most citedData-driven classification of sheared stratified turbulence from experimental shadowgraphs

2 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2024

Routes to stratified turbulence and temporal intermittency revealed by a cluster-based network model of experimental data

Adrien Lefauve, Yui Hin Marvil Cheung, Xianyang Jiang +1

Modelling fluid turbulence using a `skeleton' of coherent structures has traditionally progressed by focusing on a few canonical laboratory experiments such as pipe flow and Taylor…

physics.flu-dyn2024

Boiling stratified flow: a laboratory analogy for atmospheric moist convection

Hao Fu, Claudia Cenedese, Adrien Lefauve +1

We present a novel laboratory experiment, boiling stratified flow, as an analogy for atmospheric moist convection. A layer of diluted syrup is placed below freshwater in a beaker a…

physics.flu-dyn20231 cited

Physics-informed neural network to augment experimental data: an application to stratified flows

Lu Zhu, Xianyang Jiang, Adrien Lefauve +2

We develop a physics-informed neural network (PINN) to significantly augment state-of-the-art experimental data and apply it to stratified flows. The PINN is a fully-connected deep…

physics.flu-dyn20232 cited

Routes to stratified turbulence revealed by unsupervised classification of experimental data

Adrien Lefauve, Miles M. P. Couchman

Modeling fluid turbulence using a 'skeleton' of coherent structures has traditionally progressed by focusing on a few canonical experiments, such as pipe flow and Taylor-Couette fl…

physics.flu-dyn20232 cited

Data-driven classification of sheared stratified turbulence from experimental shadowgraphs

Adrien Lefauve, Miles M. P. Couchman

We propose a dimensionality reduction and unsupervised clustering method for the automatic classification and reduced-order modeling of density-stratified turbulence in laboratory…