Zobrazeno 1 - 10
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pro vyhledávání: '"Grout, Ray W."'
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
Autor:
Morzfeld, Matthias, Day, Marcus S., Grout, Ray W., Pau, George Shu Heng, Finsterle, Stefan A., Bell, John B.
In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov Chain Monte Carlo (MCMC) is often used for the numerical solution of such proble
Externí odkaz:
http://arxiv.org/abs/1608.01958
Publikováno v:
In Fuel 1 April 2020 265
Autor:
Grout, Ray W. S.
Conditional source-term estimation with laminar flamelet decomposition has been utilized to model the mean chemical source term in a predictive RANS simulation of two different problems. With this model, integral equations relating the unconditional
Externí odkaz:
http://hdl.handle.net/2429/15580
Publikováno v:
In Combustion and Flame October 2015 162(10):3569-3579
Akademický článek
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Autor:
Henry de Frahan, Marc T, Rood, Jon S, Day, Marc S, Sitaraman, Hariswaran, Yellapantula, Shashank, Perry, Bruce A, Grout, Ray W, Almgren, Ann, Zhang, Weiqun, Bell, John B, Chen, Jacqueline H
Publikováno v:
International Journal of High Performance Computing Applications; Mar2023, Vol. 37 Issue 2, p115-131, 17p
Publikováno v:
International Journal of Engine Research (Sage Publications, Ltd.); Sep2022, Vol. 23 Issue 9, p1503-1521, 19p