Theo dõi
M. Giselle Fernández-Godino
M. Giselle Fernández-Godino
Research Scientist, Deputy Director DSICS, Lawrence Livermore National Laboratory
Email được xác minh tại llnl.gov - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Review of multi-fidelity models
MG Fernández-Godino.
Advances in Computational Science and Engineering 1 (4), 351-400, 2023
419*2023
Issues in deciding whether to use multifidelity surrogates
M Giselle Fernández-Godino, C Park, NH Kim, RT Haftka
Aiaa Journal 57 (5), 2039-2054, 2019
2092019
StressNet-Deep learning to predict stress with fracture propagation in brittle materials
Y Wang, D Oyen, W Guo, A Mehta, CB Scott, N Panda, ...
Npj Materials Degradation 5 (1), 6, 2021
642021
Linear regression based multi-fidelity surrogate for disturbance amplification in multi-phase explosion
MG Fernández-Godino, S Dubreuil, N Bartoli, C Gogu, S Balachandar, ...
Structural and Multidisciplinary Optimization 60 (6), 2205-22220, 2019
232019
Deep convolutional autoencoders as generic feature extractors in seismological applications
Q Kong, A Chiang, AC Aguiar, MG Fernández-Godino, SC Myers, ...
Artificial Intelligence in Geosciences 2, 96-106, 2021
202021
Early time evolution of circumferential perturbation of initial particle volume fraction in explosive cylindrical multiphase dispersion
MG Fernández-Godino, F Ouellet, RT Haftka, S Balachandar
Journal of Fluids Engineering 141 (9), 091302, 2019
142019
Exploring sensitivity of icf outputs to design parameters in experiments using machine learning
JB Nakhleh, MG Fernández-Godino, MJ Grosskopf, BM Wilson, J Kline, ...
IEEE Transactions on Plasma Science 49 (7), 2238-2246, 2021
122021
Accelerating high-strain continuum-scale brittle fracture simulations with machine learning
MG Fernández-Godino, N Panda, D O’Malley, K Larkin, A Hunter, ...
Computational Materials Science 186, 109959, 2021
122021
Anomaly Detection Using Groups of Simulations
MG Fernández–Godino, A Diggs, C Park, NH Kim, RT Haftka
18th AIAA Non-Deterministic Approaches Conference, 1195, 2016
102016
Identifying entangled physics relationships through sparse matrix decomposition to inform plasma fusion design
MG Fernández-Godino, MJ Grosskopf, JB Nakhleh, BM Wilson, JL Kline, ...
IEEE Transactions on Plasma Science 49 (8), 2410-2419, 2021
92021
On the use of symmetries in building surrogate models
M Giselle Fernández-Godino, S Balachandar, RT Haftka
Journal of Mechanical Design 141 (6), 2019
92019
Predicting wind‑driven spatial deposition through simulated color images using deep autoencoders
MG Fernández-Godino, DD Lucas, Q Kong
Nature Scientific Reports 13 (1394), 12, 2023
82023
Noise filtering and uncertainty quantification in surrogate based optimization
MG Fernández-Godino, RT Haftka, S Balachandar, C Gogu, N Bartoli, ...
2018 AIAA Non-Deterministic Approaches Conference, 2176, 2018
72018
Review of multi-fidelity models (2016)
MG Fernández-Godino, C Park, NH Kim, RT Haftka
arXiv preprint arXiv:1609.07196, 2016
72016
A data-driven non-linear assimilation framework with neural networks
N Panda, MG Fernández-Godino, HC Godinez, C Dawson
Computational Geosciences 25 (1), 233-242, 2021
62021
Validation, Uncertainty Quantification and Uncertainty Reduction for a Shock Tube Simulation
C Park, MG Fernández-Godino, NH Kim, RT Haftka
18th AIAA Non-Deterministic Approaches Conference, 1192, 2016
62016
Review of multi-fidelity models. arXiv 2016
MG Fernández-Godino, C Park, NH Kim, RT Haftka
arXiv preprint arXiv:1609.07196, 0
6
StressNet-Deep learning to predict stress with fracture propagation in brittle materials. npj Mater Degrad 5
Y Wang, D Oyen, WG Guo, A Mehta, CB Scott, N Panda, ...
52021
Quantifying particle departure from axisymmetry in multiphase cylindrical detonation
MG Fernández-Godino
Ph. D. Thesis, University of Florida, Gainesville, FL, 2018
52018
Review of multi-fidelity models
M Giselle Fernández-Godino, C Park, NH Kim, RT Haftka
arXiv e-prints, arXiv: 1609.07196, 2016
52016
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