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Performance and accuracy assessments of an incompressible fluid solver coupled with a deep convolutional neural network
2022
Data-Centric Engineering
The resolution of the Poisson equation is usually one of the most computationally intensive steps for incompressible fluid solvers. Lately, DeepLearning, and especially convolutional neural networks (CNNs), has been introduced to solve this equation, leading to significant inference time reduction at the cost of a lack of guarantee on the accuracy of the solution.This drawback might lead to inaccuracies, potentially unstable simulations and prevent performing fair assessments of the CNN speedup
doi:10.1017/dce.2022.2
fatcat:fudeg4gp75gazoxamhu52wm4ui