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Fast Buffet-Onset Prediction and Optimization Method Based on Pretrained Flowfield Prediction Model
Mathematics-Informed Neural Network for Acoustic Scattering by Parallel Plates
Data-Driven Nonintrusive Model-Order Reduction for Aerodynamic Design Optimization
Mesh-Agnostic Decoders for Supercritical Airfoil Prediction and Inverse Design
Development of a Language Model for Named-Entity-Recognition in Aerospace Requirements
Automated Spoken-to-Coded Pilot Weather Reports in General Aviation
Domain Decomposition Strategy for Combining Nonlinear and Linear Reduced-Order Models
Framework for Offline Data-Driven Aircraft Fault Diagnosis
Generative Adversarial Networks for Inverse Design of Two-Dimensional Spinodoid Metamaterials
Neural Network Classification-Regression Method Applied to Approach Speed Control Strategy
Machine Learning Aided Low-Order Predictions of Fan Stage Broadband Interaction Noise
Assessing the Impact of Metrics on the Choice of Prognostic Methodologies
Physics-Informed Machine Learning Using Low-Fidelity Flowfields for Inverse Airfoil Shape Design
Introduction to the Virtual Collection on Machine Learning in Aerospace
Scalable Projection-Based Reduced-Order Models for Large Multiscale Fluid Systems
Data-Driven Approach Toward Airspace Design for Regional Air Mobility Operations in Korea
Deep Learning Closure of the Navier–Stokes Equations for Transition-Continuum Flows