A flow-matching generative model trained on minimal conditional flow units approximates the invariant phase-space distribution of turbulent channel flow at Re_tau=180, enabling synthetic turbulence generation and flow reconstruction.
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A machine-learned probability distribution in the phase space of turbulent channel flow for synthetic turbulence and flow reconstruction
A flow-matching generative model trained on minimal conditional flow units approximates the invariant phase-space distribution of turbulent channel flow at Re_tau=180, enabling synthetic turbulence generation and flow reconstruction.