Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows-Reference-Cited by-同舟云学术

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Integrating Graph Neural Network-Based Surrogate Modeling with Inverse Design for Granular Flows

Published:2024-05-13 Issue:20 Volume:63 Page:9225-9235
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Jiang Yu¹^ORCID,Byrne Edmond¹,Glassey Jarka¹²,Chen Xizhong³^ORCID

Affiliation:

1. Department of Process and Chemical Engineering, School of Engineering and Architecture, University College Cork, Cork, T12 K8AF, Ireland

2. Merz Court, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom

3. Department of Chemical Engineering, School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai 200240, PR China

Funder

University College Cork

Excellent Young Scientists Fund

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.iecr.4c00692

Reference45 articles.

1. Granular Media

2. Granular Media in a State of Flow

3. Powder processing—Models and simulations

4. Flow regimes and dynamic similarity of immersed granular collapse: A CFD-DEM investigation

5. Particle shape effects on granular column collapse using superquadric DEM

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1. Multiscale Modeling and Artificial Intelligence for Multiphase Flow Science;Industrial & Engineering Chemistry Research;2024-06-05

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