Conference Agenda

Session
MS01_05: Minisymposium - Data Science and AI in Fluid Mechanics
Time:
Wednesday, 18/September/2024:
2:30pm - 4:30pm

Session Chair: Michele Buzzicotti, University of Rome Tor Vergata and INFN
Location: H06

C.A.R.L.-Central Auditorium for Research and Learning Claßenstr. 11 52072 Aachen

Presentations
2:30pm - 2:45pm

Deep reinforcement learning for autonomous navigation in complex flows

Selim Mecanna1,2,3,4, Aurore Loisy1,2,3,4, Christophe Eloy1,2,3,4

1Aix Marseille Université; 2Centrale Méditerranée; 3CNRS; 4IRPHE

Mecanna-Deep reinforcement learning for autonomous navigation-738.pdf


2:45pm - 3:00pm

Deep Reinforcement Learning for Active Flow Control: Where we stand, and perspectives for the years to come

Jean Rabault1, Pol Suarez2, Francisco Alcantara-Avila2, Luca Guastoni2, Bernat Font3, Arnau Miro4, Xavier Garcia Lozano2, Joel Vasanth5, Joongoo Jeon6, Oriol Lehmkuhl4, Ricardo Vinuesa2

1Independent Researcher, Oslo, Norway; 2KTH Royal Institute of Technology, Stockholm, Sweden; 3TU Delft, Delft, Netherlands; 4Barcelona Supercomputing Center, Barcelona, Spain; 5National Institute of Standards and Technology, Gaithersburg, United States; 6Jeonbuk National University, Jeonju, Republic of Korea

Rabault-Deep Reinforcement Learning for Active Flow Control-938.pdf


3:00pm - 3:15pm

Deep learning-based reduced order model for three-dimensional unsteady flow with mesh transformation and stitching

Chen Gang, Xin Li

School of Aerospace Engineering, Xi’an Jiaotong University

Gang-Deep learning-based reduced order model for three-dimensional unsteady flow with-1377.pdf


3:15pm - 3:30pm

Data-driven correlations for thermohydraulic roughness properties

Simon Dalpke1, Jiasheng Yang1, Pourya Forooghi2, Bettina Frohnapfel1, Alexander Stroh1

1Institute of Fluid Mechanics, Karlsruhe Institute of Technology; 2Department of Mechanical & Production Engineering, Aarhus University

Dalpke-Data-driven correlations for thermohydraulic roughness properties-778.pdf


3:30pm - 3:45pm

Bayesian olfactory search in realistic turbulent flows

Robin A. Heinonen1, Fabio Bonaccorso1, Luca Biferale1, Antonio Celani2, Massimo Vergassola3

1University of Rome, "Tor Vergata"; 2The Abdus Salam International Center for Theoretical Physics; 3Ecole Normale Superieure

Heinonen-Bayesian olfactory search in realistic turbulent flows-214.pdf


3:45pm - 4:00pm

Bayesian Approaches for Odor Source Localization in a Turbulent Environment

Lorenzo Piro1, Robin A. Heinonen1, Massimo Cencini2,3, Luca Biferale1

1Department of Physics & INFN, University of Rome ''Tor Vergata", Via della Ricerca Scientifica 1, 00133 Rome, Italy; 2Istituto dei Sistemi Complessi, CNR, Via dei Taurini 19, 00185 Rome, Italy; 3INFN ''Tor Vergata", Via della Ricerca Scientifica 1, 00133 Rome, Italy

Piro-Bayesian Approaches for Odor Source Localization in a Turbulent Environment-483.pdf


4:00pm - 4:15pm

An LES Informed Augmented Turbulence Kinetic Energy Neural Network Model for Near-wall Jet Flows

Christopher David Ellis1, Hao Xia2, Stephen Ambrose1

1University of Nottingham; 2Loughborough University

Ellis-An LES Informed Augmented Turbulence Kinetic Energy Neural Network Model-848.pdf