Aero-Engines AI - a machine-learning app for aircraft engine system-performance prediction
Aero-Engines AI is a Windows app that deploys machine-learning analytics to predict aircraft engine performance.
Graph Neural Networks for Airfoil Performance Prediction
We are investigating the use of Graph Convolutional Neural Networks to learn relationship between airfoil coordinates and predict the performance for aerodynamics analysis. Inputs…
Pre-trained microscopy image neural network encoders
Convolutional Neural Network encoders were trained on over 100,000 microscopy images of materials.
Surrogate Models for Efficient Multiscale Modeling of Composite Materials
A custom neural network architecture containing graph convolutional network (GCN) and long short-term memory (LSTM) layers was trained as a computationally efficient surrogate for…
Inverse Design of Materials
Discovering new materials is typically a mix of art and science, with timelines to create and robustly test a new material mix / manufacturing method ranging from ten to twenty ye…
MADI - Strategic Foresight and Knowledge Management infrastructure for ARMD/TACP/CAS
The CAS Discovery team is developing, testing and using digital infrastructure to meet the pace of expected deliverables in an automated, efficient, collaborative manner, includin…
Design Optimization of Turbomachinery Rotor Blades using Neural Network Surrogate Models
A sample is made of a design space using Latin hypercube sampling. The geometry for these samples is then generated and evaluated using simulation tools. The result is then used t…