Elsevier

Computers & Chemical Engineering

Volume 48, 10 January 2013, Pages 335-344
Computers & Chemical Engineering

Operator training simulator process model implementation of a batch processing unit in a packaged simulation software

https://doi.org/10.1016/j.compchemeng.2012.09.005Get rights and content

Abstract

In chemical industry, especially in the case of continuous processes, operator training simulators (OTS) are becoming widely used. With the help of these systems several operation and safety issues can be analysed, and the operating staff of the plant can be trained for handling different plant failures. The main part of the OTS is the process model that replaces the real technology. Hence, in control development the simulated process variables are required to be reasonably accurate. The paper presents the structure of the process model of a batch processing unit in UniSim Design, different model constructions of a jacketed batch reactor and the identification of the parameters affecting its hydrodynamic and thermal behaviour. Construction of the process model is the first step in developing the OTS of the pilot plant located in the authors’ laboratory. It can be an effective tool in the development of model-based control systems.

Highlights

► Different commonly used flowsheeting simulation software was tested. ► The process model was built in packaged flowsheeting simulation software. ► Different batch reactor model constructions were tested. ► Better results can be achieved using a temperature-dependent heat transfer coefficient. ► The models of measuring instruments are necessary for reliable simulation results.

Introduction

An increasing number of chemical companies have recently decided to use OTS systems with the aim of training the operating staff on handling different plant failures, rarely used modes of operation and measuring their skills, as well as supporting engineering tasks like testing new control methods and performing safety tests without risk on the real system (Fürcht et al., 2008, Rey et al., 2008, Yang et al., 2001).

The objective of this project is to build an OTS that allows the time- and cost-effective development of the control of the batch processing unit. It can also be useful as the simulation background of laboratory practices for a large number of students (Cameron and Lewin, 2009, Edgar et al., 2006, Mahoney et al., 2000). The first step of this work was to build the process model using Honeywell's UniSim Design simulation software. It was chosen due to its widespread usage in OTS applications.

The chosen simulation software is mainly capable of the simulation of continuous processes, and it does not contain a built-in jacketed batch reactor. Hence, the possibilities provided by the software for the best available approximation of the batch reactor were analysed.

Section snippets

The batch processing unit

In the laboratory of the authors’ department, a batch processing unit (Fig. 1) containing a 30-l reactor with a conventional jacket can be found. The temperature of the reactor can be controlled by feeding heating or cooling monofluid into the recirculation loop of the jacket. The monofluid thermoblock contains three similar loops with three different temperature levels. The highest (90 °C) can be controlled by an electric heater, the medium (20 °C) by tap water through a plate heat exchanger,

Building the process model

UniSim Design simulation software is mainly used to simulate continuous processes. In the case of batch technologies, it has some limitations. For example, it does not contain a built-in jacketed reactor, and there are difficulties with the online exportation of time-dependent data to third-party software in dynamic mode. Nonetheless, some examples can be found in the literature (Aspelund, Gundersen, Myklebust, Nowak, & Tomasgard, 2010).

In the case of batch technologies, the model building

Conclusions

In the case of batch technologies, temperature is one of the most important controlled variables. Therefore, if a packaged flowsheeting simulator is used for the development of the control, it is important to analyse the adequacy provided by the built-in models. In several cases, the built-in models of the simulation software are unknown or poor information is available. This encumbers understanding the behaviour of the built-in modules, consequently achieving the expected results. This is the

Acknowledgement

This work has been supported in part by the TAMOP-4.2.2/B-10/1-2010-0025 project.

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