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Introduction to the Virtual Collection on Machine Learning in Aerospace
Book Review: Matrix Methods: Applied Linear Algebra and Sabermetrics
Scalable Projection-Based Reduced-Order Models for Large Multiscale Fluid Systems
Mathematics-Informed Neural Network for Acoustic Scattering by Parallel Plates
Fast Buffet-Onset Prediction and Optimization Method Based on Pretrained Flowfield Prediction Model
Data-Driven Nonintrusive Model-Order Reduction for Aerodynamic Design Optimization
Deep Learning Closure of the Navier–Stokes Equations for Transition-Continuum Flows
Data-Driven Approach Toward Airspace Design for Regional Air Mobility Operations in Korea
Optimization of Pin Fins Using Computational Fluid Dynamics and Machine Learning
Precision Mars Entry Navigation with Atmospheric Density Adaptation via Neural Networks
Deep Learning for Real-Time Satellite Pose Estimation on Tensor Processing Units
Data-Driven Model to Predict Aircraft Vibration Environment
Data-Driven Image Processing for Onboard Optical Navigation Around a Binary Asteroid
Verification of Image-Based Neural Network Controllers Using Generative Models
Machine Learning Approach for Identification of Microstructure–Process Linkages
Using Deep Learning to Predict Unstable Approaches for General Aviation Aircraft
Monocular Relative Pose Estimation Pipeline for Uncooperative Resident Space Objects
Enabling Limited Resource-Bounded Disjunction in Scheduling
Machine Learning Reinforced Crystal Plasticity Modeling Under Experimental Uncertainty
Power Setting Estimation of Departing Civil Jet Aircraft Based on Machine Learning
Development of a Language Model for Named-Entity-Recognition in Aerospace Requirements
Fatigue Damage Diagnostics–Prognostics Framework for Remaining Life Estimation in Adhesive Joints
Mesh-Agnostic Decoders for Supercritical Airfoil Prediction and Inverse Design
Machine Learning Gyro Calibration Method Based on Attitude Estimation
Efficient Model Updating Method for System Identification Using a Convolutional Neural Network
Learning Physics-Based Reduced-Order Models for a Single-Injector Combustion Process
Noise-Suppressed Temperature Measurement Based on Machine Learning in a Scramjet Combustor
Automated Spoken-to-Coded Pilot Weather Reports in General Aviation
Database Development and Component Design with Two-Dimensional Trusslike Microstructures
Natural-Language-Processing-Enabled Quantitative Risk Analysis of Aerial Wildfire Operations
Decision Tree– and Random Forest–Based Novel Unsteady Aerodynamics Modeling Using Flight Data
Performance Evaluation of Damaged Blades Using Numerical Simulation and Machine Learning
Filtered Integral Formulation of the Sparse Model Identification Problem
Defect Diagnosis in Solid Rocket Motors Using Sensors and Deep Learning Networks
Detecting Under-Resolved Flow Physics Using Supervised Machine Learning
Basic Research Perspective on Quantum Information Science for the Aerospace Community
Wave Detection and Tracking Within a Rotating Detonation Engine Through Object Detection
Real-Time Prediction of Probabilistic Crack Growth with a Helicopter Component Digital Twin
Extraction of Pendulum Model Parameters from Steady-State Slosh Data in Diaphragm Tanks
Common Proper Orthogonal Decomposition-Based Spatiotemporal Emulator for Design Exploration
Domain Decomposition Strategy for Combining Nonlinear and Linear Reduced-Order Models
Sensor Fault Detection in Smart Extraterrestrial Habitats Using Unsupervised Learning
Adversarial Learning Improves Vision-Based Perception from Drones with Imbalanced Datasets
Data-Driven Modeling for Transonic Aeroelastic Analysis