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Using simulation to improve batch distillation.

Using Simulation To Improve Batch Distillation

Process modeling and simulation have been employed for over 30 years to improve continuous chemical processes. By quickly providing engineering and economic data on various design and operating alternatives, simulation enables engineers to make better design and operating decisions, and to improve bottom-line results. Now, as companies focus more of their business on high-value-added specialty products, an increasing number of firms are seeking to achieve the benefits of simulation in batch distillation -- a unit operation frequently used in the production of such products.

The problems involved with design and operation of batch columns are well-suited for the capabilities of simulation. in designing columns, engineers seek to minimize capital and operating costs (which involves column height, column diameter, utility usage, cycle time. etc.) while ensuring that the separation will be achieved. Simulation allows engineers to determine the minimum costs configuration to meet performance specifications, and to feel confident recommending designs with less excess capacity. Studies are also often used to determine the proper location of a side-draw stream, or to size ancillary equipment such as condensers or reboilers.

In production, simulation helps plant engineers to devise strategies to reduce cycle time, to improve yield or purity, and to minimize operating costs. Models are used to fully understand the impact of such options as recycling intermediate cuts, using an entrainer, controlling the reflux ratio to maintain distillate purity, and bringing a column back to total reflux during distillation. Similarly, simulation helps engineers to determine how to make new products in their existing columns.

Batch distillation puts new demands on simulation technology. While steady-state simulation of continuous processes requires only the solution of algebraic equations, batch distillation simulation requires the solution of a large set of differential equations for each operation step. Furthermore, typical characteristics of batch columns, such as wide ranges of holdups and volatilities in the same column, make batch distillation one of the most difficult unit operations to simulate reliably. Only in the past decade have the mathematical techniques required for efficient robust simulation become available, such as those used in BATCHFRAC, Aspen Technology's batch column simulation system.

Case Study Perhaps the best way to understand the power of simulation is through an illustration. The following example is drawn from the experiences of one customer of Batchfrac. The company, a Batchfrac user since 1981, regarded the improvement of its batch operations as a very high priority since processes involving batch distillation consume 25-30% of its capital and 40-50% of its operating expenses. To protect our customer's confidentiality, only a general description of the batch operation will be provided.

The production engineer had two objectives for this study:

* to improve the water cut both by reducing cut time and by reducing the amount of product A and product C in the cut; and,

* to improve the product A/azeotropic agent cut by reducing the cut time, by decreasing the consumption of the azeotropic agent, and by minimizing the amount of product A remaining in succeeding cuts.

The engineer used Batchfrac to quickly and analytically examine alternative operating strategies. Among the strategies considered were:

* for the water cut, reducing/varying the reflux ratio during the operation and changing the cut temperature,

* for the product A/azeotropic agent cut, varying the feed location for the azeotropic agent, varying the feed rate, decreasing the amount of agent in the initial charge, varying the reflux ratio, and varying the distillate rate.

After examining these alternatives, the engineer determined the best operating strategy: reduce the reflux ratio for the water cut from 3/7 to 2/8; add the azeotrophic agent during the Product A cut when overhead temperature reaches 105 [degrees] C (vs. 115 [degrees] C); and feed the azeotropic agent continuously to the top of the column instead of to the pot.

The performance and economic benefits of following the new operating strategy have been considerable. For the water cut, cycle time was reduced by 1.3 hours, yielding a $20-thousand per year savings in operating costs. For the product A/azeotropic agent cut, product A losses were reduced by 25%, the consumption of the azeotropic agent was decreased by 42%, and the cut time was reduced by 2.5 hours. The last benefit alone was worth $25-thousand per year in operating cost savings.

Selection of A Modeling System

The most important consideration in choosing a simulation system is whether it can accurately model your specific batch operation. The most advanced systems, such as Batchfrac, have the ability to handle complicated real-world situations like the occurrence of two liquid phases and reaction in the column. They also contain an extensive library of physical property models to calculate vapor-liquid equilibrium and enthalpies.

The second key consideration is the company standing behind the simulation system. Aspen Technology works with over 100 companies and 80 universities around the world, and is the market leader in providing simulation technology to the chemical processing industry. AspenTech has the experience in providing technical support, training and product enhancements to ensure that both new and experienced users successfully meet their objectives.

HERBERT I. BRITT, Vice President Product Management JOEL B. ROSEN, Director of Marketing Aspen Technology, Inc., Cambridge, MA
COPYRIGHT 1989 Chemical Institute of Canada
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Copyright 1989 Gale, Cengage Learning. All rights reserved.

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Author:Britt, Herbert I.; Rosen, Joel B.
Publication:Canadian Chemical News
Date:Sep 1, 1989
Words:864
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