Flow pattern recognition in tray columns with MADM (multiple attribute decision making) method

doi:10.1016/j.compchemeng.2006.01.006

Computers & Chemical Engineering

Volume 30, Issues 6–7, 15 May 2006, Pages 1197-1200

https://doi.org/10.1016/j.compchemeng.2006.01.006 Get rights and content

Abstract

In studying the dynamic and steady behavior of distillation columns, identifying the liquid flow pattern is very important. The type of liquid flow pattern on each tray depends on design parameters such as column diameter and tray spacing and operating variables such as liquid and vapor flow rates. The innovative technique presented in this paper can help us to recognize the tray flow pattern type with MADM method. A case study is presented to illustrate the method.

Introduction

To model and simulate the distillation columns, a wide range of models has been proposed by different authors. In most of these models, the authors tried to make the models simple and general by considering some simplifying assumptions (Gani, Ruiz, & Camron, 1986), however some of them developed more rigorous and complex models (Chang, Lee, Kwon, & Moon, 1998). The amount of liquid hold-up on each tray depends on the type of flow regime (Wijn, 1999) which can highly affect the simulation results. Therefore, the liquid flow pattern should be recognized to increase the accuracy of the simulation results. During normal operation of a distillation column over a particular tray, the flow regime of the two phase dispersion in the contacting area is usually spray (jet) or froth (mixed) (Wijn, 1998). The emulsion regime is the third flow regime cited by Kister (1989). Each flow regime has its own special attributes. For example operation in the spray regime is associated with low liquid loads, low liquid holdups and low operation pressure (Wijn, 1998). Conversely, high liquid loads and high pressure is favored by emulsion regime (Kister, 1989). Each attribute has different units of measurement and also different degree of importance which can be assigned directly by decision maker or may be developed by MADM methods.

Over recent decades, the most optimizers focused on MADM methods. These methods refer to making preference decisions (e.g. evaluation, prioritization, selection) over the available alternatives that are characterized by multiple and usually conflicting attributes (Hwang & Yoon, 1981). An operating column has several specifications where some of them are design parameters such as column diameter and tray spacing while others can be operating variables such as liquid and vapor flow rates. In this study, an innovative method has been introduced which is able to evaluate the flow pattern type in the tray columns and can be used as an auxiliary software package in the distillation column simulators. A case study highlighting the application of the method is presented.

Section snippets

Method description

A MADM problem can be concisely expressed in a matrix format, where columns indicate attributes considered in a given problem and rows list competing alternatives. Thus a typical element r_ij of the matrix M indicates the performance rating of the ith alternative, A_i, with respect to the jth attribute, X_j, as below:

Three alternatives are available in the flow pattern problems which are spray regime (A₁), froth regime (A₂) and emulsion regime (A₃). Furthermore, five attributes can be supposed to

Case study

As an example, the flow pattern of a typical tray is evaluated to demonstrate the effectiveness of the proposed method. The tray specifications of a typical column simulated by a commercial software are given in Table 2. In fact, these data are the input data for the flow pattern problem which either can be obtained from an existing column or the simulation results of a column simulator. Since some of these data especially liquid and vapor flow rates cannot often be measured in an existing

Conclusion

Since the amount of the liquid on each tray is closely related to the flow regime, the recognition of liquid flow pattern is necessary to increase the simulation results accuracy. In this study, an innovative technique has been developed with MADM method which can able us to recognize the flow pattern type in the distillation columns. The presented case study illustrates the method capability in flow pattern recognition.

Acknowledgments

The author is pleased to acknowledge Professor M.J. Asgharpour for his helpful assistances given so freely in the optimization section and M. Nasir for his suggestions in papering this work.

References (6)

R. Gani et al.
A generalized model for distillation columns – I
Computers & Chemical Engineering
(1986)
E.F. Wijn
On the lower operation range on sieve and valve trays
Chemical Engineering Journal
(1998)
E.F. Wijn
Weir flow and liquid height on sieve and valve trays
Chemical Engineering Journal
(1999)

There are more references available in the full text version of this article.

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Short noteFlow pattern recognition in tray columns with MADM (multiple attribute decision making) method