Simulation and Optimization of an Industrial Sulfuric Acid Plant with Contact Process Using Python-Unisim Design

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Output type: Conference proceeding

UM6P affiliated Publication?: Yes

Author list: Mounaam A., Chhiti Y., Souissi A., Salouhi M., Harmen Y., Khouakhi M.E.

Editor list: Amine Mounaam Younes Chhiti Ahmed Souissi Mohamed Salouhi Yasser Harmen Mohamed El Khouakhi

Publication year: 2022

Journal: Lecture Notes in Networks and Systems (2367-3370)

Volume number: 306

Start page: 64

End page: 89

ISBN: 978-3-030-84810-1

eISBN: 978-3-030-84811-8

ISSN: 2367-3370


Languages: English (EN-GB)

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Sulfuric acid is widely used in different business areas such as, fertilizers, mining industry and waste gas treatment. The contact process is the modern industrial method for producing H2SO4. It has mostly replaced the chamber or lead-chamber process. Process technology is based on the production of Sulphur dioxide (SO2) by liquid sulfur burning using dry air, followed by catalytic conversion to produce sulfur trioxide (SO3) which is finally absorbed in water to obtain sulfuric acid (H2SO4). In the sulfuric acid manufacturing industries, plant modelling and simulation is a challenging task to minimize emissions, maximize production performance and revenue. In this light, the purpose of this paper was to develop semi-empirical dynamic models for modelling, simulation, and optimization of an industrial sulfuric acid manufacturing plant with contact process. Unisim Design simulator was selected to perform all simulation tasks. Unisim was coupled with Python programming language in order to sending data to Unisim Design simulator and reading back simulation results. In addition, the developed dynamic model includes a graphical user interface, thus making the model suitable for real time plant simulation, operator training and digital twin development. Finally, a parametric study, involving different optimization parameters, was carried out. The model developed in this work makes it possible to simulate the sulfuric acid plant with contact process in real time, optimize the performance and minimize the cost and SOx emissions. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.


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Last updated on 2021-22-11 at 23:16