Zobrazeno 1 - 10
of 233
pro vyhledávání: '"Pain, Christopher C."'
Autor:
Silva, Vinicius L S, Regnier, Geraldine, Salinas, Pablo, Heaney, Claire E, Jackson, Matthew D, Pain, Christopher C
Reactive transport in porous media plays a pivotal role in subsurface reservoir processes, influencing fluid properties and geochemical characteristics. However, coupling fluid flow and transport with geochemical reactions is computationally intensiv
Externí odkaz:
http://arxiv.org/abs/2405.14548
Recently, there has been a huge effort focused on developing highly efficient open source libraries to perform Artificial Intelligence (AI) related computations on different computer architectures (for example, CPUs, GPUs and new AI processors). This
Externí odkaz:
http://arxiv.org/abs/2402.17913
Autor:
Chen, Boyang, Heaney, Claire E., Gomes, Jefferson L. M. A., Matar, Omar K., Pain, Christopher C.
This paper solves the discretised multiphase flow equations using tools and methods from machine-learning libraries. The idea comes from the observation that convolutional layers can be used to express a discretisation as a neural network whose weigh
Externí odkaz:
http://arxiv.org/abs/2401.06755
Autor:
Cheng, Sibo, Chen, Jianhua, Anastasiou, Charitos, Angeli, Panagiota, Matar, Omar K., Guo, Yi-Ke, Pain, Christopher C., Arcucci, Rossella
Reduced-order modelling and low-dimensional surrogate models generated using machine learning algorithms have been widely applied in high-dimensional dynamical systems to improve the algorithmic efficiency. In this paper, we develop a system which co
Externí odkaz:
http://arxiv.org/abs/2204.03497
Autor:
Basha, Nausheen, Arcucci, Rossella, Angeli, Panagiota, Anastasiou, Charitos, Abadie, Thomas, Casas, César Quilodrán, Chen, Jianhua, Cheng, Sibo, Chagot, Loïc, Galvanin, Federico, Heaney, Claire E., Hossein, Fria, Hu, Jinwei, Kovalchuk, Nina, Kalli, Maria, Kahouadji, Lyes, Kerhouant, Morgan, Lavino, Alessio, Liang, Fuyue, Nathanael, Konstantia, Magri, Luca, Lettieri, Paola, Materazzi, Massimiliano, Erigo, Matteo, Pico, Paula, Pain, Christopher C., Shams, Mosayeb, Simmons, Mark, Traverso, Tullio, Valdes, Juan Pablo, Wolffs, Zef, Zhu, Kewei, Zhuang, Yilin, Matar, Omar K
Publikováno v:
In International Journal of Multiphase Flow September 2024 179
Publikováno v:
In Computer Methods in Applied Mechanics and Engineering 1 September 2024 429
Autor:
Heaney, Claire E., Wolffs, Zef, Tómasson, Jón Atli, Kahouadji, Lyes, Salinas, Pablo, Nicolle, André, Matar, Omar K., Navon, Ionel M., Srinil, Narakorn, Pain, Christopher C.
The modelling of multiphase flow in a pipe presents a significant challenge for high-resolution computational fluid dynamics (CFD) models due to the high aspect ratio (length over diameter) of the domain. In subsea applications, the pipe length can b
Externí odkaz:
http://arxiv.org/abs/2202.06170
Publikováno v:
In Journal of Computational Science December 2024 83
Autor:
Naderi, Sadjad, Chen, Boyang, Yang, Tongan, Xiang, Jiansheng, Heaney, Claire E., Latham, John-Paul, Wang, Yanghua, Pain, Christopher C.
Publikováno v:
In Powder Technology 1 December 2024 448
Publikováno v:
In Neural Networks July 2024 175