481 citations · 1.2k across the 57 of their papers we have counts for
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Widest scales in turbulent channels
Ramón Pozuelo, André V. G. Cavalieri, Philipp Schlatter +1
The widest spanwise scales in turbulent channel flows are studied through the use of three periodic channel-flow simulations at friction Reynolds number . The le…
Instability of the optimal edge trajectory in the Blasius boundary layer
Miguel Beneitez, Yohann Duguet, Philipp Schlatter +1
In the context of linear stability analysis, considering unsteady base flows is notoriously difficult. A generalisation of modal linear stability analysis, allowing for arbitrarily…
Predicting the wall-shear stress and wall pressure through convolutional neural networks
Arivazhagan G. Balasubramanian, Luca Guastoni, Philipp Schlatter +2
The objective of this study is to assess the capability of convolution-based neural networks to predict wall quantities in a turbulent open channel flow. The first tests are perfor…
Deep reinforcement learning for turbulent drag reduction in channel flows
L. Guastoni, J. Rabault, P. Schlatter +2
We introduce a reinforcement learning (RL) environment to design and benchmark control strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The environ…
Direct numerical simulation of a zero-pressure-gradient thermal turbulent boundary layer up to
Arivazhagan G. Balasubramanian, Luca Guastoni, Philipp Schlatter +1
The objective of the present study is to provide a numerical database of thermal boundary layers and to contribute to the understanding of the dynamics of passive scalars at differ…
Efficient prediction of turbulent flow quantities using a Bayesian hierarchical multifidelity model
Saleh Rezaeiravesh, Timofey Mukha, Philipp Schlatter
High-fidelity scale-resolving simulations of turbulent flows quickly become prohibitively expensive, especially at high Reynolds numbers. As a remedy, we may use multifidelity mode…