Rayleigh–Taylor and Richtmyer–Meshkov instabilities: a journey through scales

Y Zhou, RJR Williams, P Ramaprabhu, M Groom… - Physica D: Nonlinear …, 2021 - Elsevier
Hydrodynamic instabilities such as Rayleigh–Taylor (RT) and Richtmyer–Meshkov (RM)
instabilities usually appear in conjunction with the Kelvin–Helmholtz (KH) instability and are …

Data-driven modeling for unsteady aerodynamics and aeroelasticity

J Kou, W Zhang - Progress in Aerospace Sciences, 2021 - Elsevier
Aerodynamic modeling plays an important role in multiphysics and design problems, in
addition to experiment and numerical simulation, due to its low-dimensional representation …

Machine learning–accelerated computational fluid dynamics

D Kochkov, JA Smith, A Alieva… - Proceedings of the …, 2021 - National Acad Sciences
Numerical simulation of fluids plays an essential role in modeling many physical
phenomena, such as weather, climate, aerodynamics, and plasma physics. Fluids are well …

Cascades and transitions in turbulent flows

A Alexakis, L Biferale - Physics Reports, 2018 - Elsevier
Turbulent flows are characterized by the non-linear cascades of energy and other inviscid
invariants across a huge range of scales, from where they are injected to where they are …

[HTML][HTML] Recent advances on the numerical modelling of turbulent flows

CD Argyropoulos, NC Markatos - Applied Mathematical Modelling, 2015 - Elsevier
This paper reviews the problems and successes of computing turbulent flow. Most of the flow
phenomena that are important to modern technology involve turbulence. The review is …

Turbulence theories and statistical closure approaches

Y Zhou - Physics Reports, 2021 - Elsevier
When discussing research in physics and in science more generally, it is common to ascribe
equal importance to the three components of the scientific trinity: theoretical, experimental …

[HTML][HTML] Large-eddy simulation: Past, present and the future

Y Zhiyin - Chinese journal of Aeronautics, 2015 - Elsevier
Large-eddy simulation (LES) was originally proposed for simulating atmospheric flows in the
1960s and has become one of the most promising and successful methodology for …

DPM: A deep learning PDE augmentation method with application to large-eddy simulation

J Sirignano, JF MacArt, JB Freund - Journal of Computational Physics, 2020 - Elsevier
A framework is introduced that leverages known physics to reduce overfitting in machine
learning for scientific applications. The partial differential equation (PDE) that expresses the …

[HTML][HTML] Wind turbine wake models developed at the technical university of Denmark: A review

T Göçmen, P Van der Laan, PE Réthoré… - … and Sustainable Energy …, 2016 - Elsevier
Wind turbine wakes are one of the most important aspects in wind power meteorology
because they decrease the power production and increase the loading of downstream wind …

Using singular values to build a subgrid-scale model for large eddy simulations

F Nicoud, HB Toda, O Cabrit, S Bose, J Lee - Physics of fluids, 2011 - pubs.aip.org
An eddy-viscosity based, subgrid-scale model for large eddy simulations is derived from the
analysis of the singular values of the resolved velocity gradient tensor. The proposed σ …