195 citations · 419 across the 28 of their papers we have counts for
5 papers · 1 filter
Grad-Shafranov equilibria via data-free physics informed neural networks
Byoungchan Jang, Alan A. Kaptanoglu, Rahul Gaur +3
A large number of magnetohydrodynamic (MHD) equilibrium calculations are often required for uncertainty quantification, optimization, and real-time diagnostic information, making M…
Nonlinear parametric models of viscoelastic fluid flows
Cassio M. Oishi, Alan A. Kaptanoglu, J. Nathan Kutz +1
Reduced-order models have been widely adopted in fluid mechanics, particularly in the context of Newtonian fluid flows. These models offer the ability to predict complex dynamics,…
Topology optimization for inverse magnetostatics as sparse regression: application to electromagnetic coils for stellarators
Alan A. Kaptanoglu, Gabriel P. Langlois, Matt Landreman
Topology optimization, a technique to determine where material should be placed within a predefined volume in order to minimize a physical objective, is used across a wide range of…
Benchmarking sparse system identification with low-dimensional chaos
Alan A. Kaptanoglu, Lanyue Zhang, Zachary G. Nicolaou +2
Sparse system identification is the data-driven process of obtaining parsimonious differential equations that describe the evolution of a dynamical system, balancing model complexi…
Periodic Korteweg-de Vries soliton potentials generate quasisymmetric magnetic fields
W. Sengupta, N. Nikulsin, S. Buller +6
Quasisymmetry (QS) is a hidden symmetry of the magnetic field strength, B, that effectively confines charged particles in a three-dimensional toroidal plasma equilibrium. Here, we…