19 citations · 22 across the 3 of their papers we have counts for
4 papers · 1 filter
An empirical mean-field model of symmetry-breaking in a turbulent wake
Jared L. Callaham, Georgios Rigas, Jean-Christophe Loiseau +1
This work develops a low-dimensional nonlinear stochastic model of symmetry-breaking coherent structures from experimental measurements of a turbulent axisymmetric bluff body wake.…
Promoting global stability in data-driven models of quadratic nonlinear dynamics
Alan A. Kaptanoglu, Jared L. Callaham, Christopher J. Hansen +2
Modeling realistic fluid and plasma flows is computationally intensive, motivating the use of reduced-order models for a variety of scientific and engineering tasks. However, it is…
Learning dominant physical processes with data-driven balance models
Jared L. Callaham, James V. Koch, Bingni W. Brunton +2
Throughout the history of science, physics-based modeling has relied on judiciously approximating observed dynamics as a balance between a few dominant processes. However, this tra…
Robust flow field reconstruction from limited measurements via sparse representation
Jared Callaham, Kazuki Maeda, Steven L. Brunton
In many applications it is important to estimate a fluid flow field from limited and possibly corrupt measurements. Current methods in flow estimation often use least squares regre…