M. Giselle Fernández-Godino
Title
Cited by
Cited by
Year
Review of multi-fidelity models
MG Fernández-Godino, C Park, NH Kim, RT Haftka
arXiv preprint arXiv:1609.07196, 2016
1282016
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
362019
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
72016
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
52019
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
52018
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
42016
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
3*2021
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), 2019
32019
Quantifying Particle Departure from Axisymmetry in Multiphase Cylindrical Detonation
MG Fernández-Godino
University of Florida, 2018
32018
StressNet-Deep learning to predict stress with fracture propagation in brittle materials
Y Wang, D Oyen, WG Guo, A Mehta, CB Scott, N Panda, ...
npj Materials Degradation 5 (1), 1-10, 2021
22021
Exploring Sensitivity of ICF Outputs to Design Parameters in Experiments Using Machine Learning
JB Nakhleh, MG Fernández-Godino, MJ Grosskopf, BM Wilson, J Kline, ...
arXiv preprint arXiv:2010.04254, 2020
12020
On the use of symmetries in building surrogate models
M Giselle Fernández-Godino, S Balachandar, RT Haftka
Journal of Mechanical Design 141 (6), 2019
1*2019
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
2021
Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture
C Garcia-Cardona, MG Fernández-Godino, D O'Malley, T Bhattacharya
arXiv preprint arXiv:2012.15739, 2020
2020
Identifying Entangled Physics Relationships through Sparse Matrix Decomposition to Inform Plasma Fusion Design
MG Fernández-Godino, MJ Grosskopf, JB Nakhleh, BM Wilson, J Kline, ...
arXiv preprint arXiv:2010.15208, 2020
2020
Flyer Plate Continuum Simulations Informed with Machine Learning Crack Evolution
MG Fernandez-Godino, N Panda, D O'Malley, KS Hickmann, DA Oyen, ...
AIAA Scitech 2020 Forum, 1410, 2020
2020
Desarrollo de un programa de vigilancia para el reactor nuclear CAREM 25
MG Fernandez-Godino
Integration Project in Nuclear Engineering, 2014
2014
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Articles 1–17