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• W2127178657 abstract "The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data from experiments, field measurements, and large-scale simulations at multiple spatiotemporal scales. Machine learning (ML) offers a wealth of techniques to extract ...Read More" @default.
• W2127178657 created "2016-06-24" @default.
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• W2127178657 date "1991-01-01" @default.
• W2127178657 modified "2023-09-25" @default.
• W2127178657 title "Numerical Simulation of Transition in Wall-Bounded Shear Flows" @default.
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• W2127178657 doi "https://doi.org/10.1146/annurev.fl.23.010191.002431" @default.
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