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S2-11: Machine Learning and Multiphase flows
Time:
Monday, 12/May/2025:
2:40pm - 4:20pm
Session Chair: Fanyong Meng
Location: Mercure Salle 1
Presentations
2:40pm - 3:00pm Identification of population balance model parameters for reactive solid-liquid systems with machine learning
Antonello Raponi, Antonio Buffo, Gianluca Boccardo, Marco Vanni, Daniele Marchisio
Politecnico di Torino, Italy
3:00pm - 3:20pm Three Dimensional Modeling of Filtration Process in Complex Filter Structures using a data-free Physics-Informed Neural Network coupled with Smoothed Particle Hydrodynamic
Amin Zargaran , Fabian Hartwig, Uwe Janoske
University of Wuppertal, Germany
3:20pm - 3:40pm Advanced Pore Network Modelling (PNM) for Packed-Bed Reactors: A Neural Network Approach Using PR-CFD Data
Cristina Garcia Llamas , E.A.J.F. Frank Peters, J. A. M. Hans Kuipers
Eindhoven University of Technology, Netherlands
3:40pm - 4:00pm Prediction of heat transfer characteristics during flow condensation inside enhanced structured tubes using artificial neural network
Anil Kumar, Amit Kumar, Ravi Kumar, Arup Kumar Das
Indian Institute of Technology Roorkee, India
4:00pm - 4:20pm ANN predictions of particle trajectories in a turbulent jet
Julien ZABIOLLE 1 , Mickael Bourgoin2 , Raúl Bayoán Cal3 , Bianca Viggiano1 , Roberto Paoli1
1 Polytechnique Montréal, département mécanique, Montréal (QC) Canada; 2 Univ Lyon, Ens de Lyon, Univ Claude Bernard, CNRS, Laboratoire de Physique, Lyon, France; 3 Department of Mechanical Engineering, Portland State University, Portland, OR 97201, USA
