Deadline Date: 31 July 2026
The design and development of next-generation aerospace systems require a seamless integration of advanced numerical methods, high-fidelity simulations, and artificial intelligence (AI)-driven approaches. High-speed aerospace vehicles, including hypersonic aircraft, reusable launch systems, and space exploration platforms, operate under extreme conditions where complex interactions among aerodynamics, propulsion, structures, and thermal environments must be accurately captured. Traditional modeling techniques, while powerful, often face limitations in handling the coupled physics, large-scale computations, and real-time predictive capabilities demanded by these applications.
This special issue aims to provide a platform for disseminating pioneering research that advances the computational frontiers of aerospace science and engineering. Topics include high-speed aerodynamics and flow control, modeling of propulsion and combustion systems, multiphysics and multiscale simulations, aero-thermo-structural coupling, and re-entry aerothermodynamics. Contributions that leverage AI, machine learning, and data-driven methodologies such as surrogate modeling, reduced-order models, physics-informed neural networks, and digital twins are particularly encouraged, as they hold the potential to accelerate design cycles, improve predictive accuracy, and enable optimization at unprecedented scales.
Editorial board
