Speaker
Brian Wood
(Oregon State University)
Description
The upscaling of flows with nonlinear rheology is challenging because conventional homogenization methods usually rely on linearity to obtain closed form solutions. Here, the problem of upscaling power-law fluid flows in tree-like networks is examined. An analytical scheme is presented for direct microscale solutions to the problem. Homogenization of the problem is explored through the combination of both (1) a unique pressure-gradient decomposition that allows for a perturbative expansion to be developed, and (2) the use of machine learning on the network to effect closure. Some concrete results of the solution are presented.
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Primary author
Brian Wood
(Oregon State University)
