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ZipGAN

Project information

ZipGAN is a deep learning framework for compressing and decompressing 3D Direct Numerical Simulation (DNS) datasets of turbulent flows. It uses a Super-Resolution GAN to reconstruct full-resolution DNS fields from compressed (filtered + downsampled) representations, achieving compression ratios of up to 512x while preserving fine-scale turbulence features.

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Academic Free License v3.0

Created on

January 07, 2025

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