2 papers
physics.flu-dyn2026
Wind-Informed Rapid Flight-Planning in Complex Urban Topologies via Machine Learning and Experimental Validation
Peter I. Renn, Alejandro A. Stefan-Zavala, Julian Humml +8
Advanced air mobility operations hold the potential to enhance and expand regional transportation of both people and goods in populated areas. However, hazardous flight conditions…
physics.flu-dyn2026
Data-driven surrogate models for forecasting experimentally measured fluid flows
Peter I. Renn, Emily H. Palmer, Cong Wang +1
Data-driven modeling shows significant promise for faster-than-real-time forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must conte…