Ramin Bostanabad
Cited by
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A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality
MA Bessa, R Bostanabad, Z Liu, A Hu, DW Apley, C Brinson, W Chen, ...
Computer Methods in Applied Mechanics and Engineering 320, 633-667, 2017
Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques
R Bostanabad, Y Zhang, X Li, T Kearney, LC Brinson, DW Apley, WK Liu, ...
Progress in Materials Science 95, 1-41, 2018
Deep learning predicts path-dependent plasticity
M Mozaffar, R Bostanabad, W Chen, K Ehmann, J Cao, MA Bessa
Proceedings of the National Academy of Sciences 116 (52), 26414-26420, 2019
Stochastic microstructure characterization and reconstruction via supervised learning
R Bostanabad, AT Bui, W Xie, DW Apley, W Chen
Acta Materialia 103, 89-102, 2016
Uncertainty quantification in multiscale simulation of woven fiber composites
R Bostanabad, B Liang, J Gao, WK Liu, J Cao, D Zeng, X Su, H Xu, Y Li, ...
Computer Methods in Applied Mechanics and Engineering 338, 506-532, 2018
Leveraging the nugget parameter for efficient Gaussian process modeling
R Bostanabad, T Kearney, S Tao, DW Apley, W Chen
International journal for numerical methods in engineering 114 (5), 501-516, 2018
Characterization and reconstruction of 3D stochastic microstructures via supervised learning
R Bostanabad, W Chen, DW Apley
Journal of microscopy 264 (3), 282-297, 2016
Globally approximate gaussian processes for big data with application to data-driven metamaterials design
R Bostanabad, YC Chan, L Wang, P Zhu, W Chen
Journal of Mechanical Design 141 (11), 2019
Enhanced Gaussian process metamodeling and collaborative optimization for vehicle suspension design optimization
S Tao, K Shintani, R Bostanabad, YC Chan, G Yang, H Meingast, W Chen
International Design Engineering Technical Conferences and Computers and …, 2017
A numerical Bayesian-calibrated characterization method for multiscale prepreg preforming simulations with tension-shear coupling
W Zhang, R Bostanabad, B Liang, X Su, D Zeng, MA Bessa, Y Wang, ...
Composites Science and Technology 170, 15-24, 2019
Reconstruction of 3D microstructures from 2D images via transfer learning
R Bostanabad
Computer-Aided Design 128, 102906, 2020
Characterization of the optical properties of turbid media by supervised learning of scattering patterns
I Hassaninia, R Bostanabad, W Chen, H Mohseni
Scientific reports 7 (1), 1-14, 2017
Deep learning predicts boiling heat transfer
Y Suh, R Bostanabad, Y Won
Scientific reports 11 (1), 1-10, 2021
Train once and use forever: Solving boundary value problems in unseen domains with pre-trained deep learning models
H Wang, R Planas, A Chandramowlishwaran, R Bostanabad
arXiv e-prints, arXiv: 2104.10873, 2021
Multiscale modeling of carbon fiber reinforced polymer (CFRP) for integrated computational materials engineering process
J Gao, B Liang, W Zhang, Z Liu, P Cheng, R Bostanabad, J Cao, W Chen, ...
Ford Motor Company, Detroit, MI (United States), 2017
Evolutionary gaussian processes
R Planas, N Oune, R Bostanabad
Journal of Mechanical Design 143 (11), 2021
Multiscale simulation of fiber composites with spatially varying uncertainties
R Bostanabad, B Liang, A van Beek, J Gao, WK Liu, J Cao, D Zeng, X Su, ...
Uncertainty Quantification in Multiscale Materials Modeling, 355-384, 2020
Latent map Gaussian processes for mixed variable metamodeling
N Oune, R Bostanabad
Computer Methods in Applied Mechanics and Engineering 387, 114128, 2021
Extrapolation With Gaussian Random Processes and Evolutionary Programming
R Planas, N Oune, R Bostanabad
International Design Engineering Technical Conferences and Computers and …, 2020
Reduced-order multiscale modeling of plastic deformations in 3D alloys with spatially varying porosity by deflated clustering analysis
S Deng, C Soderhjelm, D Apelian, R Bostanabad
Computational Mechanics 70 (3), 517-548, 2022
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