The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns-Reference-Cited by-同舟云学术

The Potential of Hybrid Mechanistic/Data‐Driven Approaches for Reduced Dynamic Modeling: Application to Distillation Columns

Published:2020-10-06 Issue:12 Volume:92 Page:1910-1920
ISSN:0009-286X
Container-title:Chemie Ingenieur Technik
language:en
Short-container-title:Chemie Ingenieur Technik

Author:

Schäfer Pascal¹,Caspari Adrian¹,Schweidtmann Artur M.¹,Vaupel Yannic¹,Mhamdi Adel¹,Mitsos Alexander¹²³

Affiliation:

1. RWTH Aachen University Process Systems Engineering (AVT.SVT) Forckenbeckstraße 51 52074 Aachen Germany

2. JARA-Energy Templergraben 55 52056 Aachen Germany

3. Forschungszentrum Jülich GmbH Institute of Energy and Climate Research: Energy Systems Engineering (IEK-10) Wilhelm-Johnen-Straße 52425 Jülich Germany

Funder

Bundesministerium für Bildung und Forschung

Publisher

Wiley

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cite.202000048

Reference66 articles.

1. Modeling, Simulation, and Optimization 4.0 for a Distillation Column

2. E. D.Gilles B.Retzbach in19th IEEE Conf. on Decision and Control including the Symp. on Adaptive Processes 1980. DOI:https://doi.org/10.1109/CDC.1980.271925

3. Reduced-order steady-state and dynamic models for separation processes. Part II. Application to nonlinear multicomponent systems

4. Simulation of fractionation by orthogonal collocation

5. Dyanmic compartmental models for separation processes

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