NIROM

A non-intrusive reduced order model using deep learning for realistic wind data generation for small unmanned aerial systems in urban spaces
Realistic wind data are essential in developing, testing, and ensuring the safety of small unmanned aerial systems in operation. We present a non-intrusive reduced order modeling (NIROM) approach to replicate realistic wind data and predict wind fields.
Rohit Vuppala, Kursat Kara
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A non-intrusive reduced order model using deep learning for realistic wind data generation for small unmanned aerial systems in urban spaces