Studies on process optimization of biodiesel production from waste cooking and palm oil

This work investigated the optimisation of biodiesel production from waste cooking oil (WCO) and palm oil using a two-step transesterification process for WCO and base catalysed transesterification for palm oil. Transesterification reactions were carried out to investigate the effects of prepared catalyst CaO, methanol/WCO and methanol/palm oil ratio and temperature on the yield of biodiesel. A series of experiments were conducted to determine the best conditions for biodiesel production, using methanol/oil ratio between 4:1 and 11:1 and contact time varying between 2 and 4 h. Biodiesel yield of around 90 and 70% was obtained for palm and waste cooking oil at the methanol/oil ratios of 6:1 and 8:1 at temperature of 60 °C for reaction time of 4 h using prepared CaO as catalyst. The physicochemical properties of palm and WCO biodiesel were carried out using standard methods, while the fatty acid profile was determined using gas chromatography. The investigation concludes that biodiesel obtained from palm and waste cooking oil was within the specified limit.     

Impact of incorporating customer preference in sustainable remanufacturing of commercial returns

This paper investigates optimum production parameters for a reverse supply chain for manufacturing of primary products and remanufacturing of commercial returns (products returned by customers for refund or exchange). The market for the product consists of two categories, the primary and remanufactured products. The demands for these markets are independent and considered to be random variables following a normal distribution function. The approach presented in this work differs from many previously published works because the acceptability of products varies among customers. The interaction between the designed quality and variable customers’ preferences determines the likelihood of a product being returned. Two major decision variables targeted in this study are the production cycle time and the targeted quality for production of parts used in the product. Through an analytical formulation and numerical examples, a relationship between the total profit of the system and the two decision variables is developed and optimised. The analysis demonstrates that the total profit of the hybrid system could be increased significantly by targeting the optimum targeted (not necessarily the highest) values for quality of parts and the optimum cycle length. And this objective could be accomplished with significant gain with respect to sustainability and waste reduction.     

基于Kriging模型的载人航天某装置结构优化设计研究

对于处在振动环境中的载人航天某装置复杂结构,设计过程中存在最小化质量、同时最大化一阶整体振动频率的多目标优化问题,可以利用多目标遗传算法(NSGA-II)求解得到Pareto最优解集,但利用NSGA-II进行求解计算量大,对于复杂结构更甚。为了节省计算时间,提出基于Kriging代理模型的复杂结构多目标优化设计方法,首先通过拉丁超立方采样获得样本点,然后通过样本点创建Kriging模型,最后利用多目标遗传算法求解代理模型得到Pareto最优解集,方便设计师从中选择最优解,优化结果表明本文所述方法合理有效。     

保护地生态承载力不确定性多目标优化模型研究——以黄河源区玛多县为例

为明确给出保护地综合生态承载力的实质内涵"人类活动强度阈值",利用不确定性多目标优化方法,建立了区域保护地生态承载力优化模型.应用该模型对黄河源区玛多县进行区域保护地生态承载力评价及规模结构优化.结果表明:草畜矛盾是制约玛多县社会经济发展的瓶颈;根据《三江源国家公园总体规划》目标,在保证野生动物种群数量发展的同时畜牧业...     

城市固体废物不确定性多目标优化管理模型

在对城市固体废物管理进行系统分析,以及对各种模型深入研究的基础上,提出了不确定性多目标动态优化固体废物管理模型.模型以系统成本最小和环境影响最小为目标框架,采用不确定性分析、污染损失理论,将城市固体废物管理过程中对环境产生的影响进行货币化,使环境和经济有效地统一起来,以更加客观地解决多目标问题;同时采用完整、合理的约束条件,进一步对模型进行有效补充.将该模型应用于案例城市的优化结果表明:采用该模型可使每t固体废物处置成本较原方案减少8～18元,每年最少可节约2.8×107元,大大减少了运营成本.该模型采用二次污染处理至达标排放的费用,因此可以在系统成本最小的基础上,兼顾固体废物对环境产生影响最小的目标,有效地解决了多目标解法存在的问题.      

人工补水条件下的缺水河流生态修复综合评价方法

构建了人工补水条件下的缺水河流生态修复多目标综合评价指标体系,对生态修复中影响评价指标量化结果的因素进行了综合考虑,提出了包含主、客观因子并反映层次关系的综合权重确定方法,进而建立了一种人工补水条件下的缺水河流生态修复综合评价方法,以更好地解决多目标决策中的总目标量化问题.最后,以正在建设的永定河生态修复工程为例,通过构建典型的生态修复情景方案,对建立的评价指标体系进行应用,确定各评价指标的综合权重系数,并对构建的情景决策方案进行了综合评估,验证本文提出的评价指标权重综合调整的必要性,说明构建的人工补水条件下的缺水河流生态修复综合评价方法的合理性与可行性.结果表明,所提出的评价方法不仅对人工补水条件下的河流生态修复决策具有一定的实用价值,而且对其它类型生态修复多目标综合决策评价也具有借鉴意义.     

基于贝叶斯公式的地下水污染源识别

将贝叶斯公式与地下水二维水质对流-扩散方程相耦合,建立依靠监测井监测值的地下水污染源参数（污染源强度M、排放位置（X₀,Y₀）和排放时刻T₀）反演模型.针对监测井监测值信息量不充分或者监测值与模型参数关联性较弱的问题,提出了一种基于贝叶斯公式与信息熵的监测井优化设计方法.构建一个污染物在承压含水层中瞬时排放的算例,在确定单井监测及监测次数条件下,以监测井位置D及监测频率Dt的优化为目标,分别进行模型参数后验分布信息熵最小的单目标监测方案优化,以及信息熵最小且监测耗时最短的多目标监测方案优化.依据优化后的监测方案采用延迟拒绝自适应Metropolis算法进行污染源参数反演识别.算例研究表明：在预设定单井监测,且监测次数为5次条件下,单目标优化后的监测方案为D=（830.2,199.8）,△t=2.7,在此监测方案下,4个污染源参数M,X₀,Y₀,T₀的反演均值误差分别为19.5%、13.2%、3.4%、1.3%;多目标优化后的监测方案为D=（807.9,199.4）,△t=1.2,在此监测方案下,4个污染源参数M,X₀,Y₀,T₀的反演均值误差分别为19.9%、13.4%、3.7%、4.2%.与基于单目标优化的监测方案的反演结果相比,基于多目标优化的监测方案条件下,污染源参数的反演均值误差虽分别增加了0.4%、0.2%、0.3%、2.9%,但监测时间却显著缩短了55.6%.     

AHP与SMART方法在环境工程方案评比中的应用

本文以某大型污水海洋处置工程的方案评选工作为背景，介绍了ＡＨＰ和ＳＭＡＲＴ多目标决策方法在环境规划与决策中的应用。具体叙述了方案选优的总技术路线，目标体系的建立，目标相对权重的确定，指标值的评判与规范、方案排序与结果灵敏度和合理性分析等内容。结果表明，ＡＨＰ与ＳＭＡＲＴ方法相结合，是适于环境工程方案评选的一种较科学合理的方法。     

RESERVOIR MANAGEMENT RULES DERWED WITH THE AID OF MULTIPLE OBJECTIVE DECISION MAKING TECHNIQUES1

ABSTRACT: The determination of optimum reservoir operating rules for reservoirs with multiple conflicting objectives is still a difficult task - despite many publications in this field. In this paper a three-step Multi Objective Decision Making (MODM) method is presented, the emphasis of which is placed on the necessity to make the work easy for the decision maker, which many MODM techniques fail to achieve. The method is applied to the development of a compromise optimum operating rule for a multi-purpose reservoir. In the first step of the method stochastic DP is chosen which is combined with the “weighting method” allowing combination of various objectives into one objective function. By systematically varying the weights for the objectives a large number of pareto optimum reservoir operating rules is generated. In the second step of the method the performance of all these operating rules is tested with the aid of a model simulating reservoir operation. The results are statistically analyzed and the reliabilities for attaining the various objectives are computed. The third step of the model applies another MODM technique which allows the decision maker - in a computer dialog - to select his optimum reservoir operating rule from the large number of pareto optimum solutions generated in step 1. Here he can specify his preferences for the various objectives. For this purpose two alternative MODM techniques are offered: Compromise Programming and the SEMOPS method. Their performance is shown along with the generation and selection of operating rules for the multi-objective Wupper reservoir system in Germany.     

Optimisation of reduction of global CO2 emission based on a simple model of the carbon cycle

A simple model has been designed to describe the interaction of climate and biosphere. Carbon dioxide, understood as a major emitted gas, leads to a change of global climate. Economic interpretation of the model is based on the maximisation of the global CO₂ cumulative emissions. The two most important profiles of emission have been obtained: optimal and multi-exponential suboptimal profiles, each displaying different characteristics. This revised version was published online in July 2006 with corrections to the Cover Date.