Bioinspired hierarchical composite design using machine learning: simulation, additive manufacturing, and experiment

Abstract

A new approach to design hierarchical materials using convolutional neural networks is proposed and validated through additive manufacturing and testing.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 01, 2018
Source ID
10.1039/c8mh00653a

Entities

People

  • Chun-Teh Chen
  • Deon J. Richmond
  • Grace X Gu
  • Markus J. Buehler

Organizations

  • Air Force Office of Scientific Research
  • Massachusetts Institute of Technology
  • Office of Naval Research
  • United States Army
  • University of Cambridge

Tags

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Reinforced Composite Materials
  • Software Engineering

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Biotechnology