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Found 3 papers, 1 papers with code
Enhancing wind field resolution in complex terrain through a knowledge-driven machine learning approach
Atmospheric flows are governed by a broad variety of spatio-temporal scales, thus making real-time numerical modeling of such turbulent flows in complex terrain at high resolution computationally intractable.
Geometric Change Detection in Digital Twins using 3D Machine Learning
Both stand-alone and descriptive digital twins incorporate 3D geometric models, which are the physical representations of objects in the digital replica.
A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction
We put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improvements.
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