Zobrazeno 1 - 10
of 1 619
pro vyhledávání: '"T, Henry"'
Autor:
Hassanaly, Malik, Wimer, Nicholas T., Felden, Anne, Esclapez, Lucas, Ream, Julia, de Frahan, Marc T. Henry, Rood, Jon, Day, Marc
The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of chemical mechanisms for implementation in computational reacting flow solvers. However, for many applications, stiffness remains, and the resu
Externí odkaz:
http://arxiv.org/abs/2405.05974
Autor:
Egan, Hilary, Griffin, Kevin Patrick, de Frahan, Marc T. Henry, Mueller, Juliane, Vaidhynatha, Deepthi, Wald, Dylan, Chintala, Rohit, Doronina, Olga A., King, Ryan, Sanyal, Jibonananda, Day, Marc
Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptiv
Externí odkaz:
http://arxiv.org/abs/2404.00053
Autor:
Bauman, Paul T., Budiardja, Reuben D., Bykov, Dmytro, Chalmers, Noel, Chen, Jacqueline, Curtis, Nicholas, Day, Marc, Eisenbach, Markus, Esclapez, Lucas, Fanfarillo, Alessandro, Freitag, William, Frontiere, Nicholas, Georgiadou, Antigoni, Glenski, Joseph, Gottiparthi, Kalyana, de Frahan, Marc T. Henry, Jansen, Gustav R., Joubert, Wayne, Lietz, Justin G., Kurzak, Jakub, Malaya, Nicholas, Messer, Bronson, McDougall, Damon, Mullowney, Paul, Nichols, Stephen, Norman, Matthew, Papatheodore, Thomas, Rood, Jon, Roth, Philip C., Sreepathi, Sarat, White III, James, Wolfe, Noah
The advent of exascale computing invites an assessment of existing best practices for developing application readiness on the world's largest supercomputers. This work details observations from the last four years in preparing scientific applications
Externí odkaz:
http://arxiv.org/abs/2310.01586
Autor:
Sanchez, Isabel Barrio, Almgren, Ann S., Bell, John B., de Frahan, Marc T. Henry, Zhang, Weiqun
State redistribution (SRD) is a recently developed technique for stabilizing cut cells that result from finite-volume embedded boundary methods. SRD has been successfully applied to a variety of compressible and incompressible flow problems. When use
Externí odkaz:
http://arxiv.org/abs/2309.06372
Autor:
Ashesh Sharma, Michael J. Brazell, Ganesh Vijayakumar, Shreyas Ananthan, Lawrence Cheung, Nathaniel deVelder, Marc T. Henry de Frahan, Neil Matula, Paul Mullowney, Jon Rood, Philip Sakievich, Ann Almgren, Paul S. Crozier, Michael Sprague
Publikováno v:
Wind Energy, Vol 27, Iss 3, Pp 225-257 (2024)
Abstract Predictive high‐fidelity modeling of wind turbines with computational fluid dynamics, wherein turbine geometry is resolved in an atmospheric boundary layer, is important to understanding complex flow accounting for design strategies and op
Externí odkaz:
https://doaj.org/article/9efba383e28048cfa451cf34769c8ec5
Autor:
Giuliani, Andrew, Almgren, Ann S., Bell, John B., Berger, Marsha J., de Frahan, Marc T. Henry, Rangarajan, Deepak
State redistribution is an algorithm that stabilizes cut cells for embedded boundary grid methods. This work extends the earlier algorithm in several important ways. First, state redistribution is extended to three spatial dimensions. Second, we disc
Externí odkaz:
http://arxiv.org/abs/2112.12360
Most deep learning models are based on deep neural networks with multiple layers between input and output. The parameters defining these layers are initialized using random values and are "learned" from data, typically using stochastic gradient desce
Externí odkaz:
http://arxiv.org/abs/1903.00091
One of the challenges encountered by computational simulations at exascale is the reliability of simulations in the face of hardware and software faults. These faults, expected to increase with the complexity of the computational systems, will lead t
Externí odkaz:
http://arxiv.org/abs/1901.11113
In this work, we use ML techniques to develop presumed PDF models for large eddy simulations of reacting flows. The joint sub-filter PDF of mixture fraction and progress variable is modeled using various ML algorithms and commonly used analytical mod
Externí odkaz:
http://arxiv.org/abs/1901.05557
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-11 (2022)
Abstract While radiomics analysis has been applied for localized cancer disease, its application to the metastatic setting involves a non-exhaustive lesion subsampling strategy which may sidestep the intrapatient tumoral heterogeneity, hindering the
Externí odkaz:
https://doaj.org/article/7d25c43f12014c8face44c057bded9ba