106 citations · 360 across the 21 of their papers we have counts for
21 papers
Proximal Galerkin: A structure-preserving finite element method for pointwise bound constraints
Brendan Keith, Thomas M. Surowiec
The proximal Galerkin finite element method is a high-order, low-iteration complexity, nonlinear numerical method that preserves the geometric and algebraic structure of point-wise…
Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement
Jiachen Yang, Ketan Mittal, Tarik Dzanic +5
Adaptive mesh refinement (AMR) is necessary for efficient finite element simulations of complex physical phenomenon, as it allocates limited computational budget based on the need…
Learning robust marking policies for adaptive mesh refinement
Andrew Gillette, Brendan Keith, Socratis Petrides
In this work, we revisit the marking decisions made in the standard adaptive finite element method (AFEM). Experience shows that a naïve marking policy leads to inefficient use of…
Risk-averse design of tall buildings for uncertain wind conditions
Anoop Kodakkal, Brendan Keith, Ustim Khristenko +4
Reducing the intensity of wind excitation via aerodynamic shape modification is a major strategy to mitigate the reaction forces on supertall buildings, reduce construction and mai…
Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer
Brendan Keith, Ustim Khristenko, Barbara Wohlmuth
We develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as t…
Learning orbital dynamics of binary black hole systems from gravitational wave measurements
Brendan Keith, Akshay Khadse, Scott E. Field
We introduce a gravitational waveform inversion strategy that discovers mechanical models of binary black hole (BBH) systems. We show that only a single time series of (possibly no…