河流水质自动监测站选址适宜性评价

为建立和量化适于河流水质自动监测站选址的评价方法体系,提出了河流水质自动监测站选址一致性、可行性和适宜性评价问题,并建立了选址可行性和适宜性评价2套指标体系。以自动站选址与手工断面位置不一致为前提,利用累乘指数判断选址可行性,在可行的基础上利用模糊综合评价进一步分析选址的适宜性。应用案例显示,罗汉大桥断面水质自动站选址于手工断面下游150 m处是可行的,并且此选址高度适宜,在具有水质代表性的同时兼顾成本和运维管理需求。     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Comparative evaluation of sizing of metal hydride (MH) hydrogen storage tank filled with different alloys

This study presents a comparative analysis of sizing of metal hydride tank filled with different alloys. Alloys include solid solutions and intermetallic compounds of the generic families AB₅, AB₂, AB, A₂B. The effects of the different alloys on the sizing of metal hydride hydrogen storage tanks are complicated and depend on many factors. In this paper, a thermoeconomic optimization analysis with a simple algebraic formula was presented for the estimation of optimum metal hydride tank surface area for heat transfer enhancement. The optimum area of the metal hydride tank filled with commercially available different alloys (LaN₅, Ti_0,98Zr_0,02V_0,43Fe_0,09Cr_0,05Mn_1,5, TiFe, Mg₂NiH₄) was evaluated and compared by the developed method. The optimum net savings and the value of payback were determined for four alloys. It is found that mathematical model can be employed for the determination of optimum metal hydride tank design and increasing net savings according to alloy types. The optimum areas of the tanks filled with four alloys (LaN₅, Ti_0,98Zr_0,02V_0,43Fe_0,09Cr_0,05Mn_1,5, TiFe, Mg₂NiH₄) were calculated as 0.136, 0.130, 0.133, and 0.173 m², respectively. The optimum net savings for tanks filled with four alloys (LaN₅, Ti_0,98Zr_0,02V_0,43Fe_0,09Cr_0,05Mn_1,5, TiFe, Mg₂NiH₄) are about 461.0, 409.3, 419.6, and 979.6 $ and the values of payback are about 1.98, 2.1, 2.17, and 1.37 years, respectively. Excessive area of the metal hydride tank would not be as economical as the optimum tank area. Thermal management of metal hydride tank must be designed for optimum points calculated at which maximum savings occur.     

Evaluating the impact of uncertainty and variability on the value chain optimization of a forest biomass power plant using Monte Carlo Simulation

Mathematical programming models have been used to optimize the design and management of forest bioenergy supply chains. A deterministic mathematical model is beneficial for making optimum decisions; however, its applicability to real-world problems may be limited because it does not capture all the complexities, including uncertainties in the parameters, in the supply chain. In this paper, a combination of Monte Carlo Simulation and optimization model is used to evaluate the impact of uncertainty in biomass quality, availability and cost, and electricity prices on the supply chain of a forest biomass power plant. The optimization model is a deterministic mixed integer non-linear model with monthly time steps over a 1-year planning horizon. Variability in biomass quality, i.e. moisture content (MC) and higher heating value (HHV), based on the historical data of a real case study is studied in detail and fitted probability distributions are used in the model, while for electricity prices different scenarios are considered. The results show that the impact of variability in the MC on profit is higher than that of uncertainty in HHV. It is observed that the annual profit ranges between $13.3 million and $17.9 million in the presence of all possible uncertainties while its average is $15.5 million. Uncertainty in biomass availability and cost and electricity price results in the risks of having annual profit of less than $14 million and low monthly storage levels.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Ce-Sn-W-O_x催化剂的配伍优化及脱硝影响因素

采用共混热解法制备系列Ce-Sn-W-Ox复合氧化物,用于NH3选择性催化还原NO。通过正交实验优化CeSn-W-Ox配方,采用环境扫描电镜(ESEM)、X-射线衍射仪(XRD)等表征分析催化剂的微观形貌和固相结构,确立Ce-Sn-WOx最佳配比及结构形貌。结果表明,以粒度为5~8 mm的堇青石瓷片担载分散Ce-Sn-W-Ox,进行NH3-SCR脱除NO,当Ce/Sn/W元素摩尔比为1∶0.8∶0.6时,Ce Sn0.8W0.6Ox/堇青石NH3-SCR脱除NO效果最好。当空速为7 200 h-1,催化剂在252~426℃内脱除NO效率均大于94%。重点考察了反应空速(GHSV)、水蒸气(H2O)、SO2等对Ce Sn0.8W0.6Ox/堇青石NH3-SCR脱除NO活性的影响。研究表明,空速低于10 000 h-1时,催化剂脱硝活性受空速影响小;单独通入5%H2O对催化剂脱硝活性基本没有影响;单独通入429 mg/m3SO2导致催化剂活性略有降低;同时通入429 mg/m3SO2和5%H2O,催化剂脱硝活性下降至85.33%,除去SO2和H2O后,催化剂活性又能明显回升。     

基于GIS的乌梁素海水体富营养化状况的模糊模式识别

利用基于MATLAB 7.0实现的模糊模式识别交叉迭代模型对2006年5—10月分布于乌梁素海各水体功能区的21个水质监测点的富营养化等级进行了模糊模式识别,并在GIS技术支持下,用Arcview的空间分析功能绘制富营养化等级识别结果、对富营养化状态影响权重最大的评价指标总氮(TN)含量和富营养化状态控制元素总磷(TP)含量对应的富营养化等级水体和地表水质等级水体的空间分布月变化Grid专题图.将富营养化状态变化及其分布区域与乌梁素海同期水质监测指标浓度变化及其分布区域进行对比分析及验证.结果表明,富营养化等级识别结果的时空分布与实际情况相符,能够比较准确地反映富营养化等级定量的时空变化趋势.      

基于AHP-熵权法的跨燃气管道现浇梁施工风险评价

为保障某跨燃气管道现浇梁施工安全,建立现浇梁BIM模型进行动态施工模拟,找出影响现浇梁施工的风险因素,从地质条件、外界影响、安全管理3个方面建立了跨燃气管道现浇梁施工风险评价体系;结合"熵"理论和层次分析法综合确定各影响因素权重并对现浇梁施工风险进行模糊综合评价;研究表明:①通过BIM动态模拟,直观全面地识别出施工风险...     

基于模糊数学理论的尾矿库环境质量综合评价

尾矿库的环境对其周边地区的环境有着重大的影响.建立了尾矿库的环境质量模糊综合评价指标体系,通过专家打分法确定了某尾矿库各层评价指标的权重以及第3层次的模糊关系综合矩阵,并对此尾矿库的环境质量进行了模糊综合评价.最后得出结论:该尾矿库的环境质量综合评价等级为"中".     

人的差错行为对矿山安全的模糊综合评判

人的差错行为对矿山安全有着极大的影响.对人的差错行为因素进行分析,利用模糊综合评判的方法,对某煤矿工人作业行为安全性的评判,确定该煤矿矿工行为的安全状态,从而及时了解矿工情绪、心理等状态,适时地进行安全培训教育,以保障人员安全作业.