Zobrazeno 1 - 10
of 121
pro vyhledávání: '"Srinivasan, Gowri"'
Autor:
Pachalieva, Aleksandra, Hyman, Jeffrey D., O'Malley, Daniel, Viswanathan, Hari, Srinivasan, Gowri
We perform a set of flow and reactive transport simulations within three-dimensional fracture networks to learn the factors controlling mineral reactions. CO$_2$ mineralization requires CO$_2$-laden water, dissolution of a mineral that then leads to
Externí odkaz:
http://arxiv.org/abs/2312.13451
Autor:
D'Elia, Marta, Deng, Hang, Fraces, Cedric, Garikipati, Krishna, Graham-Brady, Lori, Howard, Amanda, Karniadakis, George, Keshavarzzadeh, Vahid, Kirby, Robert M., Kutz, Nathan, Li, Chunhui, Liu, Xing, Lu, Hannah, Newell, Pania, O'Malley, Daniel, Prodanovic, Masa, Srinivasan, Gowri, Tartakovsky, Alexandre, Tartakovsky, Daniel M., Tchelepi, Hamdi, Vazic, Bozo, Viswanathan, Hari, Yoon, Hongkyu, Zarzycki, Piotr
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material sciences with experts in the areas of heterogeneous materials, machine learn
Externí odkaz:
http://arxiv.org/abs/2202.04137
Autor:
Wang, Yinan, Oyen, Diane, Weihong, Guo, Mehta, Anishi, Scott, Cory Braker, Panda, Nishant, Fernández-Godino, M. Giselle, Srinivasan, Gowri, Yue, Xiaowei
Catastrophic failure in brittle materials is often due to the rapid growth and coalescence of cracks aided by high internal stresses. Hence, accurate prediction of maximum internal stress is critical to predicting time to failure and improving the fr
Externí odkaz:
http://arxiv.org/abs/2011.10227
Autor:
Fernández-Godino, M. Giselle, Grosskopf, Michael J., Nakhleh, Julia B., Wilson, Brandon M., Kline, John, Srinivasan, Gowri
A sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical p
Externí odkaz:
http://arxiv.org/abs/2010.15208
Autor:
Nakhleh, Julia B., Fernández-Godino, M. Giselle, Grosskopf, Michael J., Wilson, Brandon M., Kline, John, Srinivasan, Gowri
Publikováno v:
IEEE Transactions on Plasma Science, vol. 49, no. 7, pp. 2238-2246, July 2021
Building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While simulation cod
Externí odkaz:
http://arxiv.org/abs/2010.04254
Autor:
Fernández-Godino, M. Giselle, Panda, Nishant, O'Malley, Daniel, Larkin, Kevin, Hunter, Abigail, Haftka, Raphael T., Srinivasan, Gowri
Publikováno v:
Computational Materials Science, Elsevier, Volume 186, January 2021, p. 109959
Failure in brittle materials under dynamic loading conditions is a result of the propagation and coalescence of microcracks. Simulating this mechanism at the continuum level is computationally expensive or, in some cases, intractable. The computation
Externí odkaz:
http://arxiv.org/abs/2001.11328
Autor:
Ushijima-Mwesigwa, Hayato, Hyman, Jeffrey D., Hagberg, Aric, Safro, Ilya, Karra, Satish, Gable, Carl W., Sweeney, Matthew R., Srinivasan, Gowri
We present a topology-based method for mesh-partitioning in three-dimensional discrete fracture network (DFN) simulations that take advantage of the intrinsic multi-level nature of a DFN. DFN models are used to simulate flow and transport through low
Externí odkaz:
http://arxiv.org/abs/1902.08029
Autor:
Rahimi-Agham, Saeed, Chau, Viet-Tuan, Lee, Huynjin, Nguyen, Hoang, Li, Weixin, Karra, Satish, Rougier, Esteban, Viswanathan, Hari, Srinivasan, Gowri, Bazant, Zdenek P.
Publikováno v:
Proceedings of the National Academy of Sciences Jan 2019, 116 (5) 1532-1537
While the hydraulic fracturing technology, aka fracking (or fraccing, frac), has become highly developed and astonishingly successful, a consistent formulation of the associated fracture mechanics that would not conflict with some observations is sti
Externí odkaz:
http://arxiv.org/abs/1812.11023
Autor:
Schwarzer, Max, Rogan, Bryce, Ruan, Yadong, Song, Zhengming, Lee, Diana Y., Percus, Allon G., Chau, Viet T., Moore, Bryan A., Rougier, Esteban, Viswanathan, Hari S., Srinivasan, Gowri
Publikováno v:
Computational Materials Science 162, 322-332 (2019)
We propose a machine learning approach to address a key challenge in materials science: predicting how fractures propagate in brittle materials under stress, and how these materials ultimately fail. Our methods use deep learning and train on simulati
Externí odkaz:
http://arxiv.org/abs/1810.06118
Autor:
Valera, Manuel, Guo, Zhengyang, Kelly, Priscilla, Matz, Sean, Cantu, Vito Adrian, Percus, Allon G., Hyman, Jeffrey D., Srinivasan, Gowri, Viswanathan, Hari S.
Publikováno v:
Computational Geosciences 22, 695-710 (2018)
Structural and topological information play a key role in modeling flow and transport through fractured rock in the subsurface. Discrete fracture network (DFN) computational suites such as dfnWorks are designed to simulate flow and transport in such
Externí odkaz:
http://arxiv.org/abs/1705.09866