JOURNAL ARTICLE
A continuous stirred tank reactor simulator for fault diagnosis experiments.
Published In: International Journal of Modeling, Simulation & Scientific Computing, 2025, v. 16, n. 5. P. 1 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Rauber, T. W. 3 of 3
Abstract
Fault diagnosis in technical systems is an essential discipline in engineering. Appropriate simulation software tools provide a crucial didactic infrastructure to perform research, studying the multidimensional process state in case of malfunctioning of the operational state of the process. This work presents a fully documented simulator of a chemical process, a Continuously Stirred Tank Reactor (CSTR). The simulator is a considerably improved model of a benchmark process based on two chemical engineering doctoral theses. Contrary to the popular Tennessee-Eastman simulator and other publicly available simulators, the work presented here allows a profound understanding of the process and the implications of faults. The principal aim is to provide a research-oriented experimental platform for model-based and model-free fault detection and diagnosis where the model faults are easily configured and analyzable. It provides a better alternative to the Tennessee-Eastman software, with the same level of nonlinear complexity and a completely transparent and documented process model. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Modeling, Simulation & Scientific Computing. 2025/10, Vol. 16, Issue 5, p1
- Document Type:Article
- Subject Area:Chemistry
- Publication Date:2025
- ISSN:17939623
- DOI:10.1142/S1793962325500667
- Accession Number:189187857
- Copyright Statement:Copyright of International Journal of Modeling, Simulation & Scientific Computing is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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