Multicomponent Distillation Column Research Articles

Computer Aided Design of a Multi-Component Distillation Column for Processing of Nigerian Bonny Light Crude Oil

The design of the multi-component distillation column for processing of Bonny light crude is presented using advanced process simulation software (Aspen Hysys). The steady state design models were developed from Mesh equations and were used to obtain the design parameters based on the principle of conservation of mass and energy. The design parameters were column diameter, column cross sectional area, height of the column, downcomer area, hole area, weir length, wet area and tray spacing. The equations developed are capable of predicting compositions, partial pressures and temperature of the components of interest from the mixtures of crude oil. The accuracy of the design parameters were ascertained by comparing predicted results with literature data of a distillation unit. The simulation of the design models were performed using Aspen Hysys to obtain optimum values of the most significant variables/parameters (column diameters 1.558m, column height 17.048m, cross section area 1.907m2, downcomer area 0.229m2, tray spacing 0.5m, weir length 1.200m, hole area 0.191m2 and wet area 1.678m2). The result obtained from the steady state simulation shows that the feed flow rate, temperature and pressure influence the efficiency of the distillation column.

СПЕКТР БАГАТОВИМІРНИХ МОДЕЛЕЙ ДИНАМІКИ КОЛОНИ РЕКТИФІКАЦІЇ НАФТИ ДЛЯ СИНТЕЗУ РОБАСТНИХ СИСТЕМ УПРАВЛІННЯ

Classical automatic control systems of crude oil distillation columns are used to stabilize indirect parameters (temperature, pressure, level) which are considered as independent. Such systems can be used in case of small disturbances and fluctuation of oil composition. The article describes the set of linear mathematical dynamical models of multi-component crude oil atmospheric distillation column K-2 which is based on direct parameters of material balance. For development of modern multivariable automatic control systems it’s preferable to use direct material balance parameters because change of products flow ratios leads to economical loses. Developed models shows that the plant is significantly multivariable with big lag, so effective automatic control system can be designed only with use of modern control theory. The developed set of models can be used for research of robustness and quality of multivariable automatic control systems (optimal, suboptimal, model-predictive, etc) of crude oil distillations columns which oriented on material balance parameters

Robust control system design of crude oil atmospheric distillation column

The robust control system of multi-component oil atmospheric distillation column was designed. Since the dynamics of the column can not be accurately modeled, a set of models, used at different design stages of the control system was developed. In the paper, the robustness of the control system means the preservation of its high quality when connecting any model of the developed set. The big advantage of the system is the fact that it is based on a multi-dimensional digital linear-quadratic regulator and the parameters that determine the material balance of the column are used as controlled variables. Such a system is easy to implement and can successfully replace traditional control systems of oil distillation columns and modern commercial control systems, which are based on model-predictive controllers popular in the global oil and gas industry.

Identification of Nonlinear Soft Sensor Models of Industrial Distillation Process under Uncertainty

The advancement of method of nonlinear soft sensor development using a nonparametric approach based on the example of industrial multicomponent distillation column is considered. The proposed procedure for soft-sensors evaluation is directed to overcome such difficulties in practice as process nonlinearity and uncertainty due to unknown model structure and measurement errors of output.

Energy Saving through Control in an Industrial Multicomponent Distillation Column

The problem of reducing the energy consumption in an industrial multicomponent distillation column is addressed. The column is subjected to step feed and distillate flow rates, the distillate impurity is regulated by adjusting the heat duty with a PI temperature controller, and the objective is to save energy through control upgrade. First, the nonlinear feedforward output-feedback robust advanced control problem is addressed, drawing the control construction and the solvability conditions. Then, the behavior of the advanced controller is recovered using a PI temperature controller with a dynamic feedforward setpoint compensator driven by the three measured flow rate disturbances. The approach is illustrated and tested through numerical simulations with a model calibrated with industrial data, finding that: the distillate impurity mean is maintained, its variability is reduced by 80 %, and the energy consumption is reduced by 15%.

Generalized Regression Neural Network Based on Soft Sensor for Multicomponent Distillation Column

Generalized Regression Neural Network Based on Soft Sensor for Multicomponent Distillation Column

Feedforward-feedback control of an industrial multicomponent distillation column

The problem of regulating the distillate impurity content in a two-feed (paraffin-olefin) industrial multicomponent distillation column (iso-normal butane splitter) by manipulating the heat duty according to olefin-to-total feedflow load disturbance and tray temperature measurements is addressed. First, the detailed model-based nonlinear state-feedback robust control problem is addressed, identifying the solvability conditions and attainable closed-loop behavior. Then, the behavior of this controller is recovered with an output feedback PI temperature controller with dynamic feedforward setpoint compensation and antiwindup protection. The proposed approach is illustrated and tested through numerical simulations with a detailed model calibrated with industrial data, establishing the feasibility of improving the existing control scheme with PI temperature control plus manual setpoint compensation.

Approximating the minimum reflux ratio of multicomponent distillation columns based on the Adomian decomposition method

The Underwood's equations are very famous as they provide a shortcut method for evaluating the minimum reflux ratio of a multicomponent distillation column. In this paper, a semi-analytical tool for finding the roots of a practical form of the Underwood's equations is devised based on a reliable mathematical technique known as the Adomian decomposition method. Despite the discontinuities inherently present in the Underwood's equations, the proposed strategy rapidly yields highly accurate results without any difficulties. In contrast to many previous algorithms, the current method is robust and does not impose the need for any initial guess in course of solution. It is also shown that the proposed scheme can optionally be equipped with a nonlinear convergence accelerator known as the Shanks transform to become much more computationally efficient. Two multicomponent distillation problems are chosen and solved by the present approach for the sake of exemplification.

A note on an extended short-cut method for the design of multicomponent reactive distillation columns

Until now, few studies have proposed analytical short-cut methods for reliably designing multicomponent reactive distillation columns. Therefore, in this study we have improved and extended a design methodology for the design of RD columns of multicomponent systems. We have developed a graphical design method, based on distillation lines and tray-by-tray calculations defined in terms of reaction-invariant composition variables, to determine RD design parameters such as the number of theoretical stages, operating reflux ratio, the feed tray location and the top or bottom flow. In this note, we report our extended and improved method, which is analytical and useful for reliably determining the design parameters of multicomponent RD systems. We study the synthesis of TAME with inert components (with different feed thermal conditions) as case of study to show the effectiveness of the proposed strategy. Results obtained with our strategy show a significant agreement with those obtained using a rigorous model of commercial simulator AspenONE Aspen Plus®.

Minimum number of transfer units and reboiler duty for multicomponent distillation columns

Some guidelines to evaluate distillation columns, considering only basic thermodynamic data and principles, are provided in this paper. The method allows a first insight to the problem by simple calculations, without requiring column variables to ensure rational use of energy and low environmental impact. The separation system is approached by two complementary ways: minimum and infinite reflux flow rate. The minimum reflux provides the minimum energy requirements, and the infinite reflux provides the feasibility conditions. The difficulty of separation can be expressed in terms of number of transfer units (NTU). The applicability of the method is not mathematically limited by the number of components in the mixture. It is also applicable to reactive distillation. Several mixtures, including reactive distillation, are rigorously simulated as illustrative examples, to verify the applicability of the approach. The separation of the mixtures, performed by distillation columns, is feasible if a minimum NTU can be calculated between the distillate and bottom products. Once verified the feasibility of the separation, the maximum thermal efficiency depends only on boiling point of bottom and distillate streams. The minimum energy requirements corresponding to the reboiler can be calculated from the maximum thermal efficiency, and the variation of entropy and enthalpy of mixing between distillate and bottom streams.

A simple, reliable and fast algorithm for the simulation of multicomponent distillation columns

This work has developed a simple, reliable and fast algorithm for the simulation of multicomponent distillation columns, where any equilibrium stage can accept a feed-stream and/or a vapor-side-stream and/or liquid-side-stream. The new scheme considers internal molar overflows and constant relative volatilities to avoid the need of heat balances and vapor–liquid equilibrium calculations. The solution scheme is founded on a Newton-based formulation in block algebra, which relies in a simple, reliable and fast algorithm. Although the proposed calculation scheme can be classified as an approximate method, it is very useful when accurate phase equilibrium and enthalpy data are lacking. Numerical experimentations show good agreement with the results obtained with well-known rigorous simulation approaches.

Model Predictive Inferential Control of a Distillation Column

Typical production objectives in distillation process require the delivery of products whose compositions meet certain specifications. The distillation control system, therefore, must hold product compositions as near the set points as possible in faces of upset. In this project, inferential model predictive control, that utilizes an artificial neural network estimator and model predictive controller, is developed for an industrial multicomponent distillation column. First, composition control by direct measuring composition is used. This method because of large sampling delay has a poor performance. The selection of the temperature measurement points is done for indirect control of the column. The use of temperature loop leads to an offset in the composition; due to the fact that the temperature set-point must be changed when feed disturbances occurred. An artificial neural network estimator is designed to estimate the product compositions from tray temperature measurements. A model predictive controller is used to control column composition based on composition estimates. The performance of the developed inferential model predictive control system is tested for set-point tracking and load rejection.

Are All Thermal Coupling Links between Multicomponent Distillation Columns Useful from an Energy Perspective?

Thermal coupling links between multicomponent distillation columns are known to reduce the total heat duty and, therefore, the first-law energy demand of distillation configurations. Most studies on the energy savings of thermally coupled configurations have focused on cases where all thermal coupling links of a configuration have been used. We show that certain types of thermal coupling links of a configuration actually do not contribute to the first-law energy savings. Furthermore, it is often believed that the first-law energy savings due to thermal coupling links always has associated second-law temperature-level costs due to increased utility demand at extreme temperatures. However, we demonstrate that some types of thermal coupling links provide first-law energy savings without exhibiting any second-law temperature-level penalties. Finally, we present heuristics to enable quick identification of such thermal coupling links.

Measurement structure design for multicomponent distillation column with specific estimation objective

In this work, the problem of designing the estimation structure to infer some of the effluent compositions in a multicomponent distillation column is addressed, with the aim to determine the structure that yields the best estimator functioning in the sense of a suitable compromise between performance versus complexity, regardless of the particular estimation algorithm employed. The structure design involves the selection of (i) the number of modeled components, (ii) the innovated components, and (iii) the number and locations of sensors. The consideration of the problem within the adjustable-structure geometric estimation framework in the light of the column characteristics leads to a methodology with an analysis stage, where structures are screened and candidate ones are selected, followed by a synthesis stage which yields the structure with the best estimator functioning. The proposed approach is applied through simulations to an industrial-type hexacomponent distillation column, finding that the estimation task can be adequately performed with an algorithm whose number of ODEs (77) is considerably smaller than the one (2849) that results from the direct application of the standard EKF.

Modeling of Mass Transfer in Nonideal Multicomponent Mixture with Maxwell-Stefan Approach

The Intalox metal tower packing was used to simulate an industrial relevant extractive distillation column for purifying azeotropic multicomponent mixture. In order to explain the inconsistencies in the modeling of transfer process in nonideal multicomponent distillation column, a method was developed with equilibrium stage models (EQ) and non-equilibrium model (NEQ) incorporated with Maxwell-Stefan diffusion equations in the framework of AspenONE (r) simulator. Dortmund Modified UNIFAC (UNIFAC-DMD) thermodynamic model was employed to estimate activity coefficients. In addition, to understand the reason for the diffusion against driving force and the different results by EQ and NEQ models, explicit investigations were made on diffusion coefficients, component Murphree efficiency and mass transfer coefficients. The results provide valuable information for basic design and applications associated with extractive distillation.

Synthesis of distillation configurations. II: A search formulation for basic configurations

It is known that there exist a combinatorially large number of multicomponent distillation column configurations for a given feed and given product specifications. In the accompanying part I of the paper, we classified configurations into basic configurations (those that use ( n − 1) columns for an n-component feed mixture) and non-basic configurations (those that use more than ( n − 1) columns for the same feed). As n exceeds four, the number of non-basic configurations greatly exceeds the number of basic configurations and have a huge impact on the size of the search space. However, through extensive calculations for a four-component feed, we have found that a non-basic configuration never has a lower heat duty than the lowest heat duty basic configuration. While prior researchers have proposed a mathematical formulation that could be used to generate only the set of basic configurations, we present an alternative supernetwork model to achieve this goal. We show how the supernetwork can be reduced to a binary integer program (BIP), and how all feasible configurations can be drawn for a given application using a suitable solver. We present different solution techniques, including parallel algorithms based on the fact that the evaluation of the performance for each configuration is independent of any other configuration. Through such a procedure, all applicable basic configurations can be rank listed for a given application according to a chosen criterion. We also extend the supernetwork formulation to a unified non-convex MINLP that can be used in a flexible way to find the best candidate configurations for a given application. We show the power of our search formulation in accommodating general separation techniques other than distillation, such as membranes, adsorption, etc.

Comparative Control Study of a High-Purity Ternary Batch Distillation

This paper presents a comparative closed-loop performance study on a multicomponent batch distillation column that produces high-purity distillate product. Initially, the distillation model representing a ternary system of cyclohexane-toluene-chlorobenzene has been simulated to observe the open-loop dynamics at the start-up as well as production phase. The next three control schemes, namely classical proportional integral (PI) controller, nonlinear proportional integral (NLPI) control strategy and gain-scheduled proportional integral (GSPI) law, have been designed and applied on the simulated distillation column. Numerical experiments based on servo and regulatory tests show that the GSPI algorithm provides relatively better results than the other two PIs.

Modeling and Simulation of Catalytic Distillation Column for Esterification of Acetic Acid with Methanol

The present investigation pertains to a theoretical study of simulation of a multicomponent catalytic distillation column. Basically it deals with the development of a mathematical model for esterification of acetic acid with methanol by using a packed column with two different feed setups: a single feed column and a two feed column. The reaction kinetics has been assumed to be heterogeneous. It also includes the solution technique for the solution of the model. An in-house code in C++ has been developed to solve the model equations. Further, the comparison of the model has been done with available experimental data. Finally the effect of design variables namely- reflux ratio, feed tray location, and start of reactive section have been studied.

Virtual Applications Using a Web Platform to Teach Chemical Engineering: The Distillation Case

The question we will address here is how to integrate computational tools, namely the more modern and interactive ones, in the teaching of Chemical Engineers by means of the World Wide Web. The case study presented concerns the development of a web application for the simulation of multicomponent distillation columns running at steady state condition using the MATLAB WebServer. The application allows a remote user to login into a web site, choose several operating parameters and perform on-line simulations. In short, we believe that the introduction of this new perspective of teaching chemical engineering can result in ample benefits, leading students to a better and wider understanding of the processes involved.

Nonlinear adaptive control algorithm for a multicomponent batch distillation column

In this article, a nonlinear adaptive control strategy is proposed for a multicomponent batch distillation column. The hybrid control scheme consists of a generic model controller (GMC) and a nonlinear adaptive state estimator (ASE). In the first part of the study, an adaptive observer is designed aiming to estimate the partially known parameters based on the measured compositions in the presence of process/predictor mismatch. The open-loop dynamic behavior of the developed ASE estimator is investigated under initialization error, disturbance, and uncertain parameters. In the subsequent part, the adaptive GMC–ASE controller (GMC control structure in conjunction with ASE estimator) has been synthesized for the example distillation column. A simulation-based comparative study has been conducted between the derived nonlinear GMC–ASE control algorithm and a gain-scheduled proportional integral (GSPI) law in terms of constant composition control. The proposed adaptive control scheme is shown to be quite promising due to the exponential error convergence capability of the ASE estimator in addition to the high-quality performance of the GMC controller.