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What is Modeling Continuous Spatial Temporal Dynamics of Turbulent Flow about?
This paper presents a novel method for reconstructing high-resolution turbulent flow data from lower-resolution large eddy simulation (LES) data using a physics-guided neural network called Super-Resolution through Test-time Refinement (SR-TR). The SR-TR method incorporates a degradation-based refinement approach and a continuous spatial transition unit (CSTU) to effectively capture the complex spatio-temporal dynamics of turbulent flows while adhering to physical constraints. Results demonstrate the method
- Author
- zenaaleme21
- Language
- EN