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Super-resolution reconstruction of simulated stochastic wind fields using ensemble conditional diffusion model
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AI
DOI：10.1016/j.jweia.2025.106249.png)
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Abstract
En 中文
• Ensemble conditional diffusion model is utilized to conduct super-resolution reconstruction of stochastic wind fields. • A general framework for super-resolution reconstruction using the proposed DDPM is established and verified. • Transformer and custom-designed CNN modules are utilized to extract features from wind fields as a novel input condition. • The NUFFT-aided WSRM is utilized to generate 2-D turbulent wind field. • The ensemble DDPM outperforms the classic model in spatiotemporal wind field SR reconstruction.
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