响应面法优化胡敏素对Cu2+的吸附及机理研究

采用Box-Behnken响应面优化实验设计对胡敏素吸附去除水中Cu~(2+)的过程进行了优化,设定吸附时间、吸附剂用量、pH、温度和Cu~(2+)初始浓度为5个影响因素,Cu~(2+)吸附率为响应值,建立了吸附率与上述因素之间的二次多项式模型,确定最佳吸附条件,对吸附过程的等温模型及吸附机理进行了研究.响应面分析表明,吸附剂用量、pH和Cu~(2+)初始浓度是显著因素.胡敏素对Cu~(2+)吸附的最佳条件为:吸附时间110 min、吸附剂用量2.4 g·L~(-1)、pH=5.4、温度25.0℃、Cu~(2+)初始浓度208 mg·L~(-1).在该条件下,测得胡敏素对Cu~(2+)的吸附率可达到80.78%,吸附符合Langmuir等温线方程.胡敏素表面疏松多孔,有利于其通过物理吸附方式吸附Cu~(2+),同时,胡敏素表面的羟基、羧基和羰基等活性基团可以与Cu~(2+)发生配位络合作用,Na+、Ca~(2+)、Mg~(2+)等与Cu~(2+)发生离子交换作用,从而发生化学吸附.研究结果表明,胡敏素作为一种绿色、高效、廉价的吸附剂,可应用于Cu~(2+)污染废水的治理.     

基于两级拓扑优化的振动台扩展台面设计与试验验证

根据拓扑优化基本原理,利用OptiStruct进行振动台扩展台面的结构最优化设计,通过两级拓扑优化完成结构的拓扑寻优。首先利用整体级拓扑优化,找到结构的整体最佳构造。然后利用局部级拓扑优化,对局部结构进行拓扑寻优,最终完成产品的结构设计。试验结果与仿真结果对比表明,误差在5%以内,表明方法的有效性和实用性。     

遗传和模拟退火算法在水质模型参数确定中的应用简介

水质模型参数的确定是构建水质模型的基础。相对于传统优化方法,现代优化算法的优势日趋明显。本文在基于现代优化算法的水质模型参数确定研究背景下,介绍了具有代表性的遗传算法和模拟退火算法,并对该两种算法的应用现状进行综述,旨在推进该领域的进一步探索。     

APPLICATION OF ENHANCED ANNEALING TO GROUND WATER REMEDIATION DESIGN1

ABSTRACT: A methodology for ground water remediation design has been developed that interfaces ground water simulation models with an enhanced annealing optimizer. The ground water flow and transport simulators provide the ability to consider site‐specific contamination and geohydrologic conditions directly in the assessment of alternative remediation system designs. The optimizer facilitates analysis of tradeoffs between technical, environmental, regulatory, and financial risks for alternative design and operation scenarios. A ground water management model using an optimization method referred to as “enhanced annealing” (simulated annealing enhanced to include “directional search” and “memory” mechanisms) has been developed and successfully applied to an actual restoration problem. The demonstration site is the contaminated unconfined aquifer referred to as N‐Springs located at Han‐ford, Washington. Results of the demonstration show the potential for improving groundwater restoration system performance while reducing overall system cost.     

A COMPARISON OF STREAMFLOW GENERATION MODELS FOR RESERVOIR CAPACITY-YIELD ANALYSIS1

ABSTRACT: An analysis of four streamflow generation schemes for the use in the estimation of the required conservation storage for a single reservoir is presented. The comparison of the generating schemes should aid in the selection of an appropriate model type for the reservoir sizing problem. The streamflow generation models are compared using two criteria. The first comparison is between the statistics of the generated streamflow sequences and the corresponding statistics from the historical record. The second evaluation compares the median reservoir size determined by each model with the required storage based on the historical flow sequence. The results of a comparative analysis for monthly streamflow data for the Rzav River in Yugoslavia are presented and discussed. The results indicate that both evaluation criteria are required to discriminate between the various options.     

COMPARISON OF RESERVOIR LINEAR OPERATION RULES USING LINEAR AND DYNAMIC PROGRAMMING1

ABSTRACT: Mathematical optimization techniques are used to study the operation and design of a single, multi-purpose reservoir system. Optimal monthly release policies are derived for Hoover Reservoir, located in Central Ohio, using chance-constrained linear programming and dynamic programming-regression methodologies. Important characteristics of the former approach are derived, discussed, and graphically illustrated using Hoover Reservoir as a case example. Simulation procedures are used to examine and compare the overall performance of the optimal monthly reservoir release policies derived under the two approaches. Results indicate that, for the mean detention time and the corresponding safe yield target water supply release under existing design of Hoover Reservoir, the dynamic programming policies produce lower average annual losses (as defined by a two-sided quadratic loss function) while achieving at least as high reliability levels when compared to policies derived under the chance-constrained linear programming method. In making this comparison, the reservoir release policies, although not identical, are assumed to be linear. This restricted form of the release policy is necessary to make the chance-constrained programming method mathematically tractable.     

MODELS FOR WATER AND POWER SCHEDULING FOR THE CALIFORNIA STATE WATER PROJECT1

ABSTRACT: A large-scale simulation/optimization model provides schedules for operation of water and power for the California State Water Project (SWP). The SWP consists of a series of reservoirs linked by rivers, pumping plants, canals, tunnels, and generating plants and is operated by the California Department of Water Resources. The Department provides water to municipal and agricultural users, and manages its electrical loads and resources. The model, therefore, performs hydraulic and electrical computations leading to optimal operation of the entire system. It consists of hydraulic network programming components to meet the storage objectives at all the reservoirs, a linear programming component to determine the schedules at pumping and generating plants, an electrical network programming component to balance electrical loads and resources, and a number of other simulation components. It operates on yearly, weekly, and daily bases. It is primarily used for real-time operation of the SWP and can provide hourly detail schedules which are implemented by the SWP staff via a computerized system.     

APPROACHES TO WATER RESOURCE POLICY AND PLANNING IN TEXAS1

ABSTRACT: Texas is one of the states in which limitations in water supplies could severely constrain economic growth in certain areas. The traditional planning approach for addressing this problem has involved devising schemes for large water development projects, which for many years included the importation of water from other states. Now the attitude towards water resource management is changing, and it is generally agreed that better management of existing supplies is the preferred approach. In this paper we review some of the changes that have recently occurred in Texas, including attempts to streamline the water institutions in such a way that they might be more responsive to the need for more comprehensive management of water resources statewide, with greater emphasis on social and environmental concerns.     

DERIVING THE NONLINEAR RISK-BENEFIT ALGORITHM FOR RESERVOIRS1

ABSTRACT: The Nonlinear Risk-Benefit (NRB) Algorithm includes risk as one of the objectives in a multiple-objective optimization problem. The NRB Algorithm is derived by extending the Surrogate Worth Trade-Off method to quadratic programming. This category of problem is common in water resources planning and design, especially multipurpose reservoir systems. Consequently, an example is given using the algorithm for optimally operating a multipurpose reservoir.