arXiv (OAI Expanded)
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A derivative-free framework for capturing macroscopic behavior of incompressible turbulent flows
The derivative-free loss method (DFLM) is a mesh-free neural network approach for solving partial differential equations by simulating stochastic walkers rather than computing derivatives directly. Although DFLM has previously been applied to the Navier--Stokes equations, extending it to turbulent f
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