A hypernetwork conditions a conservative-form CNN to predict WENO5 weights from mesh and initial-condition metadata, preserving conservation and generalizing across resolutions for 1D hyperbolic conservation laws.
Journal of computational physics , volume=
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DNS study of supersonic shear layers identifies self-similar scalings and derives a closed-form entrainment ratio that rises with Mc and λ.
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Hypernetwork-Conditioned WENO5 Conservative-Form CNNs for One-Dimensional Conservation Laws
A hypernetwork conditions a conservative-form CNN to predict WENO5 weights from mesh and initial-condition metadata, preserving conservation and generalizing across resolutions for 1D hyperbolic conservation laws.
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Numerical Study of Compressibility and Velocity Parameter Effects on Spatially Evolving Supersonic Turbulent Shear Layers
DNS study of supersonic shear layers identifies self-similar scalings and derives a closed-form entrainment ratio that rises with Mc and λ.