An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks

Published 2020 View Full Article

  1. Home
  2. Publications
  3. Publication Search
  4. Publication Details
Title
An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks
Authors
Keywords
Multiscale modelling, Progressive damage, Surrogate model, Artificial neural network
Journal
COMPOSITES PART B-ENGINEERING
Volume 194, Issue -, Pages 108014
Publisher
Elsevier BV
Online
2020-04-12
DOI
10.1016/j.compositesb.2020.108014

Ask authors/readers for more resources

Protocol

Community support

Reagent

Community support

Reprint

Contact the author

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started
Webinars Posters Questions Hubs Funding Journals Articles Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.