Global factors shaping the future of food aid: the implications for WFP

Food aid is a key component of a humanitarian response but its use in other programming contexts is subject to numerous criticisms. Even in humanitarian emergencies food aid is often late, unreliable and out of proportion to other elements of the response. Three major factors will shape the future of food aid. First, mechanisms of food aid governance are being reviewed and may undergo major changes—particularly the Food Aid Convention now that hopes have diminished for an Agreement on Agriculture at the World Trade Organisation. The second significant factor is donor agency trends. Overall levels of food aid have dropped fairly steadily in recent decades and there are several discernible trends in resource allocation, procurement and the use of food aid. The third factor is an emerging body of best practice that will define acceptable standards of food aid programming in the future.     

最大剪切模量对土动力参数及地震反应的影响

最大剪切模量是影响土的动剪切模量比、阻尼比和土层地震反应的最重要参数之一。通常采用室内应变法来确定最大剪切模量，给出土的动剪切模量比和阻尼比，而采用现场剪切波速法求得的结果则很少见。研究了剪切波速法和应变法所确定的最大剪切模量对土动剪切模量比、阻尼比和土层地震反应的影响，推导了两种方法所确定的动剪切模量比和阻尼比之间的关系式。结果表明：最大动剪切模量对土的动剪切模量比、阻尼比和土层地震反应的影响很显著。     

重大危险源动态监管与应急救援平台建设研究

由于缺乏相关的国家及行业标准规范,各地重大危险源监管与应急救援平台建设中主要存在如下问题:其一,只重视硬件建设,而忽视软件和信息建设;其二,重大危险源安全监管数据采集标准不统一,采用的相关软件和硬件技术不规范,难以在各级平台间实现数据共享。笔者参照重大危险源4级监管与应急救援体系,将国家科技攻关课题的相关研究成果同安全生产工作的实际需要有机地结合,提出重大危险源动态监管和事故应急救援平台建设方案。分析我国重大危险源监管及应急救援系统的建设现状及存在的主要问题;提出平台的设计原则、实现数据共享的主要思路;设计软件系统总体规划及各部分的功能。     

多因素耦合条件下硫化矿自燃神经网络动态预测模型研究

硫化矿石自燃是多种因素、多场耦合综合作用的结果,是一典型的非线性问题。笔者应用人工神经网络技术,以Matlab软件为平台,通过现场调查和理论分析,建立了矿石含硫量、通风强度、环境温度3因素与硫化矿石自燃之间的预测模型;通过数据样本学习与部分现场监测数据相结合进行模拟,研究表明预测数据与实测结果基本吻合,误差控制在10%以内,取得了较好的效果。该研究为预防硫化矿石自燃提供一个新的思路和方法,具有一定的理论意义和应用价值。     

Water Network Synthesis Using Mutation-Enhanced Particle Swarm Optimization

Different techniques for the synthesis of industrial water reuse/recycle networks have been developed in recent process integration research. These tools range from graphical pinch analysis approaches to mathematical programming models. The latter have the advantage of being flexible enough to incorporate various water network constraints, but in many cases these are often non-linear, thus making the identification of global optima difficult. Recent work has demonstrated the effectiveness of metaheuristic algorithms such as particle swarm optimization (PSO), for finding good solutions these problems. This work describes the use of a modified PSO for solving mixed integer non-linear programming (MINLP) models for water network synthesis. By incorporating a mutation operator for the binary variables in the model, the algorithm is able to escape sub-optimal network topologies and proceed towards better solutions than can be found with ordinary PSO. Two case studies involving water recycle/reuse are used to demonstrate the new design methodology.     

Integrated model for renewable energy planning in Turkey

All economic sectors are associated with energy use; therefore, government organizations aim to supply sustainable energy for human needs and economic growth. In particular, increased environmental concerns of the public in Turkey have impacted policymaking for renewable energy (RE) management in Turkey. The primary objective for RE sources of the Turkish Ministry of Energy is to ensure that 30% of the share of electricity production is from RE resources in 2023. In this paper, the integrated multi-objective, multi-period linear programming model is presented to determine effective allocation of RE supply for seven different geographical regions in Turkey for the period of 2017 to 2024. The integrated model consists of two different stages. The first stage involves qualitative evaluations of RE sources for seven geographical regions. Analytical Hierarchy Process (AHP) is applied to determine criteria priorities and overall ratings of geographical regions across determined criteria for RE sources are computed. The second stage of the integrated model consists of a multi-objective, multi-period linear programming model. The proposed multi-objective linear programming model is coded in MPL (Mathematical Programming Language) and solved using the GUROBI 5.1.0 solver. The output of the integrated model presents the total supply amount of RE sources for geographical regions in planning period. The ε-constraints method is applied to compute the total supply amount of RE from geographical regions for the period of 2017 to 2024. In this study, a systematic decision-making model is generated to allocate renewable energy sources to the geographical regions. The presented model integrates qualitative evaluations and quantitative parameters of different geographical regions to determine the optimal supply amount of RE. The obtained results are consistent with the potential quantities of RE alternatives in geographical regions, regional specifications, and social requirements.     

A MULTIOBJECTIVE MODEL FOR REGIONAL WATER QUALITY MANAGEMENT1

ABSTRACT: Linear programming is the simplest of all the optimization techniques used in regional water quality management studies; but the technique can optimize only one goal. When there are multiple goals with the same or different priorities, goal programming is a useful decisionmaking tool. This paper illustrates the application of goal programming to a regional water quality management problem where the following two goals are considered: (1) minimize the total cost of waste treatment, and (2) maintain the water quality goals (dissolved oxygen) close to the minimum level stated in the stream standards.     

MANY RESOURCES,MANY USES: A SYSTEM ANALYSIS APPROACH TO RENEWABLE RESOURCE DEVELOPMENT1

ABSTRACT: Decisionmaking associated with the Nation's 1.7 billion acres of forest and range land has become increasingly complicated because of the rise in competition for resource use and in the awareness of environmental and social effects. This system analysis approach uses four models to synthesize pertinent masses of information into measures of economic, environmental, and social impacts. The system results can be used to help evaluate alternative national programs. The models are:

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OPTIMAL RESERVOIR MANAGEMENT AND CROP PLANNING UNDER DETERMINISTIC AND STOCHASTIC INFLOWS1

ABSTRACT: This study analyzes planning under deterministic and stochastic inflows for the Mayurakshi project in India. Models are developed to indicate the optimal storage of reservoir water, the transfer of water to the producing regions, and the spillage of water from the reservoir, if needed. A deterministic programming model was first formulated to represent the existing situation. A chance-constrained model then was constructed to evaluate potential violations of the deterministic model. Both models were quantified for the command area. Data were collected from surveys of the area and from government agencies. Both the deterministic and change-constrained models suggest a more intensive cropping program in the region. Both emphasize more dependence on rabi and less on kharif crops. The chance-constrained especially suggests use of more water in the rabi season. Important chances in cropping programs and labor use take place under the chance-constrained model.     

UNIT HYDROGRAPHS – A COMPARATIVE STUDY1

ABSTRACT. Unit hydrographs derived by using two methods, linear programming and least squares, are compared. Test data comprise rainfall and runoff information from four storms over the North Branch Potomac River near Cumberland, Maryland. The mathematical bases of these methods for unit-hydrograph derivation are explained. The linear programming method minimizes the sum of absolute deviations, and the least squares method minimizes the sum of the squares of deviations. Computer subroutines are readily available for application of these methods. The unit hydrographs derived with the two methods are practically the same for storms 2 and 3, but differ somewhat for storms 1 and 4. However, the reconstituted direct surface runoff hydrographs are similar to those observed with the exception of the hydrograph for storm 4 which had a relatively more non-uniform rainfall excess of a considerably larger duration.