Fatigue life modeling and prediction methods for composite materials and structures—Past, present, and future prospects

Anastasios Vassilopoulos
2019
Book chapter

Abstract

This chapter aims to provide an overview of the fatigue life modeling and prediction methods for composite materials and structures, recalling methods used in the past, discovering the present status, and attempting to foresee future trends.

Official source

https://infoscience.epfl.ch/record/276289?ln=en

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Fatigue life modeling and prediction methods for composite materials and structures—Past, present, and future prospects

Predicting protein interactions using geometric deep learning on protein surfaces

A generic diffusion-based approach for 3D human pose prediction in the wild

Meta Transfer Learning for Early Success Prediction in MOOCs

Predicting protein interactions using geometric deep learning on protein surfaces

A generic diffusion-based approach for 3D human pose prediction in the wild

Meta Transfer Learning for Early Success Prediction in MOOCs