On the use of rhodium mirrors for optical diagnostics in ITER P Mertens, R Boman, S Dickheuer, Y Krasikov, A Krimmer, D Leichtle, ... Fusion engineering and design 146, 2514-2518, 2019 | 11 | 2019 |
PyAlbany: A Python interface to the C++ multiphysics solver Albany K Liegeois, M Perego, T Hartland Journal of Computational and Applied Mathematics 425, 115037, 2023 | 5 | 2023 |
GMRES with embedded ensemble propagation for the efficient solution of parametric linear systems in uncertainty quantification of computational models K Liegeois, R Boman, ET Phipps, TA Wiesner, M Arnst Computer Methods in Applied Mechanics and Engineering 369, 113188, 2020 | 4 | 2020 |
Hierarchical off-diagonal low-rank approximation of Hessians in inverse problems, with application to ice sheet model initialization T Hartland, G Stadler, M Perego, K Liegeois, N Petra Inverse Problems 39 (8), 085006, 2023 | 3 | 2023 |
Performance Portable Batched Sparse Linear Solvers K Liegeois, S Rajamanickam, L Berger-Vergiat IEEE Transactions on Parallel and Distributed Systems 34 (5), 1524-1535, 2023 | 2 | 2023 |
PyTrilinos2: automatic (re) generation of a Python interface for Trilinos. K Liegeois, C Glusa Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Computationally efficient estimation of the extreme event probability of the mass loss of Greenland and Antarctic ice sheets. K Liegeois, M Perego, G Stadler Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Kokkos Kernels Math Library. L Berger-Vergiat, S Rajamanickam, J Loe, B Kelley, E Harvey, J Foucar, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Performance portable batched sparse linear solvers in Kokkos Kernels. K Liegeois, S Rajamanickam, L Berger-Vergiat Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Kokkos Kernels (Sake project). L Berger-Vergiat, S Rajamanickam, V Dang, B Kelley, N Ellingwood, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
On the extreme event probability estimation of land ice mass loss [Slides] K Liegeois, M Perego, G Stadler Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
Ice sheet initialization as an integral part of ice sheet modeling M Perego, L Bertagna, T Hartland, T Hillebrand, M Hoffman, K Liegeois, ... AGU Fall Meeting Abstracts 2021, C25A-01, 2021 | | 2021 |
Hierarchical off-diagonal Hessian approximation for Bayesian inverse problems with application to the flow of the Greenland ice sheet. T Hartland, G Stadler, M Perego, KAJ Liegeois, N Petra Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021 | | 2021 |
PyAlbany: a Python wrapper for Albany. K Liegeois Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2021 | | 2021 |
Ensemble propagation for efficient uncertainty quantification: Application to the thermomechanical modeling of a first mirror for the ITER core CXRS diagnostics K Liegeois, R Boman, E Phipps, P Mertens, Y Krasikov, M Arnst UNCECOMP 2019/3rd International Conference on Uncertainty Quantification in …, 2019 | | 2019 |
Efficient parametric computations using ensemble propagation for high dimensional finite element models K Liegeois, R Boman, E Phipps, M Arnst CÉCI Scientific Meeting, 2019 | | 2019 |
On the Ensemble Propagation for Efficient Uncertainty Quantification of Mechanical Contact Problems K Liegeois, R Boman, E Phipps, T Wiesner, M Arnst SIAM Conference on Uncertainty Quanti cation 2018, 2018 | | 2018 |
Ensemble propagation for efficient uncertainty quantification on emerging architectures: Application to thermomechanical contact K Liegeois, R Boman, P Mertens, A Panin, E Phipps, M Arnst Quantification of Uncertainty: Improving Efficiency and Technology, 2017 | | 2017 |
Comparison of interval and stochastic methods for uncertainty quantification in metal forming M Arnst, K Liegeois, R Boman, JP Ponthot ICOMP International Conference on COmputational methods in Manufacturing …, 2016 | | 2016 |