Influence assessment of inlet parameters on thermal risk and productivity: Application to the epoxidation of vegetable oils

The influence of inlet parameters on the production and thermal risk of complex chemical systems can be cumbersome to evaluate. To determine the optimum safe operating conditions, one needs to solve complex differential equations derived from energy and material balances. This robust approach cannot...

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Bibliographic Details
Main Authors: Buvat, J.-C (Author), Lefebvre, D. (Author), Leveneur, S. (Author), Rigaux, T. (Author), Zora, N. (Author)
Format: Article
Language:English
Published: Elsevier Ltd 2021
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Online Access:View Fulltext in Publisher
Description
Summary:The influence of inlet parameters on the production and thermal risk of complex chemical systems can be cumbersome to evaluate. To determine the optimum safe operating conditions, one needs to solve complex differential equations derived from energy and material balances. This robust approach cannot be made on-site, and it is essential to propose simplest tools to evaluate rapidly the performance and safety of some operating conditions. This is the aim of this paper that establishes explicit relationships between the production and thermal risk parameters, and the inlet parameters. In addition, it also proposes a Pareto chart that can be used to make the tradeoff between safety and performance. Such relationships and chart were developed for the production of epoxidized cottonseed oil under isoperibolic and semi-batch mode. The kinetic model developed by Zheng et (Zheng et al., 2016). was used. First, a numerical approach, i.e., least square method, was used to find explicit relationships between thermal risk parameters, production parameters and six inlet parameters. The use of such an approach allows a better understanding of this process. Second, safety and performance indicators are proposed and discussed to evaluate the operating conditions thanks to a simple and intuitive schema. Besides, this approach can be used to find the optimum conditions more rapidly. © 2021 Elsevier Ltd
ISBN:09504230 (ISSN)
DOI:10.1016/j.jlp.2021.104551