Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Phong C"'
Autor:
Phong C. H. Nguyen, Nikolaos N. Vlassis, Bahador Bahmani, WaiChing Sun, H. S. Udaykumar, Stephen S. Baek
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
Abstract For material modeling and discovery, synthetic microstructures play a critical role as digital twins. They provide stochastic samples upon which direct numerical simulations can be conducted to populate material databases. A large ensemble o
Externí odkaz:
https://doaj.org/article/87b2d0cb56a94e30ac409f7fd95834df
Many applications in computational and experimental fluid mechanics require effective methods for reconstructing the flow fields from limited sensor data. However, this task remains a significant challenge because the measurement operator, which prov
Externí odkaz:
http://arxiv.org/abs/2411.13815
Autor:
Xinlun Cheng, Sheng Zhang, Phong C. H. Nguyen, Shahab Azarfar, Gia-Wei Chern, Stephen S. Baek
Publikováno v:
Physical Review Research, Vol 5, Iss 3, p 033188 (2023)
Complex spin textures in itinerant electron magnets hold promises for next-generation memory and information technology. The long-ranged and often frustrated electron-mediated spin interactions in these materials give rise to intriguing localized spi
Externí odkaz:
https://doaj.org/article/62b88033ec8341b982a22ad2b1310fbe
Autor:
Nguyen, Phong C. H., Cheng, Xinlun, Azarfar, Shahab, Seshadri, Pradeep, Nguyen, Yen T., Kim, Munho, Choi, Sanghun, Udaykumar, H. S., Baek, Stephen
Modeling unsteady, fast transient, and advection-dominated physics problems is a pressing challenge for physics-aware deep learning (PADL). The physics of complex systems is governed by large systems of partial differential equations (PDEs) and ancil
Externí odkaz:
http://arxiv.org/abs/2402.12503
Autor:
Cheng, Xinlun, Zhang, Sheng, Nguyen, Phong C. H., Azarfar, Shahab, Chern, Gia-Wei, Baek, Stephen S.
Publikováno v:
Phys. Rev. Research 5, 033188 (2023)
Complex spin textures in itinerant electron magnets hold promises for next-generation memory and information technology. The long-ranged and often frustrated electron-mediated spin interactions in these materials give rise to intriguing localized spi
Externí odkaz:
http://arxiv.org/abs/2306.11833
Many mechanical engineering applications call for multiscale computational modeling and simulation. However, solving for complex multiscale systems remains computationally onerous due to the high dimensionality of the solution space. Recently, machin
Externí odkaz:
http://arxiv.org/abs/2303.12261
Artificial intelligence (AI) is rapidly emerging as an enabling tool for solving various complex materials design problems. This paper aims to review recent advances in AI-driven materials-by-design and their applications to energetic materials (EM).
Externí odkaz:
http://arxiv.org/abs/2211.08179
Autor:
Nguyen, Phong C. H., Nguyen, Yen-Thi, Seshadri, Pradeep K., Choi, Joseph B., Udaykumar, H. S., Baek, Stephen
Publikováno v:
Pyrotech. 2023, e202200268
Predictive simulations of the shock-to-detonation transition (SDT) in heterogeneous energetic materials (EM) are vital to the design and control of their energy release and sensitivity. Due to the complexity of the thermo-mechanics of EM during the S
Externí odkaz:
http://arxiv.org/abs/2211.04561
Autor:
Nguyen, Phong C. H., Nguyen, Yen-Thi, Choi, Joseph B., Seshadri, Pradeep K., Udaykumar, H. S., Baek, Stephen
Publikováno v:
Sci. Adv. 2023, eadd6868
The thermo-mechanical response of shock-initiated energetic materials (EM) is highly influenced by their microstructures, presenting an opportunity to engineer EM microstructure in a "materials-by-design" framework. However, the current design practi
Externí odkaz:
http://arxiv.org/abs/2204.07234
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.