Modelling Phosphorus Retention in Lakes and Reservoirs

Steady-state models for the prediction of P retention coefficient (R) in lakes were evaluated using data from 93 natural lakes and 119 reservoirs situated in the temperate zone. Most of the already existing models predicted R relatively successfully in lakes while it was seriously under-estimated in reservoirs. A statistical analysis indicated the main causes of differences in R between lakes and reservoirs: (a) distinct relationships between P sedimentation coefficient, depth, and water residence time; (b) existence of significant inflow–outflow P concentration gradients in reservoirs. Two new models of different complexity were developed for estimating R in reservoirs: , where τ is water residence time (year), was derived from the Vollenweider/Larsen and Mercier model by adding a calibrated parameter accounting for spatial P non-homogeneity in the water body, and is applicable for reservoirs but not lakes, and , where [P_in] is volume-weighted P concentration in all inputs to the water body (μg l⁻¹), was obtained by re-calibrating the OECD general equation, and is generally applicable for both lakes and reservoirs. These optimised models yield unbiased estimates over a large range of reservoir types.     

生物表面活性剂产生菌犁头霉菌(Absidia orchidis)的筛选及发酵条件优化

采用植物油为唯一碳源,设计选择培养基,从饭店下水道污泥中筛选出生物表面活性剂产生菌.结果分离到12株菌,其中一株能使发酵液的表面张力值从68 mN·m-1降低到34.5 mN·m-1,具有开发潜力,被选出作进一步的研究.该菌株经鉴定为犁头霉菌(Absidia orchidis).通过正交试验对犁头霉菌的培养条件进行优化,其优化培养条件为:植物油3.6 g·L-1,KH2PO412.1 g·L-1,Na2HPO45 g·L-1,(NH4)2SO4 1 g·L-1,NaNO32 g·L-1,酵母浸膏0.1 g·L-1,MgSO4·7H2O 0.15 g·L-1,NaCl 5 g·L-1,CaCl2 0.1 g·L-1,EDTA 1 g·L-1,KI 0.83μg·L-1,H3PO4 0.01μg·L-1,CoCl2·6H2O 0.048μg·L-1,MnSO4·H2O 0.312μg·L-1,Na2 MoO4·2H2O 0.048μg·L-1,ZnCl2 0.287μg·L-1,CuSO4·5H2O 0.125μg·L-1,初始pH值8,接种量6%.发酵70h时可获得生物表面活性剂的最大收获量,此时发酵液中生物表面活性剂的相对浓度达402倍.     

城市有机垃圾间歇厌氧消化pH控制动力学研究

对厌氧消化系统的物料及电离平衡进行分析,利用底物降解和微生物生长动力学建立城市有机垃圾间歇厌氧消化pH值控制模型,并研制开发了间歇厌氧消化过程pH值与产气量最优化计算机软件.运用该模型可预测不同厌氧消化过程的最佳pH值,从而通过控制厌氧系统的pH值使系统产气量达到最大,通过2组对比实验验证模型的有效性.结果表明,在相同的实验条件下厌氧系统的pH控制在最佳值时系统产气较未对pH值控制时稳定,且总产气量平均提高20%左右.     

煤矿应急资源优化管理与调度监控研究

为了提高煤矿应急资源在日常的分类分级管理和在突发事故救援过程中的统一调度,把煤矿应急资源划分为人员流、物资流和信息流,并且通过构建煤矿应急资源救援调度模型和建立煤矿应急资源实时监控机制,提高应急资源在突发事故或预案演练中的应急保障能力,最终实现应急资源的日常分类管理、灾时统一调度的应急联动体系。     

湖北省土地利用减碳增效系统仿真及结构优化研究

土地利用变化是引起碳排放的重要原因之一,土地经济效益是利用土地的目标之一,如何通过优化土地利用结构实现土地利用减碳增效是值得研究的重要问题。基于系统结构与功能相互作用的视角,梳理复杂系统内变量间的反馈关系,运用系统动力学(SD)进行建模,将约束条件纳入到多目标规划(MOP)中,实现MOP与SD模型整合,进行系统仿真并得出优化后2020年湖北省土地利用结构。结果显示,利用SD-MOP模型能够实现减碳增效目标下土地利用结构优化,与2008年真实值相比,耕地、林地、牧草地及建设用地分别增加了0.33×10~4、30.17×10~4、0.08×10~4和16.37×10~4 hm~2,其他农用地及未利用地分别减少7.23×10~4、33.15×10~4 hm~2;与无约束SD单模型仿真相比,土地利用碳排放量减少了58×10~4 t,经济效益年增长率维持在3.58%,优化方案具有可行性。SD-MOP模型优化的土地利用结构符合区域可持续发展要求,兼顾了土地利用碳减排和经济效益增长的双重目标,能为区域土地资源优化配置提供参考。     

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.     

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.     

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.     

基于灰色模糊理论的流域水电规划环境影响综合评价

结合模糊优选理论和灰色关联分析方法,提出灰色模糊综合评价法,该方法将灰色关联分析作为优属度确定的隶属度计算方法;提出理想环境序列建立遵循的原则,引入梯形模糊数实现定性指标量化并采用变异系数法确定评价指标权重.应用灰色模糊综合评价法对黄河流域河段水电规划的高坝方案和多级开发方案进行了比选研究,计算了两个方案的优属度及其开发性因子、稳定性因子、保护性因子、经济活力因子、社会可接受因子、环境风险因子等6个指标层优属度,结果表明,多级开发方案总体优于高坝方案;多级开发方案的保护性远好于高坝开发方案,而高坝方案的开发性略好于多级开发方案,稳定性、经济活力、社会可接受、环境风险等因子两种方案比较接近.评价结果与流域实际情况比较符合,证明该方法是一种有效的方法.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.