Article
Version 1
Preserved in Portico This version is not peer-reviewed
Hybrid AI-Analytical Modeling of Droplet Dynamics on Inclined Heterogeneous Surfaces
Version 1
: Received: 21 March 2024 / Approved: 22 March 2024 / Online: 22 March 2024 (11:53:49 CET)
A peer-reviewed article of this Preprint also exists.
Demou, A.D.; Savva, N. Hybrid AI-Analytical Modeling of Droplet Dynamics on Inclined Heterogeneous Surfaces. Mathematics 2024, 12, 1188. Demou, A.D.; Savva, N. Hybrid AI-Analytical Modeling of Droplet Dynamics on Inclined Heterogeneous Surfaces. Mathematics 2024, 12, 1188.
Abstract
This work presents a novel approach for the study of the movement of droplets on inclined surfaces under the influence of gravity and chemical heterogeneities. The developed numerical methodology uses data-driven modeling to extend the applicability limits of an analytically derived reduced-order model for the contact line velocity. More specifically, while the reduced-order model is able to capture the effects of the chemical heterogeneities to a satisfactory degree, it does not account for gravity. To alleviate this shortcoming, datasets generated from direct numerical simulations are used to train a data-driven model for the contact line velocity, which is based on the Fourier neural operator and corrects the reduced-order model predictions to match the reference solutions. This hybrid surrogate model, which comprises of both analytical and data-driven components, is then integrated in time to simulate the droplet movement, offering a speedup of five orders of magnitude compared to direct numerical simulations. The performance of this hybrid model is quantified and assessed in different wetting scenarios, by considering various inclination angles and values for the Bond number, demonstrating the accuracy of the predictions as long as the adopted parameters lie within the ranges considered in the training dataset.
Keywords
wetting hydrodynamics; droplet transport; reduced-order modeling; machine learning; Fourier neural operator
Subject
Physical Sciences, Fluids and Plasmas Physics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
