28 citations · 65 across the 11 of their papers we have counts for
11 papers
Algebraic Multigrid with Filtering: An Efficient Preconditioner for Interior Point Methods in Large-Scale Contact Mechanics Optimization
Socratis Petrides, Tucker Hartland, Tzanio Kolev +6
Large-scale contact mechanics simulations are crucial in many engineering fields such as structural design and manufacturing. In the frictionless case, contact can be modeled by mi…
Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization
Tobias Duswald, Brendan Keith, Boyan Lazarov +2
This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on applications in computational m…
High-performance finite elements with MFEM
Julian Andrej, Nabil Atallah, Jan-Phillip Bäcker +15
The MFEM (Modular Finite Element Methods) library is a high-performance C++ library for finite element discretizations. MFEM supports numerous types of finite element methods and i…
DynAMO: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws
Tarik Dzanic, Ketan Mittal, Dohyun Kim +4
We introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost a…
An Adaptive Sampling Augmented Lagrangian Method for Stochastic Optimization with Deterministic Constraints
Raghu Bollapragada, Cem Karamanli, Brendan Keith +3
The primary goal of this paper is to provide an efficient solution algorithm based on the augmented Lagrangian framework for optimization problems with a stochastic objective funct…
Scalable DPG Multigrid Solver for Helmholtz Problems: A Study on Convergence
Jacob Badger, Stefan Henneking, Socratis Petrides +1
This paper presents a scalable multigrid preconditioner targeting large-scale systems arising from discontinuous Petrov-Galerkin (DPG) discretizations of high-frequency wave operat…
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…
An adaptive multigrid solver for DPG methods with applications in linear acoustics and electromagnetics
Socratis Petrides, Leszek Demkowicz
We propose an adaptive multigrid preconditioning technology for solving linear systems arising from Discontinuous Petrov-Galerkin (DPG) discretizations. Unlike standard multigrid t…
A 3D DPG Maxwell Approach to Nonlinear Raman Gain in Fiber Laser Amplifiers
S. Nagaraj, J. Grosek, S. Petrides +2
We propose a three dimensional Discontinuous Petrov-Galerkin Maxwell approach for modeling Raman gain in fiber laser amplifiers. In contrast with popular beam propagation models, w…
Discrete least-squares finite element methods
Brendan Keith, Socratis Petrides, Federico Fuentes +1
A finite element methodology for large classes of variational boundary value problems is defined which involves discretizing two linear operators: (1) the differential operator def…