A Grid-Structured Model of Tubular Reactors

• URL: http://arxiv.org/abs/2112.10765v1
• Date: Mon, 13 Dec 2021 19:54:23 GMT
• Title: A Grid-Structured Model of Tubular Reactors
• Authors: Katsiaryna Haitsiukevich, Samuli Bergman, Cesar de Araujo Filho, Francesco Corona, Alexander Ilin
• Abstract summary: The proposed model may be entirely based on the known form of the partial differential equations or it may contain generic machine learning components such as multi-layer perceptrons. We show that the proposed model can be trained using limited amounts of data to describe the state of a fixed-bed catalytic reactor.
• Score: 61.38002492702646
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We propose a grid-like computational model of tubular reactors. The architecture is inspired by the computations performed by solvers of partial differential equations which describe the dynamics of the chemical process inside a tubular reactor. The proposed model may be entirely based on the known form of the partial differential equations or it may contain generic machine learning components such as multi-layer perceptrons. We show that the proposed model can be trained using limited amounts of data to describe the state of a fixed-bed catalytic reactor. The trained model can reconstruct unmeasured states such as the catalyst activity using the measurements of inlet concentrations and temperatures along the reactor.

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