A physics-informed machine learning model for the prediction of drop breakup in two-phase flows-Reference-Cited by-同舟云学术

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A physics-informed machine learning model for the prediction of drop breakup in two-phase flows

Published:2024-11 Issue: Volume:180 Page:104934
ISSN:0301-9322
Container-title:International Journal of Multiphase Flow
language:en
Short-container-title:International Journal of Multiphase Flow

Author:

Cundy Chris,Mirjalili Shahab^ORCID,Laurent Charlélie^ORCID,Ermon Stefano^ORCID,Iaccarino Gianluca,Mani Ali^ORCID

Funder

US Department of Energy

Publisher

Elsevier BV

Reference35 articles.

1. On spray formation;Anon;J. Fluid Mech.,2004

2. LES of atomizing spray with stochastic modeling of secondary breakup;Apte;Int. J. Multiph. Flow,2003

3. Neural flows: Efficient alternative to neural ODEs;Biloš;Adv. Neural Inf. Process. Syst.,2021

4. Birth of microbubbles in turbulent breaking waves;Chan;Phys. Rev. Fluids,2019

5. Real-world single image super-resolution: A brief review;Chen;Inf. Fusion,2022

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