基于非支配排序遗传算法的乙苯脱氢工艺条件优化

为提高现有乙苯脱氢制苯乙烯生产装置的生产率和节能水平,优化技术是一种有效的技术手段。基于改进的非支配排序遗传算法(NSGA-Ⅱ)研究了乙苯脱氢工艺条件的优化问题。把乙苯脱氢反应过程的转化率、选择性作为优化目标,动力学模型以及实际生产状况作为约束条件,构造乙苯脱氢过程的多目标优化问题。基于NSGA-Ⅱ算法求解得到的优化问题的Pareto最优集,分析了各个操作条件对乙苯脱氢生产过程转化率和选择性的影响,最后利用模糊综合评价法,为合理决策提供了有效的依据。结果表明NSGA-Ⅱ具有良好的全局优化性能,运用该算法可在不同的操作约束条件下,求解得到相应的满意解。     

活性污泥法脱氮除磷工艺优化设计的灵敏度分析

以ASM2D为机理模型对活性污泥法脱氮除磷工艺进行优化设计,在满足出水水质标准的前提下,使总设计费用达到最低,对优化模型中的各种参数进行灵敏度分析。结果表明,不同种类参数的灵敏度差别很大,其中目标函数中各参数对结果影响最大,最大灵敏度达到-99.02%;进水组分、化学计量系数和动力学参数的最大灵敏度分别为16.06%、11.9%和7.60%。随着排放标准的下降,系统的总费用也随之减少。对优化设计中参数进行灵敏度分析可以得出一些重要参数对结果的影响程度,为参数校正和结果输出提供理论依据。     

基于改进粒子群算法的乙苯脱氢过程多目标优化

设计了一种基于支配关系构造非支配解集的多目标粒子群算法(MOPSO),将当前找到的非支配解保存到一个外部集——最优解集,利用支配更新其最优解集,多次迭代后得到Pareto最优解集。把乙苯脱氢反应过程的收率和选择性作为优化目标,动力学模型和实际生产状况作为约束条件构造乙苯脱氢过程的多目标优化问题,利用改进的多目标粒子群算法进行优化求解。基于求得的Pareto最优解集研究了各个操作条件对乙苯脱氢生产过程收率和选择性的影响,为后续乙苯催化脱氢系统实施先进控制奠定了基础。     

A systematic model calibration methodology based on multiple errors minimization method for the optimal parameter estimation of ASM1

A one-step model calibration methodology of the activated sludge model no. 1 (ASM1) of a full-scale wastewater treatment plant (WWTP) is proposed. First, the key parameters among all parameters of the ASM1 model are selected by sensitivity analysis based on the effluent quality index. Second, multiple response surface methodology (MRSM) is conducted to find the optimal parameter values of the ASM1 model. Lastly, an MRSM analysis is conducted in order to determine the optimal parameter values. This study was conducted in order to develop a new systematic model calibration methodology that can greatly help the modeler to find the optimal solution by selecting the key parameters and optimizing the parameters. In two case studies of simple activated sludge process and a full-scale plant, the experimental results indicated that the calibrated models can improve the prediction quality of the ASM model and the efficiency of the modeling.     

Multi-objective modeling and optimization for scheduling of cracking furnace systems

Cracking furnace is the core device for ethylene production. In practice, multiple ethylene furnaces are usual y run in parallel. The scheduling of the entire cracking furnace system has great significance when multiple feeds are simultaneously processed in multiple cracking furnaces with the changing of operating cost and yield of product. In this paper, given the requirements of both profit and energy saving in actual production process, a multi-objective optimization model contains two objectives, maximizing the average benefits and minimizing the average coking amount was proposed. The model can be abstracted as a multi-objective mixed integer non-linear programming problem. Considering the mixed integer decision variables of this multi-objective problem, an improved hybrid encoding non-dominated sorting genetic algorithm with mixed discrete variables (MDNSGA-I ) is used to solve the Pareto optimal front of this model, the algorithm adopted crossover and muta-tion strategy with multi-operators, which overcomes the deficiency that normal genetic algorithm cannot handle the optimization problem with mixed variables. Finally, using an ethylene plant with multiple cracking furnaces as an example to illustrate the effectiveness of the scheduling results by comparing the optimization results of multi-objective and single objective model.     

基于神经网络和遗传算法的塑料热压成型多目标优化

论述了人工神经网络和遗传算法在塑料热压成型工艺优化中的应用,首先利用人工神经网络建立热压成型工艺参数与零件性能之间关系的数学模型,然后用遗传算法对工艺参数优化。根据多目标函数优化问题的单目标化思想,对优化后的单目标进行分解,得到最优工艺参数条件下的塑料热压产品性能,从而为建立和控制塑料热压成型工艺参数提供了一种行之有效的方法。     

Optimal design of liquid-solid circulating fluidized bed for continuous protein recovery

In recent years, liquid-solid circulating fluidized beds (LSCFBs) are being applied as a reactor system in a number of new applications. This study addresses optimal design of LSCFB system at the design stage for the continuous protein recovery. The operation of LSCFB system for continuous protein recovery is associated with several important objectives such as production rate and recovery of protein as well as the amount of ion exchange resin requirements, all of which need to be optimized simultaneously. In this study, an experimentally validated mathematical model was used to perform the multi-objective optimization of the LSCFB system at the design stage. In the optimization study, eight operating and design parameters were used as decision variables. These variables were chosen based on systematic sensitivity analysis of the system which showed complex interplay of the decision variables over the system performance indicators. Elitist non-dominated sorting genetic algorithm with its jumping gene adaptation (NSGA-II-aJG) was used to solve a number of two- and three-objective function optimization problems. The optimization resulted in Pareto optimal solutions, which provides a broad range of non-dominated solutions due to conflicting behavior of the decision variables on the system performance indicators. Compared to the optimization results obtained in the operating stage, the performance of the system was further improved at the design stage optimization as changes in physical dimensions of the LSCFB system can provide better performance than would have been possible by adjusting only the operating parameters.     

活性污泥法污水处理厂的运行模拟

结合ASM1和二沉池模型组成活性污泥模拟系统,将某污水处理厂的常规检测数据转化为活性污泥系统模型所需的组分数据,然后调整模型参数,使污水处理厂出水指标最接近于污水处理厂实际数据,从而确定适合该污水处理厂的模型参数,最后对该污水处理厂的工艺参数进行了模拟改造。     

非线性污水处理过程的多目标优化

研究了复杂非线性污水处理过程的多目标优化。针对污水处理过程的非线性动力系统,建立了使污水处理过程运行成本和描述实际输出与期望输出偏差的平方可积误差设计指标同时达到最优的多目标优化模型。采用间接优化方法,首先将描述污水处理过程优化的多目标非线性问题转化为多目标线性规划问题,然后利用遗传算法对其进行求解。本文方法不仅获得了多目标优化问题的近似Pareto前沿,而且由于采用的是多目标线性规划方法,所以具有计算成本低的优点。     

活性污泥法脱氮除磷工艺的优化设计

利用活性污泥2D模型对城市污水厂脱氮除磷工艺进行优化设计,构建A²/O工艺的仿真模型,通过模型校正对工艺参数进行优化,并将优化设计与传统设计法和试算法进行比较。结果表明,优化模型得出的模拟结果与实验测定值基本相吻合。优化设计法得出的污水厂基建费用和运行成本与其他两种方法相比,都有了很大的降低,虽然出水水质略有下降,但仍满足国家排放一级B标准。活性污泥2D模型可以对污水厂进行优化设计和控制。在满足出水水质前提下,降低污水厂的费用,并对以后的工艺设计提供理论指导。     

Mathematical modeling and modification of an activated sludge benchmark process evaluated by multiple performance criteria

Optimal modification of an activated sludge process (ASP) evaluated by multiple performance criteria was studied. A benchmark process in BSM1 was taken as a target process. Four indexes of percentage of effluent violation (PEV), energy consumption (OCI), total volume of tanks (TV) and total suspended solid in tank5 (TSSa5), were criteria and eleven process parameters were decision variables, making up the multiple criteria optimization model, which was solved by non-dominated sorting genetic algorithm II (NSGA-II) in MATLAB. Pareto solutions were obtained; one solution (opt1) was selected based on the authors’ decision for a further analysis. Results show that the process with opt1 strategy exhibits much better performance of PEV and OCI than with the default, being improved by 74.17% and 9.97% specifically under dry influent and without control. These results indicated that the multiple criterion optimization method is very useful for modification of an ASP.     

Off-Line Determination of the Optimal Command Policies for a Sludge Drying Application

The main objective of this work is to develop, using a predictive control method, an off-line determination of the operating parameters for a sludge drying stage. At each time step, two operating parameters are identified by simultaneously minimizing three objective functions over a finite horizon. A laboratory dryer is briefly presented and used, in order to evaluate the suitability of the direct model employed to simulate sludge drying. Surface temperature, drying kinetics, and evaporated mass flux obtained from experimental measurements are compared to numerical simulations. Afterward, the optimization procedure is carried out and the results are discussed.     

基于混合建模的煤泥流化床锅炉干法脱硫操作优化

煤泥流化床锅炉干法脱硫系统因成本低、脱硫效率较高而应用广泛。流化床锅炉的运行条件对脱硫效率具有重要影响,而脱硫剂的增加既会提高脱硫效率又会降低锅炉热效率,因此存在最佳操作条件。首先采用LSSVM建立了SO₂浓度预测模型,并通过实际数据验证了模型的准确性和快速性。在此基础上,通过机理分析,建立了脱硫剂对锅炉热效率影响的全面准确模型。最后,以企业总体运行费用最低为目标,建立了总的操作优化目标函数。以SO₂预测模型和锅炉热效率模型为基础,通过求解总的优化命题,得到了不同SO₂浓度限制和不同SO₂排放费用下的最佳锅炉操作条件。通过优化明显地降低了脱硫运行费用,提高了脱硫效率,对流化床锅炉干法脱硫系统具有重要的指导意义。     

Product quality improvement of batch crystallizers by a batch-to-batch optimization and nonlinear control approach

Batch crystallization is one of the widely used processes for separation and purification in many chemical industries. Dynamic optimization of such a process has recently shown the improvement of final product quality in term of a crystal size distribution (CSD) by determining an optimal operating policy. However, under the presence of unknown or uncertain model parameters, the desired product quality may not be achieved when the calculated optimal control profile is implemented. In this study, a batch-to-batch optimization strategy is proposed for the estimation of uncertain kinetic parameters in the batch crystallization process, choosing the seeded batch crystallizer of potassium sulfate as a case study. The information of the CSD obtained at the end of batch run is employed in such an optimization-based estimation. The updated kinetic parameters are used to modify an optimal operating temperature policy of a crystallizer for a subsequent operation. This optimal temperature policy is then employed as new reference for a temperature controller which is based on a generic model control algorithm to control the crystallizer in a new batch run.     

Biological Treatment of Saline Wastewater by Fed-Batch Operation

The adverse effects of salt on biological treatment of saline wastewater inoculated by activated sludge culture were investigated. A synthetic wastewater composed of diluted molasses, urea, KH₂PO₄ and various concentrations of salt (1–5% w/v NaCl) was treated in an aerobic-biological reactor operating in fed-batch mode. An activated sludge culture obtained from a wastewater treatment plant was used as the seed. Variations of chemical oxygen demand (COD) removal rate and efficiency with salt concentration were determined. A rate expression including salt inhibition effect was proposed and kinetic constants were determined by using the experimental data. © 1997 SCI.     

CAST工艺在大连凌水河污水处理厂的应用

介绍了大连凌水河污水处理厂CAST工艺设计参数和工艺特点,实际运行中进出水水质情况及运行效果。分析了CAST工艺的进水方式、曝气量、污泥浓度等运行参数对污水处理效果的影响。凌水河污水处理厂的运行结果表明,CAST工艺对城市污水有较好的处理效果,出水指标稳定达到了《城镇污水处理厂污染物排放标准》（GB18918-2002）一级B标准。     

Optimal Design and Economic Evaluation of Dividing‐Wall Columns

In an effort to reduce costs, a systematic optimization approach is proposed to address the energy consumption of dividing‐wall columns (DWCs). This iterative optimization procedure begins by minimizing the overall heat duty using an innovative objective function within a constrained design space. A sensitivity analysis is then carried out on the manipulated variables to obtain their optimal ranges. Optimal operating parameters are obtained through the evaluation of the total annualized cost (TAC). For the separation process of benzene/toluene/o‐xylene, the optimal DWC flow sheet exhibits a significant decrease in TAC when compared to conventional flow sheet optimum designs. The applied optimization method and sensitivity analysis have proven to produce results at the global optimum. This method is both practical and easily applied to other systems, even to systems with more than three components.     

Predictive control with multiobjective optimization: Application to a sludge drying operation

The main objective of this study is to develop an offline tuning of the operating input parameters for a sludge drying operation, by using multiobjective optimization techniques combined with a predictive control method. The manipulated variables concerned are the temperature and the relative humidity of the drying air (T_air, RH_air). The optimal time for the reversal operation of the product is also investigated. The optimization procedure is coupled to a one-dimensional numerical model that allows the simulation of moisture content and temperature field evolutions in the product during the drying step. A genetic algorithm is used to identify the two manipulated variables, at each step time, by minimizing simultaneously three objective functions over a finite horizon. These objective functions are linked to penalties concerning the heating and dehumidifying of the outside air used for the drying stage and to a global moisture content gap relative to a drying target. First, the heat and mass transfer model is validated for the drying step of a plate sample of sludge, with a reversal operation. Afterwards, the optimization procedure is carried out, and the results are discussed in terms of an energetic analysis.     

基于多目标函数的亚临界有机朗肯循环的参数优化和性能分析

以系统净输出功率W_net、热源流体进出口(火用)降DE_g、系统总不可逆损失I和系统总投资成本C₂₀₁₃构建多目标优化模型,采用线性加权评价函数法对该模型进行求解,以R600a、R245fa、R601a、Pentane 4种纯工质以及R600a/R601a、R245fa/R601a、R245fa/Pentane和R600a/R245fa 4种非共沸混合工质为例,对亚临界有机朗肯循环（ORC）的蒸发温度T_e和冷凝温度T_c进行优化。研究结果表明：采用单目标有时得不到最优值,而采用多目标均能得到最优值,且多目标优化可以较好地协调各性能指标间的关系,使所要求的各项指标均能达到较优,因此多目标优化比单目标优化更加合理;存在最优蒸发温度T_e,opt和最优冷凝温度T_c,opt使多目标函数F（X）最小,同时,T_e,opt、T_c,opt随工质不同而不同;在T_e,opt或T_c,opt下,对比纯工质和混合工质的不同单目标函数值和F（X）值时,混合工质并不总是优于纯工质。     

催化剂失活条件下的碳二加氢反应器模拟与优化

乙炔加氢反应催化剂的活性与选择性随着使用时间变化而变化,操作参数需要相应的改变从而使得收益最大化。因此本文采集工业数据,通过遗传算法拟合了反应动力学模型和失活反应模型的参数;比较了国内最普遍使用的两种催化剂的选择性和活性保持方面的性能;针对串联使用的两台装填不同催化剂的反应器组合,以运行周期、乙烯产率最优为评价标准,提出了反应器3种组合优化、负荷分配优化等优化策略。将优化策略应用于实际工业装置的分析与运行,乙烯产率和总选择性提高,效果得到验证。