TY  - JOUR
N2  - We highlight the work of a multi-university collaborative programme, PREMIERE (PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems), which is at the intersection of multi-physics and machine learning, aiming to enhance predictive capabilities in complex multiphase flow systems across diverse length and time scales. Our contributions encompass a variety of approaches, including the Design of Experiments for nanoparticle synthesis optimisation, Generalised Latent Assimilation models for drop coalescence prediction, Bayesian regularised artificial neural networks, eXtreme Gradient Boosting for microdroplet formation prediction, and a sub-sampling based adversarial neural network for predicting slug flow behaviour in two-phase pipe flows. Additionally, we introduce a generalised latent assimilation technique, Long Short-Term Memory networks for sequence forecasting mixing performance in stirred and static mixers, active learning via Bayesian optimisation to recover coalescence model parameters for high current density electrolysers, Gaussian process regression for drop size distribution predictions for sprays, and acoustic emission signal inversion using gradient boosting machines to characterise particle size distribution in fluidised beds. We also offer perspectives on the development of a shape optimisation framework that leverages the use of a multi-fidelity multiphase emulator. The results presented have applications in chemical synthesis, microfluidics, product manufacturing, and green hydrogen generation.
ID  - discovery10195423
UR  - https://doi.org/10.1016/j.ijmultiphaseflow.2024.104936
TI  - Machine learning and physics-driven modelling and simulation of multiphase systems
Y1  - 2024/09//
SN  - 0301-9322
AV  - public
KW  - Machine Learning
KW  -  
Numerical simulations
KW  -  
Multiphase
KW  -  
Multi-fidelity
KW  -  
Microfluidics
KW  -  
Hybrid methods
PB  - Elsevier BV
JF  - International Journal of Multiphase Flow
A1  - Basha, Nausheen
A1  - Arcucci, Rossella
A1  - Angeli, Panagiota
A1  - Anastasiou, Charitos
A1  - Abadie, Thomas
A1  - Casas, César Quilodrán
A1  - Chen, Jianhua
A1  - Cheng, Sibo
A1  - Chagot, Loïc
A1  - Galvanin, Federico
A1  - Heaney, Claire E
A1  - Hossein, Fria
A1  - Hu, Jinwei
A1  - Kovalchuk, Nina
A1  - Kalli, Maria
A1  - Kahouadji, Lyes
A1  - Kerhouant, Morgan
A1  - Lavino, Alessio
A1  - Liang, Fuyue
A1  - Nathanael, Konstantia
A1  - Magri, Luca
A1  - Lettieri, Paola
A1  - Materazzi, Massimiliano
A1  - Erigo, Matteo
A1  - Pico, Paula
A1  - Pain, Christopher C
A1  - Shams, Mosayeb
A1  - Simmons, Mark
A1  - Traverso, Tullio
A1  - Valdes, Juan Pablo
A1  - Wolffs, Zef
A1  - Zhu, Kewei
A1  - Zhuang, Yilin
A1  - Matar, Omar K
N1  - Crown Copyright © 2024 Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
VL  - 179
ER  -