Reservoir computing of three-dimensional turbulent convection
Florian Heyder and Jörg Schumacher

Data-driven thermochemical model for simulating hypersonic reacting flows
Clément Scherding, Taraneh Sayadi, Georgios Rigas, Denis Sipp and Peter J. Schmid

Modal analysis of a 3D gravitational liquid sheet
Antonio Colanera, Alessandro Della Pia, Maria Rosaria Acquaviva, Matteo Chiatto and Luigi de Luca

Solving natural convection problems in annulus pipes using physics informed neural network
Ehsan Fattahi, Seyedalborz Manavi and Thomas Becker

Multi-fidelity modeling of single dendritic crystal growth of binary alloys
Josef M. Winter, Jakob W. J. Kaiser, Meike Tütken, Stefan Adami and Nikolaus A. Adams

A physics-constrained neural network for super-resolution of turbulent Rayleigh-Bénard Convection
Diane Salim, David Sondak and Blakesley Burkhart

Reinforcement learning for discretization-aware LES models
Marius Kurz and Andrea Beck

Correcting the discretization error of coarse grid CFD simulations with machine learning
Anna Kiener, Stefan Langer and Philipp Bekemeyer

Learning and Inference assisted by Feature Space Engineering (LIFE): A generalizable approach for data-driven augmentation of Physical Models
Karthik Duraisamy, Vishal Srivastava and Niloy Gupta

Data set generation at novel test-rig for validation of numerical models using in-house algorithms
Agata Widuch, Marcin Nowak, Dawid Sukiennik, Kari Myöhänen, Markku Nikku, Alessandro Parente and Wojciech Adamczyk

Solving partial differential equations using physics informed cascade neural network
Seyedalborz Manavi, Ehsan Fattahi and Thomas Becker

Exploration of data-driven numerical methods for fluid flows by end-to-end optimization
Aaron Buhendwa, Deniz Bezgin and Nikolaus Adams

Active flow control on airfoils through deep reinforcement learning
Pol Suarez, Pau Varela, Juan Echevarría, Jean Rabault, Maxence Deferrez, Bernat Font, Luis Miguel García-Cuevas, Arnau Miró, Andrés Tiseira, Oriol Lehmkhul and Ricardo Vinuesa

Data-Driven Surrogate Modelling of Aerodynamic Forces on the Superstructure of Container Vessels
Rupert Pache and Thomas Rung

Deep learning based data assimilation for  aeroelasticity and non-linear aerodynamics  
Avicene Chaarane, Jean-Camille Chassaing and Taraneh Sayadi

Surrogate modeling of unsteady aerodynamic loads acting on a plunging airfoil
Rahul Sundar, Virendra Kumar, Dipanjan Majumdar, Chhotelal Shah and Sunetra Sarkar

Wind flow field predictions over high-rise buildings using machine learning framework
Onkar Jadhav, Anina Glumac and Stephane Bordas

Efficient data-driven control of fluids using autonomous surrogate models
Sebastian Peitz and Katharina Bieker