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Particle-based adaptive coupling of 3D and 2D fluid flow models.

Authors :
Suchde, Pratik
Source :
Computer Methods in Applied Mechanics & Engineering. Sep2024, Vol. 429, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

This paper proposes the notion of model adaptivity for fluid flow modelling, where the underlying model (the governing equations) is adaptively changed in space and time. Specifically, this work introduces a hybrid and adaptive coupling of a 3D bulk fluid flow model with a 2D thin film flow model. As a result, this work extends the applicability of existing thin film flow models to complex scenarios where, for example, bulk flow develops into thin films after striking a surface. At each location in space and time, the proposed framework automatically decides whether a 3D model or a 2D model must be applied. Using a meshless approach for both 3D and 2D models, at each particle, the decision to apply a 2D or 3D model is based on the user-prescribed resolution and a local principal component analysis. When a particle needs to be changed from a 3D model to 2D, or vice versa, the discretization is changed, and all relevant data mapping is done on-the-fly. Appropriate two-way coupling conditions and mass conservation considerations between the 3D and 2D models are also developed. Numerical results show that this model adaptive framework shows higher flexibility and compares well against finely resolved 3D simulations. In an actual application scenario, a 3 factor speed up is obtained, while maintaining the accuracy of the solution. • Novel notion of model adaptivity: governing equations are adaptively changed. • Coupling 3D Navier–Stokes and 2D thin film flow. • No a-priori information describing where to use which model. • Model and discretization changed on-the-fly. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00457825
Volume :
429
Database :
Academic Search Index
Journal :
Computer Methods in Applied Mechanics & Engineering
Publication Type :
Academic Journal
Accession number :
178734417
Full Text :
https://doi.org/10.1016/j.cma.2024.117199