Off-line optimization and control for real time integration of a three-phase hydrogenation catalytic reactor

In order to develop and test the integration procedure, in this paper a real time process integration involving the optimization and control of the process is presented, in this case, with the two-layer approach. The used optimization algorithms were Levenberg–Marquardt and SQP that solve a non-linear least square problem subject to bounds on the variables. The two-layer approach is a hierarchical control structure where an optimization layer calculates the set points and manipulated variables to the advanced controller, which is based on the dynamic matrix control with constraints (QDMC). The non-isothermal dynamic model of the three-phase slurry catalytic reactor with appropriate solution procedure was utilized in this work (Vasco de Toledo, E. C., Santana, P. L., Maciel, M. R. W., & Maciel Filho, R. (2001). Dynamic modeling of a three-phase catalytic slurry reactor. Chemical Engineering Science, 56, 6055–6061). The model consists on mass and heat balance equations for the catalyst particles as well as for the bulk phases of gas and liquid. The model was used to describe the dynamic behavior of hydrogenation reaction of o-cresol to obtain 2-methil-cyclohexanol, in the presence of a catalyst Ni/SiO₂.     

气流床气化炉反应模型在实时优化(RTO)中的应用

以多喷嘴对置式气化炉为研究对象,采用未反应芯收缩核模型为联泓公司煤制甲醇装置气流床气化过程进行建模,采用ROMeo软件实现全厂实时优化。结果表明:气化炉的模拟结果与工厂运行数据基本吻合,气化炉有效气CO和H2组分工厂数据与模拟结果的相对误差均小于2%;ROMeo的模拟、数据整定和优化等功能保证了在线实时优化的成功实施,避免了气化炉氧气的过量消耗,可确保合成气中有效气(H₂和CO)的产出和分布最有利于下游生产;可使甲醇产量从123740 kg/h增加到124190 kg/h,甲醇纯度从95.4%提高到95.7%。经核算,实时优化可使联泓公司的收益提高1.6%,效益增量达800万元/a。     

Membrane/sorption-enhanced methanol synthesis process: Dynamic simulation and optimization

In this study, a dynamic mathematical model of a Membrane-Gas-Flowing Solids-Fixed Bed Reactor (Membrane-GFSFBR) with in-situ water adsorption in the presence of catalyst deactivation is proposed for methanol synthesis. The novel reactor consists of water adsorbent and hydrogen-permselective Pd-Ag membrane. In this configuration feed gas and flowing adsorbents are both fed into the outer tube of the reactor. Contact of gas and fine solids particles inside packed bed results in selective adsorption of water from methanol synthesis which leads to higher methanol production rate. Afterwards, the high pressure product is recycled to the inner tube of the reactor and hydrogen permeates to the outer tube which shifts the reaction towards more methanol production. Dynamic simulation result reveals that simultaneous application of water adsorbent and hydrogen permeation in methanol synthesis process contributes to a significant enhancement in methanol production. The notable advantage of Membrane-GFSFBR is the continuous adsorbent regeneration during the process. Moreover, a theoretical investigation has been performed to evaluate the optimal operating conditions and to maximize the methanol production in Membrane-GFSFBR using differential evolution (DE) algorithm as a robust method. The obtained optimization result shows there are optimum values of inlet temperatures of gas phase, flowing solids phase, and shell side under which the highest methanol production can be achieved.     

冷冻干燥过程的数学模型

本文以物料衡算和热量衡算为基础，作适当的简化，导出了所需参数较少，但能准确地预测冷冻干燥全过程时间的数学模型，通过对胡萝卜和土豆的实验研究，检验了模型的适用性和准确性。     

Simultaneous hybrid modeling of a nosiheptide fermentation process using particle swarm optimization

Hybrid modeling approaches have recently been investigated as an attractive alternative to model fermentation processes. Normally, these approaches require estimation data to train the empirical model part of a hybrid model. This may result in decreasing the generalization ability of the derived hybrid model. Therefore, a simulta-neous hybrid modeling approach is presented in this paper. It transforms the training of the empirical model part into a dynamic system parameter identification problem, and thus al ows training the empirical model part with only measured data. An adaptive escaping particle swarm optimization (AEPSO) algorithm with escaping and adaptive inertia weight adjustment strategies is constructed to solve the resulting parameter identification problem, and thereby accomplish the training of the empirical model part. The uniform design method is used to determine the empirical model structure. The proposed simultaneous hybrid modeling approach has been used in a lab-scale nosiheptide batch fermentation process. The results show that it is effective and leads to a more consistent model with better generalization ability when compared to existing ones. The performance of AEPSO is also demonstrated.     

Dynamic optimization of 1,3-propanediol fermentation process: A switched dynamical system approach

This paper considers a dynamic optimization problem (DOP) of 1,3-propanediol fermentation process (1,3-PFP). Our main contributions are as follows. Firstly, the DOP of 1,3-PFP is modeled as an optimal control problem of switched dynamical systems. Unlike the existing switched dynamical system optimal control problem, the state-dependent switching method is applied to design the switching rule. Then, in order to obtain the numerical solution, by introducing a discrete-valued function and using a relaxation technique, this problem is transformed into a nonlinear parameter optimization problem (NPOP). Although the gradient-based algorithm is very efficient for solving NPOPs, the existing algorithm is always trapped in a local minimum for such problems with multiple local minima. Next, in order to overcome this challenge, a gradient-based random search algorithm (GRSA) is proposed based on an improved gradient-based algorithm (IGA) and a novel random search algorithm (NRSA), which cannot usually be trapped in a local minimum. The convergence results are also established, and show that the GRSA is globally convergent. Finally, a DOP of 1,3-PFP is provided to illustrate the effectiveness of the GRSA proposed by this paper.     

露天矿剥采进度计划优化研究现状及发展趋势

对露天矿剥采进度优化研究的现状做了概括，对国内外有代表性的研究方法及数学模型（整数规划、目标规划、动态规划、系统模型法等）进行介绍与评价，并对该领域研究发展趋势（如人工智能法、综合方法）做了分析。     

Mathematical model and optimization of drying process for a through-circulation dryer

A mathematical model of a through-circulation dryer is proposed. This model approximates the drying time of constantrate drying and fallingrate drying processes. Based on the proposed model, the optimal drying conditions of maximizing the drying production rate in a continuous through-circulation dryer are obtained. The drying production rate, in terms of the independent operating variables, is a nonlinear objective function, and is optimized under the nonlinear inequality constraint functions by a differential algorithm.     

Energy and drying time optimization of convective drying: Taguchi and LBM methods

In this study, a novel method for numerical simulation of drying is proposed and the process is optimized by Taguchi method. A 2D numerical solution is performed to analyze coupled heat and mass transfer occurring during drying of a rectangular moist object. The dryer section and the moist object are conjugately simulated where the coupled heat and mass transfer equations are solved together. The lattice Boltzmann method is employed to solve hydrodynamic, heat, and mass transfer equations. This study applied the Taguchi method to determine optimum conditions for drying so as to minimize the drying time and energy consumption. The control factors included temperature, air velocity, and thickness ratio (the moist object thickness to channel width). The following optimal conditions were obtained: temperature (T?=?60?°C), velocity (V?=?0.1 m/s), and thickness ratio (TR =0.1). The results of numerical solution are then compared to the measured data available in the literature, presenting a reasonable agreement.     

Modification and optimization of benzene alkylation process for production of ethylbenzene

In this paper, an industrial ethylbenzene production unit has been simulated and the results are compared against five-day experimental data. According to prevailing unit condition, i.e. recycled ratio of benzene, benzene selectivity, and energy consumption, the unit is not working under its optimum conditions for minimum cost of ethylbenzene production. In the current design, high amount of benzene recycle (6:1) causes to have an additional cost due to fractionation of ethylbenzene from benzene. A new approach is proposed to modify the benzene alkylation process and reduce the unit's energy consumption. In the newly designed scheme, two double-bed alkylation reactors converted into four single-bed reactors. The amount of injected ethylene, alkylation reactors temperature, and recycled stream are regulated as adjustable parameters for the optimization of the process. In the modified process, the reflux ratio reduced to 1.87 and the benzene selectivity increased. The optimized process shows a considerable decrease in the unit's energy consumption in compare to the current process. Also, the mass fraction of ethylbenzene would reach to 99.12% of purity before entering to the transalkylation reactor for further purification. Therefore, if the presented purity is acceptable for the final application, the transalkylation reactor could be eliminated from the new design.     

Real‐time economic model predictive control of nonlinear process systems

Closed‐loop stability of nonlinear systems under real‐time Lyapunov‐based economic model predictive control (LEMPC) with potentially unknown and time‐varying computational delay is considered. To address guaranteed closed‐loop stability (in the sense of boundedness of the closed‐loop state in a compact state‐space set), an implementation strategy is proposed which features a triggered evaluation of the LEMPC optimization problem to compute an input trajectory over a finite‐time prediction horizon in advance. At each sampling period, stability conditions must be satisfied for the precomputed LEMPC control action to be applied to the closed‐loop system. If the stability conditions are not satisfied, a backup explicit stabilizing controller is applied over the sampling period. Closed‐loop stability under the real‐time LEMPC strategy is analyzed and specific stability conditions are derived. The real‐time LEMPC scheme is applied to a chemical process network example to demonstrate closed‐loop stability and closed‐loop economic performance improvement over that achieved for operation at the economically optimal steady state. © 2014 American Institute of Chemical Engineers AIChE J, 61: 555–571, 2015     

Reconstitute tobacco product drying model

Drying is one of the most energy-inrensive and frequently used professes in the tobacco industry. In the present work, heat and mass transfer phenomena in drying sheet materials with impinging air flow are analyzed. A blended leaf (BL) drying model is developed and validated to predict the drying behavior of the reconstitute tobacco product. A numerical method of line technique [Schiesser. 1991] was used to solve the coupled differential equations governing the drying process. This model has been successfully applied to simulate BL drying processes in the pilot plant and the BL. plant. The present model provides a relatively last and efficient way to improve process performance, increase plant productivity, and optimize energy utilisation. With this model, the number of trials necessary to achieve the objectives is reduced, in other words, a large amount of time, money, and manpower is saved. The model results are also helpful in studying the drying behavior of reconstitute tobacco products and understanding the effect of dryer profiles on the sheet strength and subjective results.     

基于累积损伤过程的随机需求下订购时间间隔模型

将累积损伤过程运用于固定订购时间间隔模型中,把订单的出现看成库存系统受到的冲击,把订单产生的随机需求量看成给库存系统的冲击带来的损伤,以求得最低期望单位时间成本为目标,建立C(T,K)成本模型,最后用一个算例展示了当成本最低时的最优订购时间间隔和初始库存水平。     

高铝衬砖的工艺控制

应用主成分分析法（ＰＣＲ），探讨了高铝衬砖生产工艺过程中组成、粒度、压力等因素对砖坯烧成的影响。建立了它们之间的数学模型。     

Post-combustion CO2 capture process: Equilibrium stage mathematical model of the chemical absorption of CO2 into monoethanolamine (MEA) aqueous solution

This paper deals with the modeling and optimization of the chemical absorption process to CO₂ removal using monoethanolamine (MEA) aqueous solution. Precisely, an optimization mathematical model is proposed to determine the best operating conditions of the CO₂ post-combustion process in order to maximize the CO₂ removal efficiency. Certainly, the following two objective functions are considered for maximization: (a) ratio between the total absorbed CO₂ and the total heating and cooling utilities and (b) ratio between total absorbed CO₂ and the total amine flow-rate.Temperature, composition and flow-rate profiles of the aqueous solution and gas streams along the absorber and regenerator as well as the reboiler and condenser duties are considered as optimization variables. The number of trays or height equivalent to a theoretical plate (HETP) on the absorber and regenerator columns as well as the CO₂ composition in flue gas are treated as model parameters. Correlations used to compute physical-chemical properties of the aqueous amine solution are taken from different specialized literature and are valid for a wide range of operating conditions. For the modeling, both columns (absorber and regenerator) are divided into a number of segments assuming that liquid and gas phases are well mixed.GAMS (General Algebraic Modeling System) and CONOPT are used, respectively, to implement and to solve the resulting mathematical model.The robustness and computational performance of the proposed model and a detailed discussion of the optimization results will be presented through different case studies. Finally, the proposed model cannot only be used as optimizer but also as a simulator by fixing the degree of freedom of the equation system.     

小直径钻头层次优选AHP模型的确立及应用

钻井中,钻头费用在1口井的总投资里所占的比例一般不大,但钻头的使用效果会直接影响整个钻井。由于小直径钻头的特殊性,轴强度低,落井后不易打捞,以及转速、钻压、井下工具等因素的限制,小直径钻头的优选较常规尺寸更重要,在进行小直径钻头评价和优选时,每种类型的小直径钻头都包含有各类技术经济指标,很多指标既相互依赖,又相互矛盾,因而给决策、评价带来很大困难。另外,决策人员有时很容易受某一具体指标的影响,常常会单凭一项经济或技术指标而肯定或否定某一类型的钻头。为此,本文对中原油田小井眼(458″)钻头尝试运用综合评价法中的层次分析(AHP,A nalyticH ierarchy Process)理论进行评价与优选。