106 citations · 360 across the 21 of their papers we have counts for
3 papers · 1 filter
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…