Abstrakti
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.
Alkuperäiskieli | Englanti |
---|---|
Otsikko | 2021 IEEE 19th International Conference on Industrial Informatics (INDIN) |
Kustantaja | IEEE |
Sivumäärä | 5 |
ISBN (elektroninen) | 978-1-7281-4395-8 |
DOI - pysyväislinkit | |
Tila | Julkaistu - 21 heinäk. 2021 |
OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
Tapahtuma | IEEE International Conference on Industrial Informatics - Palma de Mallorca, Spain, Palma de Mallorca, Espanja Kesto: 21 heinäk. 2021 → 23 heinäk. 2021 https://2021.ieee-indin.org/ |
Conference
Conference | IEEE International Conference on Industrial Informatics |
---|---|
Lyhennettä | INDIN |
Maa/Alue | Espanja |
Kaupunki | Palma de Mallorca |
Ajanjakso | 21/07/2021 → 23/07/2021 |
www-osoite |