Year: 2020
Type: article
Abstract: Separations of mixtures play a critical role in chemical industries. Over the last century, the knowledge in the area of chemical thermodynamics and modeling of separation processes has been substantially expanded. Since the models are still not completely accurate, hybrid models can be used as an alternative that allows to retain existing knowledge and augment it using data. This paper explores some of the weaknesses in the current knowledge in separations design, simulation, optimization, and operation, and presents many examples where data‐driven and hybrid models have been used to facilitate these tasks.
Source: Chemie Ingenieur Technik
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,500
Funders: International Max Planck Research School for Environmental, Cellular and Molecular Microbiology, Deutsche Forschungsgemeinschaft, International Max Planck Research School for Advanced Methods in Process and Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg
OpenAlex ID: W3031657662