Batch Reactive Distillation Research Articles

State estimation and inferential control for a reactive batch distillation column

An optimal reflux ratio profile is obtained for a reactive batch distillation system utilizing the capacity factor as the objective function in a nonlinear optimization problem. Then, an Artificial Neural Network (ANN) estimator system, which utilizes the use of several ANN estimators, is designed to predict the product composition values of the distillation column from temperature measurements inferentially. The network used is an Elman network with two hidden layers. The designed estimator system is used in the feedback inferential control algorithm, where the estimated compositions and the reflux ratio information are given as inputs to the controller to see the performance of the ANN. In the control law, a scheduling policy is used and the optimal reflux ratio profile is considered as pre-defined set-points. It is found that, it is possible to control the compositions in this dynamically complex system by using the designed ANN estimator system with error refinement whenever necessary.

Dynamic simulation and nonlinear control of a rigorous batch reactive distillation

This work deals with the dynamics and control of a high-purity batch distillation column with chemical reaction. A heterogeneous esterification reaction between the acetic acid and butanol takes place to produce butyl acetate. The process model is formulated considering variable liquid holdup, UNIQUAC model for thermodynamic property predictions, nonlinear Francis weir formula for tray hydraulics, pseudohomogeneous model to represent the reaction kinetics and rigorous energy balance. A structured and simple iterative approach is devised to compute the vapor flows with the fast convergence, under the rigorous energy balance. The representative column is treated with a distillate policy based on which, the lightest product, water is removed as distillate at the starting of production phase. As a consequence, the column gets progressively richer with the main product, butyl acetate. In addition, almost complete conversion of the limiting reactant is achieved. In order to maintain the product purity at the top, a nonlinear generic model controller (GMC) in two different forms has been proposed. Finally, a comparative closed-loop performance is addressed. It is shown that the control scheme, along with the effective distillate strategy, leads to almost complete conversion of ingredients and high-purity products.

A convenient preparation of ethoxymethoxymethane and its effect on the solubility of methanol/gasoline blends

Ethoxymethxoymethane (EMM) was conveniently prepared by acetalization of aqueous formaldehyde with methanol and ethanol in a batch reactive distillation mode using a cation-exchange resin catalyst for the first time. EMM was found to be a significant cosolvent of methanol/gasoline blends.

Chance constrained optimization of process systems under uncertainty: I. Strict monotonicity

An approach for chance constrained programming of large-scale nonlinear dynamic systems is presented. The stochastic property of the uncertainties is explicitly considered in the problem formulation in which some input and state constraints are to be complied with predefined probability levels. The method considers a nonlinear relation between the uncertain input and the constrained variables. It also involves efficient algorithms so as to compute the probabilities and, simultaneously, the gradients through integration by collocation in finite elements. The formulation of single or joint probability limits incorporates the issue of feasibility and the contemplation of trade-off between robustness and profitability regarding the objective function values. The approach is relevant to all cases when uncertainty can be described by any kind of joint correlated multivariate distribution function. Thus, chance constrained programming is a promising technique in solving optimization problems under uncertainty in system engineering. The potential and the efficiency of the presented systematic methodology, which assumes a strict monotonic relationship between the uncertain input and the uncertain constrained output, are illustrated with application to a reactive batch distillation processes under uncertainty.

A generic feasibility study of batch reactive distillation in hybrid configurations

AbstractA new graphical feasibility method is developed to investigate batch reactive distillation processes in middle vessel column. The suggested methodology can deal with fully reactive, nonreactive, and complex column configuration. A new formulation is suggested to describe the composition profiles in the reactive sections. Its application has made possible to develop a generic feasibility methodology containing the same model equations independently of the presence or absence of reaction. By combining the reactive and nonreactive models, not only the fully reactive and fully nonreactive but also hybrid configurations can be studied. Feasibility criteria related to the hybrid configurations are also presented. Application of the new methodology is demonstrated on the production of ethyl acetate in batch reactive distillation. Five configurations are found feasible; pure EtOAc is produced as distillate, and pure H2O is produced at the bottom. In each case, continuous feeding of AcOH is necessary. © 2009 American Institute of Chemical Engineers AIChE J, 2009

Nonlinear state estimation and control of a batch reactive distillation

This paper deals with the advanced adaptive control of a batch reactive distillation (RD) column for the production of ethyl acetate. The nonlinear adaptive control law consists of the generic model controller (GMC) and an adaptive state estimator (ASE). In the first part of the present work, the design approach of the ASE scheme in two different forms, namely ASE1 and ASE2, has been addressed for a batch reactive rectifier. The predictor model of both the ASE estimators includes only a component mole balance equation around the condenser-reflux drum system and an extra state equation having no dynamics, and therefore, there is a large process/predictor mismatch. In presence of this structural discrepancy, the adaptive estimation schemes compute the imprecisely known parameters quite accurately based on the measured distillate composition under initialization error, disturbance and uncertainty. In the subsequent part, the adaptive GMC–ASE1 control structure has been formulated for the sample reactive column. This nonlinear control strategy shows comparatively better closed-loop performance than the gain-scheduled proportional integral (GSPI) controller due to the exponential error convergence capability of the estimation scheme and the high-quality control of the GMC law.

Experimental and Modeling Studies for a Reactive Batch Distillation Column

Modeling of esterification reaction of ethanol with acetic acid in a reactive batch distillation column is investigated. The dynamic model developed is verified using the data of a theoretical study available in the literature. However, the existing models are found to be inappropriate for this system when compared with the experimental data. Then the model is improved using the data obtained from the experiments performed on a lab-scale column. In the model, different rate expressions and different thermodynamic models (ϕ–ϕ, EOS-G ex , and γ–ϕ methods) considering different equations of state (EOS), mixing rules and activity coefficient models are used. It is found that the γ–ϕ approach considering van der Waals mixing rule and NRTL activity coefficient model gives the best fit between the dynamic model and the results of the experiments for the system under study.

Study of the Performance of Batch Reactive Distillation Column

Batch reactive distillation was studied in packed bed column. Esterification of methanol with acetic acid to produce methyl acetate and water with homogenous sulfuric acid as a catalyst was considered. This system was chosen because the reaction is reversible and the boiling point of reactant and products are different.The reaction was carried out with and without distillation column and shows that the reactive distillation is more efficient from the conventional process (reactor and then separation). The conversion of acetic acid and concentration of methyl acetate increase by (30.43% and 75.14%) respectively at the best condition (reflux ratio 2, feed mole ratio 2 and batch time 90 minute).The influence of various parameters, such as batch time, reflux ratio, and feed mole ratio (methanol to acetic acid) on the performance of the batch reactive distillation column was studied, through the effect of the concentration of product and conversion of reactant.The results obtained for the non-ideal packed bed reactive batch distillation column show that the conversion of acetic acid is 90% at the best condition reflux ratio 2, feed mole ratio 2, and batch time 90 minute

Improving the Maximum Conversion of Ethanol Esterification

In this study, the (catalysed) esterification process of acetic acid with ethanol producing ethyl acetate and water is modelled using detailed mass and energy balances and thermodynamic properties within gPROMS modelling software (version 3.0.3, 2004). The basic model was taken from Mujtaba and Macchietto (1997) assuming no azeotrope formation in the system. Kinetic (hydrochloric acid as a catalyst at 100 °C) and vapour-liquid equilibrium models are taken from Bogacki et al. (1989) and Suzuki et al. (1970) respectively. Physical properties are calculated using the Ideal Physical Properties Foreign Objective (IPPFO) package interfaced to gPROMS. The performance of the batch reactive distillation is evaluated in terms of the maximum conversion of ethanol to ethyl acetate. Five cases with varying amounts of reactants (including the cases with the reduced amount of water in the feed and keeping the amount of acetic acid and ethanol fixed) are utilized to improve the conversion of ethanol to ethyl acetate. Both piecewise constant and linear reflux ratio profiles (single time interval) are considered as a control variable for the base case while the piecewise constant single reflux ratio strategy is adopted for other optimized cases. The results show that both the maximum conversion and distillate product (base case) are improved using the linear reflux strategy as a control variable compared to those with a constant reflux ratio profile. Increasing the amount of water in the feed leads to a reduction in the conversion and distillate product; moreover, the column was operated at a higher reflux ratio compared to the case without any water in the feed.

Estimation of Still Trajectory for Batch Reactive Distillation Systems

This work addresses a new method for estimating the liquid still composition trajectory of batch reactive distillation systems based on material balance and reaction equilibrium data. The still trajectory information is essential to determining whether pure products are reachable from this still pot trajectory when several distillation boundaries are present, initial feed compositions can vary, and the number of components exceeds our visualization capability. For a given feed to product flow ratio with constant feed charge and product compositions, the still pot composition trajectory is mathematically confined to the intersection between the reaction equilibrium manifold and a “material balance plane” that is the union of stoichiometric lines and material balance rays connecting still and product compositions. Starting from this estimated still pot trajectory, we can easily extend feasibility studies of various batch reactive distillation configurations even for multireaction systems.

Thermodynamic analysis of a reactive distillation process for deep hydrodesulfurization of diesel: Effect of the solvent and operating conditions

Abstract The effect of the solvent type, operating pressure and catalyst loading for deep hydrodesulfurization of diesel through a reactive distillation process has been analyzed. The analysis considers the computation of reactive residue curve maps for the hydrodesulfurization of dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophene (4,6-DMDBT) in a simple reactive batch distillation process. For the computation of the reactive residue curves, the hydrogenolysis and hydrogenation reaction paths were considered. The visualization of the reactive residue curves is posed in terms of elements. Through the computation of the reactive residue curve maps it was possible to reproduce the experimental information stating that DBT is preferentially converted following the hydrogenolysis reaction route, while 4,6-DMDBT is mostly eliminated by the hydrogenation reaction route. From the reactive residue curve maps the effect of the solvent, pressure and catalyst loading on the conversion of 4,6-DMDBT was studied. It was found that when n-hexadecane (n-C16H34) is used as the solvent medium and the operating pressure is set to 10 atm a complete conversion of 4,6-DMDBT is achieved. The same conversion is achieved using tetraline (C10H12) as solvent but the pressure must be increased up to 30 atm and a higher amount of catalyst is required.

On-line Optimizing Control for a Class of Batch Reactive Distillation Columns

The problem of designing an on-line optimizing output-feedback (OF) controller for the class of reaction: A + B ↔ C + D of batch reactive distillation columns with temperature measurements is addressed. The joint process-control design problem is solved within a constructive framework, by combining relative degree and detectability structures concepts in the light of particular system features. The result is an OF control scheme that decides the total reflux period and batch durations, and manipulates the reflux rate over the withdrawal period. The proposed approach is illustrated with a case example (esterification of ethanol and acetic acid) through numerical simulations, yielding a closed-loop operation which is similar to the open-loop ones previously obtained via direct optimization.

State Estimation for a Reactive Batch Distillation Column

An Artificial Neural Network (ANN) estimator is designed to predict the composition values of a reactive batch distillation system inferentially. The estimator for the reactive batch distillation system, which is recently a preferred industrial operation for specialty chemicals production, is designed using temperature measurements throughout the column. The reflux ratio of the batch distillation column is also used as input to the ANN as well as temperature values. The ANN used is an Elman network with two hidden layers; having 20 neurons in the first hidden layer, three neurons in the second hidden layer, and four neurons in the output layer. The performance of the designed network is tested in open-loop and it is found that, it is possible to predict the product compositions by using the designed ANN estimator which can be used in the control of the product compositions.

Esterification of Acrylic Acid with 1,4‐Butanediol in a Batch Distillation Column Reactor over Amberlyst 15 Catalyst

AbstractThe esterification reaction of acrylic acid (AA) with 1,4‐butanediol (BD) to produce 4‐hydroxybutyl acrylate (HBA) was carried out in a batch reactive distillation mode over the Amberlyst 15 catalyst. The reactive distillation was highly desirable to increase the reaction rate of BD and eventually to obtain the high purity of HBA because the unreacted BD was not easily separable to the produced HBA after the reaction. The reaction pressure below 760 mm Hg was used to remove the by‐product water from the reaction zone. The air‐bubbling operation was successfully applied to prevent the polymerization of reactants and products under the vacuum condition (400 ∼ 760 mm Hg). The reaction rates were strongly dependent on the reaction pressure, especially, the reaction rate of BD disappearance. The increased reaction rate of BD by the reactive distillation enabled to produce a high purity of HBA.

Esterification of Lactic Acid with n-Butanol by Reactive Distillation

Esterification of lactic acid with n-butanol may be performed to synthesize n-butyl lactate or to recover lactic acid from its aqueous solution. In the present work, the reaction is performed in the presence of cation-exchange resins as a catalyst. Kinetic parameters like activation energy and the rate constants are estimated using the pseudohomogeneous model. The applicability of reactive distillation for this reaction is evaluated through experiments using batch and continuous reactive distillation techniques. An equilibrium stage model is formulated, and simulation results are compared with the experimental results. Further, the effects of operating parameters like feed mole ratio, catalyst loading, and boilup rate are evaluated on the conversion of lactic acid in batch reactive distillation. Experimental results of continuous reactive distillation are compared with the simulation results observed using the Aspen plus process simulator. Effects of operating variables were studied with the help of the e...

A new operation mode for reactive batch distillation in middle-vessel columns: Start-up and operation

The most outstanding feature of batch distillation is its flexibility in design and operation. In particular, when chemical reactions and physical separations have some overlapping operating conditions the combination of these tasks can offer significant benefits. In this work, we propose a new operation mode for reactive batch distillation in middle-vessel columns. The special feature of this novel operation mode lies on the fact that depending on the characteristics of the reaction mixture, the reaction will also take place either along the upper column or along the lower column. The performance of the novel operation mode is demonstrated through rigorous simulation of an industrial reactive batch distillation process. Furthermore, since the performance of the start-up procedure has a large impact on the entire reactive batch distillation process, we also focus on the description of the dynamic behavior of the start-up operation starting from the cold and empty batch columns as the initial state. The proposed model includes both equation and variable discontinuity. Thus, we propose in this work a modeling approach to describe the state transitions during the start-up phase.

Dynamic Simulation of Reactive Batch Distillation Column for Ethyl Acetate Synthesis

A detailed mathematical dynamic model of reactive batch distillation column is formulated for ethyl acetate synthesis and presented in terms of differential and algebraic equations (DAEs). These DAEs are solved using fourth order Runge-Kutta method in MATLAB® to obtain the detailed column dynamics. The simulation results provide the dynamics of reboiler and distillate compositions, reboiler temperature, ethyl acetate purity in the accumulated distillate and conversion of the reactants. These results are analyzed to derive the optimum operating policy, i.e., reflux ratio and batch time.

Constructing residue curve maps for butyl acetate synthesis

This work presents a laboratory study of liquid phase N-butylacetate synthesis (Patm = 560 mmHg), employing simultaneous distillation and reaction (batch reactive distillation) and an ion exchange resin (Lewatit K-2431) as catalyst. The conditions in which the operation was limited by reaction equilibrium (equilibrium regime) and not by kinetics effects (kinetic regime) was determined by constructing experimental residue curves using different catalyst loads. The feasibility of implementing esterification through a simultaneous reaction-separation arrangement was established. Pure butylacetate could be obtained in such process as a bottom product from a reactive distillation column, overcoming the reaction system’s conversion limitations.

Recovery of lactic acid by batch reactive distillation

AbstractLactic acid, being virtually a non‐boiling compound, is difficult to separate from its aqueous solution by conventional methods such as distillation. It is necessary to convert it to the relatively volatile ester and the separation of the ester, followed by hydrolysis, is recommended as an appropriate method of recovery. In the present work, we explore and investigate a novel reactive distillation strategy to perform esterification, distillation and hydrolysis in a single unit. The experiments were performed in a batch reactive distillation set‐up and the results have been explained with the help of an appropriate model. An unsteady state mathematical model based on an equilibrium stage concept was developed for batch reactive distillation. A pseudo‐homogeneous model was used for the determination of reaction kinetics. The effect of operating parameters such as feed concentration, mole ratio, catalyst loading, boil‐up rate, etc. on the recovery of lactic acid was studied with the help of simulation and experimental results. The feasibility issue of reactive distillation has been discussed based on the results obtained. Copyright © 2006 Society of Chemical Industry

Composition estimation of multicomponent reactive batch distillation with optimal sensor configuration

An inferential state estimation scheme based on extended Kalman filter (EKF) with optimal selection of sensor locations using principal component analysis (PCA) is presented for composition estimation in multicomponent reactive batch distillation. The properties of PCA are exploited to provide the most sensitive dynamic temperature measurement information of the process to the estimator for accurate estimation of compositions. The state estimator is supported by a simplified dynamic model of reactive batch distillation that includes component balance equations together with thermodynamic relations and reaction kinetics. The performance of the proposed scheme is evaluated by applying it for composition estimation on all trays, reboiler, reflux drum and products of a reactive batch distillation column, in which ethyl acetate is produced through an esterification reaction between acetic acid and ethanol. This quaternary system with azeotropism is highly nonlinear and typically suited for implementation of the proposed scheme. The results demonstrate that the proposed EKF estimation scheme with optimal temperature sensor configuration is effective for inferential estimation of compositions in multicomponent reactive batch distillation.