Machine learning for material characterization with an application for predicting mechanical properties-Reference-Cited by-同舟云学术

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Machine learning for material characterization with an application for predicting mechanical properties

Published:2021-03 Issue:1 Volume:44 Page:
ISSN:0936-7195
Container-title:GAMM-Mitteilungen
language:en
Short-container-title:GAMM‐Mitteilungen

Author:

Stoll Anke¹,Benner Peter²

Affiliation:

1. Data‐Mining and Machine Learning Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany

2. Computational Methods in Systems and Control Theory The Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany

Publisher

Wiley

Subject

Applied Mathematics,General Physics and Astronomy,General Materials Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/gamm.202100003

Reference181 articles.

1. Parameter identification of a mechanical ductile damage using Artificial Neural Networks in sheet metal forming

2. Modeling and simulation of low-cycle fatigue life of steel reinforcing bars using artificial neural network

3. Determination of deformation and failure properties of ductile materials by means of the small punch test and neural networks

4. Identification of ductile damage and fracture parameters from the small punch test using neural networks

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