旋转填充床中微观混合模型与实验验证

根据旋转填充床中液体流动和混合特征,建立了一个新的复合式微观混合模型,并对串联竞争反应的标准体系进行了模拟和实验验证。结果表明,在旋转填充床内,当体积比α较小时（如α＝2）,微观混合影响很小,过程处于化学反应控制区;当α较大时（如α＝20）,过程处于微观混合作用区,提高转速使离集指数降低,流量增加对离集指数影响很小;考虑液体初始宏观分布不均匀对混合的影响,模型计算结果与实验结果吻合良好。     

Influence of process parameters on extraction equilibria for the chiral separation of amines and amino‐alcohols with a chiral crown ether

Reactive extraction is studied as a promising chiral separation technique for commercial production scale. For chiral separation of amines and amino alcohols, a chiral crown ether was identified as a versatile enantioselective extractant. In this paper, the influence of various process conditions on the extraction performance is studied experimentally, and a predictive model is constructed based on the chemical and physical equilibria. It was found that the operational selectivity in one extraction step is mainly determined by the complexation constants between crown ether and enantiomers (which are dependent on solvent and temperature) and by the extractant concentration, whereas the distribution ratio is also strongly influenced by the pH. The model gives an excellent prediction of the operational selectivity and a good explanation for the system's responses to changes in process conditions. The model can be used as a basis for a multistage equilibrium extractor model and for conceptual process design. Under optimal process conditions, an operational selectivity >1.5 was obtained for five out of seven model compounds, with satisfying distribution ratios (D ～ 1–10). Copyright © 2006 Society of Chemical Industry     

Optimization of the amines-CO2 capture process by a nonequilibrium rate-based modeling approach

Amine-based chemical absorption has become the most mature technology among carbon dioxide capture processes, featuring the advantages of high separation efficiencies and its simplicity to attach it to existent industrial facilities. Nevertheless, further improvements on its performance are required in order to implement this technology to a wider extent. Energy expenditure at the solvent regeneration unit has been remarked as the major drawback of the process under discussion; therefore, the main objective of this work is to compute optimal operating policies which ensure minimum heat load at the reboiler along with reasonable removal efficiencies. A deterministic mathematical model of a reported pilot plant was deployed as the basis for the nonlinear programming optimization formulations, using a rate-based approach and an eNRTL thermodynamic framework. Several optimization scenarios were studied to account for diverse capture targets and degrees of freedom. Furthermore, sensitivity analyses were performed to understand the stand-alone effect of some variables on the process. Results reflect the importance of optimizing the complete plant to account for significant interactions between variables, as well as choosing an operational arrangement according to the separation goal demanded.     

Fluid catalytic cracking optimisation using factorial design and genetic algorithm techniques

Statistical techniques coupled with genetic algorithm (GA) were used to identify optimal values of key operational variables in fluid catalytic cracking (FCC) process. A Kellog Orthoflow F fluid catalytic cracking process model was considered. It is known as a highly nonlinear process with a large number of variables with strong interactions among them. A reduced process model was obtained through factorial design technique to be used as a process function in the optimisation work giving as result the operational conditions that maximise conversion without infringing operational restrictions with savings in computational burden and time. An increase of 8.71% in process conversion was achieved applying GA as optimisation technique. © 2012 Canadian Society for Chemical Engineering     

CLosed-Cycle Drying of Solids

The influence of the recovery system and other system parameters upon drying selectivity was studied in a closed-cycle dryer. A continuously-worked unit consisting of a single stage dryer and a ondenser was simulated. In the dryer, a thin solid wetted with a liquid mixture was dryed in contact with an inert gas flowing either parallelly or as an impinging jet Partial recycle of the exhaust gas was allowed. Two recovery systems were studied, a scrubber condenser and an indirect condenser. Both drying and condensation were described by a mathematical model considering a s-phase-controlled process. The inlet liquid composition in the scrubber condenser has the greatest influence on drying selectivity. Degree of vapour recovery, recycle ratio and other operational parameters ffect selectivity and equipment dimensions in a variable extent. The combined use of these variables constitutes a powerful method to control selectivity. The present models may be useful to aid the optimization of the system with regard to product quality in gas-phase-conirolled processes.     

CLosed-Cycle Drying of Solids

ABSTRACT

The influence of the recovery system and other system parameters upon drying selectivity was studied in a closed-cycle dryer. A continuously-worked unit consisting of a single stage dryer and a ondenser was simulated. In the dryer, a thin solid wetted with a liquid mixture was dryed in contact with an inert gas flowing either parallelly or as an impinging jet Partial recycle of the exhaust gas was allowed. Two recovery systems were studied, a scrubber condenser and an indirect condenser. Both drying and condensation were described by a mathematical model considering a s-phase-controlled process. The inlet liquid composition in the scrubber condenser has the greatest influence on drying selectivity. Degree of vapour recovery, recycle ratio and other operational parameters ffect selectivity and equipment dimensions in a variable extent. The combined use of these variables constitutes a powerful method to control selectivity. The present models may be useful to aid the optimization of the system with regard to product quality in gas-phase-conirolled processes.     

一种新型的基于Levenshtein距离层次聚类的时序操作优化方法

现代流程工业过程中，DCS采集并存储了大量的操作时序数据，若能将其中有价值的操作经验和操作信息提取出来，则可大大提高操作系统的性能。然而，操作经验概念较为模糊，无法具体量化。因此，将具有时序特征的操作数据符号化，使操作经验以区块化形式表示，并提出一种基于Levenshtein距离的时序层次凝聚聚类算法，通过对操纵变量的历史时序操作数据进行相似性搜索，进而获得多种相似的操作模式，并将每种类型的操作模式对应的过程变量进行性能分析，从而得到并保存实际工作过程中所需的操作经验，以达到生产过程操作优化的目的。为了验证所提出方法，将其用于连续组分精馏操作过程，实验结果表明所提出的基于Levenshtein距离层次聚类的操作优化方法的有效性。     

基于多分类概率极限学习机的污水处理过程操作工况识别

污水处理过程复杂多变的运行工况以及系统脆弱的抗负荷冲击能力,常常导致污水处理厂运行目标难以实现,有效识别污水操作工况的变化对污水处理过程安全运行和操作优化十分重要。为增强未知样本分类可靠性,在概率极限学习机二分类基础上,将其扩展到多分类概率极限学习机方法(extreme learning machine)。该方法首先采用极限学习机建立污水处理过程实时变量和污水处理过程工况编码之间的预报模型,然后根据类别的输出预报值分别建立每个类训练样本潜在函数的均值,确定所有类的条件概率密度函数,非线性最小二乘辨识条件概率密度函数参数,最后根据贝叶斯原理计算所有类的后验概率,由后验概率最大值判别样本所属类别。以辽宁某城市污水处理厂实时数据为背景进行验证,实验结果表明多分类概率极限学习机分类的可靠性和准确性优于极限学习机分类方法。     

Process modeling and optimization of industrial ethylene oxide reactor by integrating support vector regression and genetic algorithm

This article presents an artificial intelligence‐based process modeling and optimization strategies, namely support vector regression–genetic algorithm (SVR‐GA) for modeling and optimization of catalytic industrial ethylene oxide (EO) reactor. In the SVR‐GA approach, an SVR model is constructed for correlating process data comprising values of operating and performance variables. Next, model inputs describing process operating variables are optimized using Genetic Algorithm (GAs) with a view to maximize the process performance. The GA possesses certain unique advantages over the commonly used gradient‐based deterministic optimization algorithms The SVR‐GA is a new strategy for chemical process modeling and optimization. The major advantage of the strategies is that modeling and optimization can be conducted exclusively from the historic process data wherein the detailed knowledge of process phenomenology (reaction mechanism, kinetics, etc.) is not required. Using SVR‐GA strategy, a number of sets of optimized operating conditions leading to maximized EO production and catalyst selectivity were obtained. The optimized solutions when verified in actual plant resulted in a significant improvement in the EO production rate and catalyst selectivity.     

Optimization of the N2 generation selectivity in aqueous nitrate reduction using internal circulation micro-electrolysis

The reduction of nitrate using internal circulation micro-electrolysis technology (ICE) was investigated. The effect of the reaction time, initial pH, Fe/C ratio, and aeration rate on the nitrate reduction was investigated using a single factor experiment. Based on the results of the single factor experiment, a response surface methodology (RSM) was applied to optimize the N₂ generation selectivity. The effects and interactions of three independent variables were estimated using a Box-Behnken design. Using the RSM analysis, a quadratic polynomial model with optimal conditions at pH=8.8, Fe/C=1:1, and an aeration rate of 30 L·min^-1 was developed by means of the regression analysis of the experimental data. Using the RSM optimization, the optimal conditions yielded a N₂ generation selectivity of 72.0%, which is in good agreement with experimental result (73.2%±0.5%) and falls within the 95% confidence interval (IC:66.8%-77.3%) of the model results. This indicates that the model obtained in this study effectively predicts the N₂ generation selectivity for nitrate reduction by the ICE process, thus providing a theoretical basis for process design.     

Modeling of poly(ethylene terephthalate) reactors: 5. A continuous prepolymerization process

A mathematical model for the continuous prepolymerization of BHET to PET, carried out in a series of stirred tank reactors, has been developed. The influence of process and operational variables on productivity, as well as the side-product formation (which controls the product quality), have been studied in a range as close to industrial practice as possible. The overall conclusions concerning the productivity profile, as well as some side products, appear to be substantiated from the available data in the open literature. The results of the mathematical model have been used to highlight the key process and operational variables that are likely to give the best productivity and product quality in industrial practice.     

考虑不同产品选择性目标的乙醇胺反应精馏塔模拟与优化

提出以环氧乙烷和液氨为原料,水为催化剂,反应精馏塔合成乙醇胺的工艺。分别以一乙醇胺（MEA）和二乙醇胺（DEA）的选择性最大为目标,探讨了在同一反应精馏塔中实现不同产物选择性目标的可行性和可达到的最大选择性。研究在Aspen Plus模拟软件上进行,通过考察操作压力、水进料量、进料氨烷比、再沸比、环氧乙烷进料位置等参数对反应精馏的影响规律,取得实现不同产物选择性目标的参数优化调节方法。研究表明,大的氨烷比、水进料量和再沸比有利于提高MEA选择性,小的氨烷比、水进料量和再沸比则有利于提高DEA选择性,在优化条件下,MEA选择性可达70.30%,DEA选择性可达41.89%。与文献方法比较,采用反应精馏合成乙醇胺具有明显的优越性和操作柔性。     

Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA

In this study, the effects of ultrasound irradiation on transesterification process and characteristics of the synthesized biodiesel were investigated. The study was divided into two parts. In the first part, response surface methodology (RSM) and Central Composite Design (CCD) were employed to design experiments, develop the regression model, and evaluate individual and interactive impacts of five independent operational variables. The obtained results were then predicted by an optimized artificial neural network-genetic algorithm (ANN-GA) algorithm. The estimated results were compared with the experimental results. In the second part of the work, the impact of ultrasound irradiation on the main characteristics of the synthesized biodiesel was investigated. The analysis of the operating conditions indicated that reaction temperature and MeOH:oil molar ratio were the most important variables on reaction yield. The experimental results showed that there was a change in the main properties of the synthesized palm oil biodiesel with the density changed by about 0.3 kg/m³, viscosity by 0.12 mm²/s, pour/cloud point by 1–2°C, and flash point by 5°C, depending on different combinations of operational parameters. Besides, the numerical optimization technique was employed to optimize process variables in order to obtain the maximum FAME content (reaction yield) along with the best properties using both RSM and ANN-GA techniques. The maximum reaction yields of 95.2% and 95.1% were predicted by the RSM and ANN-GA models, respectively, at the optimum conditions. The conditions predicted by RSM and ANN-GA proved to be feasible for modeling and optimizing transesterfication yield with an accuracy of 99.18% and 99.14% and biodiesel properties of 98.61% and 98.28%, respectively.     

Experimental study and simulation of a three-phase flow stirred bioreactor

In order to obtain the reasonable operating conditions and minimize the power consumption in the stirred bioreactor, the hydrodynamic experiments in the stirred bioreactor have been taken to obtain the basic data. Subsequently, an Eulerian model for the gas–liquid–solid three phase flow in the stirred bioreactor has been proposed and the CFD simulation has been conducted. By comparing the results of experiment and simulation, it can be concluded that the simulation results were consistent with the experimental data. The inner relationship between operating variables and indicators could be obtained by comparing the results of just suspension speed, gas holdup, power consumption and operational maps, further the reasonable operating conditions could be also determined under the minimum power consumption. The operational maps could provide the theoretical foundation for industrial application of the gas–liquid–solid stirred bioreactors under the low solid concentration(no more than 20 wt%).     

Modeling of poly(ethylene terephthalate) reactors. I. A semibatch ester interchange reactor

A comprehensive model for a semibatch ester interchange reactor has been developed with a view to investigate the effect of various process and operational variables on the DMT conversion rate as well as the by-product formation. The influence of important variables such as EG-to-DMT ratio, catalyst concentration, and operational variables such as temperature and pressure has been considered. Definite conclusions concerning the choice of the desirable range of process and operational variables to maximize productivity and minimize by-product formation have been reached.     

Modeling and simulation of the drying of thin sheets in a continuous infrared dryer

The model gives the temperature and moisture distributions of the air, and of the moist sheet, as a function of time and distance in the dryer. The influence of the sheet's velocity and that of the radiant energy on the dryer performance as well as the effect of the moisture content of the entering sheet have been studied. A set of 27 experiments was carried out using the infrared dryer in order to calibrate the model. In these, the following three variables each had three operational levels: web velocity, initial web moisture and heating power. The model predictions agreed very well with the experimental data. Model predictions using arithmetic averages for the parameters, and parameters correlated with operational variables, are also presented and discussed.     

Synthesis of adipic acid through oxidation of K/A oil and its kinetic study in a microreactor system

Synthesis of adipic acid (AA) through the oxidation of cyclohexanol and cyclohexanone (K/A oil) with nitric acid was conducted in a capillary microreactor system. Effects of the temperature, the nitric acid concentration, the volumetric flow rate ratio of nitric acid to K/A oil, and the capillary length on the selectivity and the product yield were investigated systematically to achieve optimal reaction conditions. Notably, a high yield of AA (i.e., 90%) was achieved just in 6 seconds at 85°C with the use of 55 wt% nitric acid. Gas components produced in this oxidation process and its total volumetric flow rate were determined under various operational conditions, which was beneficial for reaction mechanism characterization and process optimization. Finally, a kinetic model was established, which was of crucial theoretical significance and practical value for optimizing the reactor design and better understanding such fast and highly exothermic multiphase processes with abundant gas production.     

聚酯(PET)反应过程研究Ⅴ预缩聚反应过程分析和反应动力学研究

对乙二醇和对苯二甲酸预缩聚反应过程进行了分析，把该过程分解为反应动力学和反应器内各种传质，对预缩聚反应过程的反应动力学进行了实验研究。得到了不同温度下的反应速率及其参数     

Drying of Carrots in a Fluidized Bed. II. Design of a Model Based on a Modular Neural Network Approach

The present paper deals with the design of a neural network type model for drying of carrots, which includes the associated transport mechanisms of the process. The model uses the operational variables and the time as input parameters. Two sub-layers of linear and sigmoidal nodes make up the hidden layer, to represent the external and internal resistances to the diffusion of water vapors during the drying process. The single output node weights the contribution of each mechanism of the drying process to predict the exit moisture content of the product. This model was used to predict the drying of carrot particles in a mechanically fluidized bed dryer reported in a previous paper [Reyes, A.; Alvarez, P.; Marquardt, F. Drying of carrots in a fluidized bed: I.- effects of drying conditions and modeling. Drying Technology 2002, 20 (7), 1463-1483.]. Simulated drying curves obtained with this model fits adequately the curves determined experimentally for the most operation conditions, which would indicate that this model is appropriate to be used for rough estimations in the design, the selection of optimal operational conditions, and the scaling up of dryers.