SO-RaNN applies randomized neural networks to linearized PNP and PNP-NS subproblems with value-level positivity cut-offs, time-interpolated mass scaling, SAV post-processing, and divergence-free velocity construction.
Kajiwara, Maximal Lp Lq regularity for the Stokes equations with various boundary conditions in the half space, arXiv: 2201.05306
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Structure-Oriented Randomized Neural Networks for Poisson-Nernst-Planck and Poisson-Nernst-Planck-Navier-Stokes Systems
SO-RaNN applies randomized neural networks to linearized PNP and PNP-NS subproblems with value-level positivity cut-offs, time-interpolated mass scaling, SAV post-processing, and divergence-free velocity construction.