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Data‐Driven Subgrid‐Scale Modeling for Convection‐Dominated Concentration Boundary Layers
Author(s) -
Weiner Andre,
Hillenbrand Dennis,
Marschall Holger,
Bothe Dieter
Publication year - 2019
Publication title -
chemical engineering and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.403
H-Index - 81
eISSN - 1521-4125
pISSN - 0930-7516
DOI - 10.1002/ceat.201900044
Subject(s) - boundary (topology) , boundary layer , convection , mass transfer , scale (ratio) , computer science , boundary value problem , mathematics , mathematical optimization , mechanics , physics , mathematical analysis , quantum mechanics
A flexible modeling approach for the accurate approximation of convection‐dominated reactive‐species boundary layers is introduced. A substitute problem is solved numerically and analyzed by employing statistical methods. The numerical data are then used to train a machine learning model that can be used to approximate the reactive mass transfer locally if a direct resolution of the concentration boundary layer is infeasible. Compared to previous modeling approaches, the machine learning model replaces the analytical solution of a simplified substitute problem, which makes it applicable to more complicated and general settings.