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20082026
most citedHeterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS

966 citations

Showing physics.flu-dynShow all

124 papers · 1 filter

physics.flu-dyn2024★ 12 cited

Bursting bubble in an elasto-viscoplastic medium

A. G. Balasubramanian, V. Sanjay, M. Jalaal +2

A gas bubble sitting at a liquid-gas interface can burst following the rupture of the thin liquid film separating it from the ambient, owing to the large surface energy of the resu…

physics.flu-dyn2024★ 4 cited

Drag prediction of rough-wall turbulent flow using data-driven regression

Zhaoyu Shi, Seyed Morteza Habibi Khorasani, Heesoo Shin +3

Efficient tools for predicting the drag of rough walls in turbulent flows would have a tremendous impact. However, methods for drag prediction rely on experiments or numerical simu…

physics.flu-dyn2024★ 2 cited

Prediction of flow and elastic stresses in a viscoelastic turbulent channel flow using convolutional neural networks

Arivazhagan G. Balasubramanian, Ricardo Vinuesa, Outi Tammisola

Neural-network models have been employed to predict the instantaneous flow close to the wall in a viscoelastic turbulent channel flow. Numerical simulation data at the wall is util…

physics.flu-dyn2024★ 3 cited

The effect of contact angle hysteresis on a droplet in a viscoelastic two-phase system

Kazem Bazesefidpar, Outi Tammisola

We investigate the dynamic behaviour of a two-dimensional (2D) droplet adhering to a wall in Poiseuille flow at low Reynolds numbers, in a system where either the droplet is viscoe…

physics.flu-dyn2023★ 13 cited

The impact of finite span and wing-tip vortices on a turbulent NACA0012 wing

Siavash Toosi, Adam Peplinski, Philipp Schlatter +1

High-fidelity simulations are conducted to investigate the turbulent boundary layers around a finite-span NACA0012 wing with a rounded wing-tip geometry at a chord-based Reynolds n…

physics.flu-dyn2023★ 13 cited

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…