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Title: A finite element/neural network framework for modeling suspensions of non-spherical particles
Author(s): Minakowska, Martyna
Richter, Thomas
Sager, SebastianLook up in the Integrated Authority File of the German National Library
Issue Date: 2021
Type: Article
Language: English
URN: urn:nbn:de:gbv:ma9:1-1981185920-1020463
Subjects: Non-spherical particles
Finite element method
Neural network
Abstract: An accurate prediction of the translational and rotational motion of particles suspended in a fluid is only possible if a complete set of correlations for the force coefficients of fluid-particle interaction is known. The present study is thus devoted to the derivation and validation of a new framework to determine the drag, lift, rotational and pitching torque coefficients for different non-spherical particles in a fluid flow. The motivation for the study arises from medical applications, where particles may have an arbitrary and complex shape. Here, it is usually not possible to derive accurate analytical models for predicting the different hydrodynamic forces. The presented model is designed to be applicable to a broad range of shapes. Another important feature of the suspensions occurring in medical and biological applications is the high number of particles. The modelling approach we propose can be efficiently used for simulations of solid-liquid suspensions with numerous particles. Based on resolved numerical simulations of prototypical particles we generate data to train a neural network which allows us to quickly estimate the hydrodynamic forces experienced by a specific particle immersed in a fluid.
Open Access: Open access publication
License: (CC BY 4.0) Creative Commons Attribution 4.0(CC BY 4.0) Creative Commons Attribution 4.0
Sponsor/Funder: Projekt DEAL 2021
Journal Title: Vietnam journal of mathematics
Publisher: Springer
Publisher Place: Singapore
Volume: 49
Issue: 1
Original Publication: 10.1007/s10013-021-00477-9
Page Start: 207
Page End: 235
Appears in Collections:Fakultät für Mathematik (OA)

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