68 citations · 90 across the 6 of their papers we have counts for
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physics.flu-dyn2024★ 4 cited
A Priori Uncertainty Quantification of Reacting Turbulence Closure Models using Bayesian Neural Networks
Graham Pash, Malik Hassanaly, Shashank Yellapantula
While many physics-based closure model forms have been posited for the sub-filter scale (SFS) in large eddy simulation (LES), vast amounts of data available from direct numerical s…
physics.ao-ph2024★ 17 cited
Field measurements reveal insights into the impact of turbulent wind on loads experienced by parabolic trough solar collectors
Ulrike Egerer, Scott Dana, David Jager +3
To ensure efficient and reliable operation of a concentrating solar-thermal power (CSP) plant, its solar collector field needs to accurately focus sunlight. The optical efficiency…