复杂第III类反应体系反应器网络综合

在第I, II类反应体系反应器网络综合研究的基础上,对第III类复杂反应体系的反应器网络综合问题进行求解,基于第III类反应体系的阶段性特征,提出反应系踪、瞬时反应物、瞬时产物及瞬时选择性的概念,发展了反应器网络综合的分段导数分析法,提出了分段导数分析的三步策略和分析步骤. 通过对两个实例的分析说明了进行第三类反应体系的反应器网络综合的方法. 结果表明,所提出的分段导数分析法不但简单可靠,且通过优化可获得最优反应器网络结构.     

Model-based,thermo-physical optimisation for high olefin yield in steam cracking reactors

The steam cracking practice seems to have reached a stage of maturity which makes it increasingly difficult to improve ethylene yield. In order to determine if there is still scope for yield improvements it is helpful to know what the optimal reaction conditions for the steam cracking process are. This work presents a model-based synthesis approach that enables to determine the optimal thermal and physical reaction conditions for a particular feed, maximising olefin yield. A distributive reaction-mixing synthesis model has been combined with an industrially proven large kinetic scheme, SPYRO^®, which contains over 7000 reactions between 218 molecular and 27 radical species. The model combination allows optimising the following degrees of freedom with respect to olefin yield: feed distribution, product removal, macro-mixing, along a reaction volume coordinate. The reaction temperature upper limit is put at 1300 K, exceeding the current (metallurgical) bound by 100 K. For the cracking of ethane a linear-concave unconstrained temperature profile with a maximum temperature of ∼1260 K proves optimal which is lower than allowed while all ethane should be supplied at the entrance of the reaction volume. For propane and heavier feedstocks an isothermal profile at the upper temperature bound, with dips at the beginning and the middle of the reaction coordinate is optimal, while distribution of the hydrocarbon feed along the reactor coordinate results in higher yields. The theoretical maximum achievable ethylene yield for ethane cracking is found to be 66.8 wt% while in conventional cracking typically 55 wt% is considered to be the maximum value. This optimum is constrained by the pressure which is at its lower bound. The resulting residence time is in the same order as with current technology for ethane cracking. For the more heavy feedstocks these times are one order of magnitude smaller which will be a challenge for designing.     

A systematic generation of reactor designs: I. Isothermal conditions

A new method is proposed for systematic generation of conceptual design of reactor networks. Given feed compositions and a kinetic model, the objective is to find the optimal mixing structure and feed distribution. The method aims at finding the optimal sequence and sizes of ideal reactors and the optimal addition of extra feed streams along the reactor path. The total reaction time is calculated so as to maximize the space time yield subject to a minimum yield of the key product component. The method does not have any limitations with respect to the number of components or reactions. A new model formulation is proposed that comprises both CSTR and PFR model equations and the design problem is formulated as an optimal control problem. In this paper, only isothermal conditions are considered.     

反应器网络综合三分布参数通用模型

提出了一种应用于反应器网络综合的三分布参数通用模型 .3个分布参数分别是侧线进料、侧线循环和侧线采出参数 ,这些参数能影响反应器网络内部的浓度和停留时间分布 ,所以由它们构成的通用模型具有简捷有效的特点 .基于此模型可将反应器网络集成转化成一个优化问题 ,通过有限元正交配置将原来含有微分方程的优化模型转化为非线性优化问题 ,优化计算后得到最优分布参数 .从案例研究可以看出 ,侧线进料、循环和采出策略能较全面地反映在不同动力学和优化目标函数下的最优反应器网络特征 ,并进而简化为工业可行的反应器网络     

Staging of the Fischer‐Tropsch Reactor with a Cobalt‐Based Catalyst

A method for systematic reactor design, described by Hillestad [1], is applied to the Fischer‐Tropsch synthesis. The reactor path is sectioned into stages and design functions are optimized to maximize an objective function. Two different objective functions are considered: the yield of wax and a measure of the profitability. With the chosen kinetic model [2] and the path temperature constrained by 240 °C, staging of the Fischer‐Tropsch synthesis based on the first criteria will increase the yield of wax. By introducing the cost of heat transfer area in the objective function, the total heat transfer area requirement of a two‐stage reactor is significantly less than of a single‐stage reactor.     

Optimal synthesis of Fenton reactor networks for phenol degradation

There is an increasing need to treat effluents contaminated with phenol with advanced oxidation processes (AOPs) to minimize their impact on the environment as well as on bacteriological populations of other wastewater treatment systems. One of the most promising AOPs is the Fenton process that relies on the Fenton reaction. Nevertheless, there are no systematic studies on Fenton reactor networks. The objective of this paper is to develop a strategy for the optimal synthesis of Fenton reactor networks. The strategy is based on a superstructure optimization approach that is represented as a mixed integer non-linear programming (MINLP) model. Network superstructures with multiple Fenton reactors are optimized with the objective of minimizing the sum of capital, operation and depreciation costs of the effluent treatment system. The optimal solutions obtained provide the reactor volumes and network configuration, as well as the quantities of the reactants used in the Fenton process. Examples based on a case study show that multi-reactor networks yield decrease of up to 45% in overall costs for the treatment plant.     

A kinetic modelling study of ethane cracking for optimal ethylene yield

Current generation steam cracking plants are considered to be mature. As a consequence it is becoming more and more important to know whether the underlying mechanistic cracking process offers still scope for further improvements. The fundamental kinetic limits to cracking yields have recently been researched in detail for different feed stocks with a new synthesis reactor model, d-RMix, incorporating a large scale mechanistic reaction scheme, SPYRO^® [M.W.M. van Goethem, S. Barendregt, J. Grievink, J.A. Moulijn, P.T.J. Verheijen “Model-based, thermo-physical optimisation for high olefin yield in steam cracking reactors”, Chemical Research and Engineering Developments 88 (2010) 1305–1319]. Mathematical optimization revealed for ethane cracking a maximum ethylene yield of about 67 wt%. with a linear-concave optimal temperature profile along the reaction coordinate with a maximum temperature between 1200 and 1300 K. Further mechanistic analysis of these results showed that the linear-concave shape not only suppresses the successive dehydrogenation and condensation reactions of ethylene, but mainly reduces the role of the ethane initiation reaction to form two methyl radicals.     

基于二维传递模型的反应器网络综合

反应器网络综合的任务在于寻求适宜的反应器类型、尺寸及反应单元间的连接关系并确定各反应器的操作条件,其研究方法主要包括超级结构法和目标法,采用的基本单元均为一维理想模型。文中同时考虑传质、传热、流体流动以及反应动力学,通过偏微分方程描述轴向及径向上的温度、浓度分布,建立了二维反应器模型。基于该二维传递模型,采用状态空间构建反应器网络,并以年度总费用为目标函数评价反应器系统的经济性。最后,以提出的模型对环氧丙烷反应器网络进行了优化设计,实例验证了方法的有效性。     

基于目标函数瞬时值的反应器网络综合方法

反应器网络综合是化工过程集成的关键问题之一,但求解过程十分复杂。提出了目标函数瞬时值的概念,并研究了利用目标函数瞬时值曲线所对应的面积进行反应器网络综合的方法。以两个复杂反应为例说明了该方法的应用并和国内外文献进行了对比。从案例研究可以看出,本方法能够得到最优反应器网络,也避免了求解大规模的非线形最优化问题,也克服了可得区法维数的限制,具有几何直观的特点。     

A case study for reactor network synthesis: the vinyl chloride process

A key objective of the integrated reactor network synthesis approach is the development of waste minimizing process flowsheets (Lakshmanan & Biegler, 1995). With increasing environmental concerns in process design, there is a particularly strong need to maximize conversion to product and avoid generation of wasteful byproducts within the reactor network. This also avoids expensive treatment and separation costs downstream in the process. In this study, we present an application of the mixed integer nonlinear programming (MINLP)-based reactor network synthesis strategy developed by Lakshmanan and Biegler (1996a). Here we focus on applying these reactor network synthesis concepts to the vinyl chloride monomer production process. Vinyl chloride is currently produced by a balanced production process from ethylene, chlorine and oxygen with three separate reaction sections: oxychlorination of ethylene; direct chlorination of ethylene; and pyrolysis of ethylene dichloride. The hydrogen chloride produced in the pyrolysis reactor is used completely in the oxychlorination reactor. Byproducts such as chlorinated hydrocarbons and carbon oxides are generated by these reaction sections. These are studied using reaction kinetic models for the three reaction sections. The case study results in optimal reactor networks that improve the conversion of ethylene to vinyl chloride and minimize the formation of byproducts. These results are used to generate an improved flowsheet for the production of vinyl chloride monomer. Moreover, an overall profit maximization, that includes the effect of heat integration, is presented and a set of recommendations that improve the selectivity of vinyl chloride production are outlined. Finally, the optimal reactor structures, overall conversion and annual profit are shown to be only mildly sensitive with respect to small changes in the kinetic parameters.     

物质封闭循环的反应路径综合方法

为了达到目标废物的零排放,综合物质封闭循环的反应路径方案很有意义,这一问题往往通过多产品的联产来实现. 在相关物质所构成的简单计量系数反应方程网络的基础上,构造优化数学模型,得出了最优的物质封闭循环的反应路径.     

Optimization of ODHE membrane reactor based on mixed ionic electronic conductor using soft computing techniques

This work presents the optimization of the operating conditions of a membrane reactor for the oxidative dehydrogenation of ethane. The catalytic membrane reactor is based on a mixed ionic–electronic conducting material, i.e. Ba_0.5Sr_0.5Co_0.8Fe_0.2O_δ−3, which presents high oxygen flux above 750 °C under sufficient chemical potential gradient. Specifically, diluted ethane is fed into the reactor chamber and air (or diluted air) is flushed to the other side of the membrane. A framework based on Soft Computing techniques has been used to maximize the ethylene yield by simultaneously varying five operation variables: nominal reactor temperature (Temp); gas flow in the reaction compartment (QHC); gas flow in the oxygen-rich compartment (QAir); ethane concentration in the reaction compartment (%C₂H₆); and oxygen concentration in oxygen-rich compartment (%O₂). The optimization tool combines a genetic algorithm guided by a neural network model. This shows how the neural network model for this particular problem is obtained and the analysis of its behavior along the optimization process. The optimization process is analyzed in terms of: (1) catalytic figures of merit, i.e., evolution of yield and selectivity towards different products and (2) framework behavior and variable significance. The two experimental areas maximizing the ethylene yield are explored and analyzed. The highest yield reached in the optimization process exceeded 87%.     

A sensitivity analysis and multi-objective optimization to enhance ethylene production by oxidative dehydrogenation of ethane in a membrane-assisted reactor

Owing to the importance of process intensification in the natural gas associated processes, the present contribution aims to investigate the production of an important natural gas downstream product in an improved system. Accordingly, a membrane-assisted reactor for the oxidative dehydrogenation of ethane is presented. The presented system includes a membrane for axial oxygen dosing into the reaction side. Such a strategy would lead to optimum oxygen distribution along the reactor length and prevention of hot spot formation as well. A feasibility study is conducted by developing a validated mathematical model composed of mass and energy balance equations. The effects of various operating variables are investigated by a rigorous sensitivity analysis. Then, by applying the genetic algorithm, a multi-objective optimization procedure is implemented to obtain the optimum operating condition. Considerable increase in the ethane conversion and ethylene yield are the advancements of membrane-assisted oxidative dehydrogenation reactor working under the optimum condition. More than 30% increase in the ethane conversion is obtained. Furthermore, the ethylene yield is enhanced up to 0.45.     

反应器网络多目标综合优化

通过反应系统综合优化获得经济效益好、对环境友好的反应系统是大多化工厂提高全流程整体经济和环境性能的重要手段。反应器网络综合优化方法主要包括可得区法、导数分析法、超结构优化法、目标类法、经验推断法和分布参数法等,然而却很少有文献报道对反应器网络进行多目标综合优化。由于过程中往往存在多个相互冲突的目标函数,所以仅仅依靠单目标对反应器网络进行综合优化已显得不合适。本文采用分布参数法建立多目标优化模型,目标函数为经济最大化和环境影响最小,并采用非支配排序基因算法(NSGA-Ⅱ)进行优化得到Pareto最优解集。     

Synthesis of reactor networks in overall process flowsheets within the multilevel MINLP approach

This paper presents the superstructure-based mixed-integer non-linear programming approach to the synthesis of reactor networks in an equation-oriented environment. The model comprises a general superstructure in which the exact formulation of the recycle reactor (RR) and a continuous stirring tank reactor (CSTR) are embedded so as to enable a different feeding (cross flow, side stream), recycling and bypassing. The reactor arrangement is capable of representing several reactor systems such as a pure CSTR, a pure plug flow reactor, pure RR, their combinations and also a cross flow reactor. The superstructure is suitable either for an isothermal or non-isothermal, simple or complex reactor network. With the multilevel-hierarchical strategy, it is possible to postulate the superstructure at different levels of representation of flowsheet alternatives. Therefore, the superstructure is optimized more effectively and reliably. The approach has been applied to a complex non-isothermal reaction problem — an industrial example of the production of allyl chloride.     

Heterogeneous catalytic reactor design with optimum temperature profile II: application of non-uniform catalyst

A new methodology has been developed to design non-isothermal, non-adiabatic heterogeneous catalytic fixed bed and tubular reactors with optimal temperature profiles inside a reactor. Catalyst characteristics such as pellet diameter, shape and activity distributions inside a pellet are considered simultaneously for reactor design. Various types of non-uniform activity distributions inside a pellet are modelled and optimised for the maximisation of an objective such as yield or selectivity. Dirac-δ, layered and general non-uniform distribution profiles such as egg-shell, egg-yolk and middle peak distributions are applied for the reactor design. The research demonstrates that different catalyst distribution profiles can approach the optimum performance. Whilst it is known that the Dirac-δ profile (and its step-function equivalent) always gives the best performance for clean catalyst, other profiles can approach this performance and might offer advantages in catalyst manufacture and under degraded conditions. A profile-based synthesis approach is applied to generate various shapes of activity profiles for multiple sections along the reactor during the optimisation of non-uniform catalyst pellets. A case study with the ethylene oxidation process illustrates that the catalyst characteristics, such as activity distribution profiles inside a pellet, sizes and shapes can be manipulated to control the temperature through the reactor very effectively, leading to significant improvements in selectivity or yield. The non-uniform catalyst pellet is further applied to various reactor configurations such as inert mixing and side stream distributions. This work is the first to consider all of these effects simultaneously.     

SMCA—the real optimal operation of a multistage adiabatic fixed-bed reactor

A general rule and a straightforward approach of the real optimal operation of a multistage adiabatic fixed-bed reactor (MAFBR) for a single reaction system, namely, the stagewise maximum conversion approach (SMCA), were derived based on the analysis of the operation of a Fauser—Montecatini type, five-stage ammonia synthesis reactor. The SMCA can be implemented in reactors which have ageing catalysts and maldistributed gas. The SMCA has been applied efficiently to industrial SO₂ oxidation and NH₃ synthesis plants. Suggestions on the design of a new MAFBR are made.     

Systematic staging in chemical reactor design

The foundation and implementation of a method for systematic reactor design is described. The reactor path is sectioned into stages where each stage is designed so as to optimize an overall objective. This is a further development of a previously proposed method for designing chemical reactors (Hillestad, 2004, Hillestad, 2005). Reactants pass through a series basic operations or functions to form the desired products. The basic operations are represented by design functions on the path volume. The design functions are fluid mixing (dispersion), distribution of extra feed points, distribution of heat transfer area and coolant temperature, catalyst dilution distribution and more. The conceptual reactor design problem is solved as an optimal control problem. A direct method is applied where both the design functions and the state variables are discretized. The realization of the optimization is a staged process string of multi-functional units. A kinetic model of the gas phase methanol synthesis is used as an example. By applying the method on the model, a staged reactor design with less heat transfer area and higher production is possible.     

Genetic-based multi-objective optimization of alkylation process by a hybrid model of statistical and artificial intelligence approaches

The purpose of this research is to find the optimal operating point in the production process of the cumene. Therefore, the production process was optimized through statistical and genetic algorithm-based methods. The performance of an alkylation reactor was optimized through maximizing the yield of cumene production. Response surface methodology (RSM) with design type of central composite was applied for design of experiment, modelling, and optimizing the process. The analysis of variance (ANOVA) was performed for finding the important operative parameters as well as their effects. The effects of three parameters including temperature, reactor length, and pressure on the alkylation process were investigated. Further, two types of feed-forward neural network were applied to model the alkylation reactor. To develop the neural network model, leave-one-out method was used. The best prediction performance belonged to a fitting network with 2 and 8 neurons in the hidden layer, respectively. This model was used for optimizing the performance of the alkylation reactor. The statistical and artificial intelligence systems were capable of prediction of cumene production yield in different conditions with R² of 0.9098 and 0.9986, respectively. Genetic algorithm-based optimization was performed by the developed neural network model. The maximum accessible value of cumene production yield was 0.7771, which can be achieved when the temperature, length of reactor, and column pressure are 160°C, 2 m, and 4000 kPa, respectively. By finding the optimal operating point in the cumene production process, capital cost, energy consumption, and other operating costs can be significantly reduced.