Data-driven approach for the prediction of mechanical properties of carbon fiber reinforced composites
Abstract
Supervised machine learning models are trained on experimental data to predict the mechanical properties of composite materials. Results show that these techniques are reasonably accurate and generalizable.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2022
- Source ID
- 10.1039/d2ma00698g
Entities
People
- Charles Yang
- Grace X Gu
- Steven Zadourian
- Vade Shah
- Zilan Zhang
Organizations
- General Motors
- Office of Naval Research
- University of California