual‐objective optimization model identifies barriers to remove that maximize connected aquatic habitat and minimize water scarcity. Aquatic habitat is measured using monthly average streamflow, temperature, channel gradient, and geomorphic condition as indicators of aquatic habitat suitability. Water scarcity costs are minimized using economic penalty functions while a budget constraint specifies the money available to remove barriers. We demonstrate the approach using a case study in Utah's Weber Basin to prioritize removal of instream barriers for Bonneville cutthroat trout, while maintaining human water uses. Removing 54 instream barriers reconnects about 160 km of quality‐weighted habitat and costs approximately US$10 M. After this point, the cost‐effectiveness of removing barriers to connect river habitat decreases. The modeling approach expands barrier removal optimization methods by explicitly including both economic and environmental water uses.