High-fidelity temporal prediction model for vehicle wake based on deep learning and bidirectional information fusion
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Published online on February 28, 2026
Abstract
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
Vehicle wake has complex, nonlinear, and multi-timescale characteristics, consuming expensive time and costs in simulations or experiments. A deep learning-based flow field time series prediction model is a relatively good solution. However, current ...
Vehicle wake has complex, nonlinear, and multi-timescale characteristics, consuming expensive time and costs in simulations or experiments. A deep learning-based flow field time series prediction model is a relatively good solution. However, current ...