Publication detail

A neural network ensemble for the identification of mechanical fracture parameters of fine-grained brittle matrix composites

LEHKÝ, D. LIPOWCZAN, M. ŠIMONOVÁ, H. KERŠNER, Z.

Original Title

A neural network ensemble for the identification of mechanical fracture parameters of fine-grained brittle matrix composites

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

The paper describes a method for the identification of selected mechanical parameters of fine-grained brittle matrix composites, and its software implementation. The artificial neural network-based inverse analysis method can be employed to obtain parameters from experimental data acquired during three-point bending tests on notched prism specimens. This capability is utilized and extended in order to conduct parameter identification on fine-grained brittle matrix composites.

Keywords

Inverse Analysis, Fine-grained Composites, Fracture Parameters, Artificial Neural Networks

Authors

LEHKÝ, D.; LIPOWCZAN, M.; ŠIMONOVÁ, H.; KERŠNER, Z.

Released

1. 1. 2019

Pages from

1

Pages to

9

Pages count

9

BibTex

@inproceedings{BUT162690,
  author="David {Lehký} and Martin {Lipowczan} and Hana {Šimonová} and Zbyněk {Keršner}",
  title="A neural network ensemble for the identification of mechanical fracture parameters of fine-grained brittle matrix composites",
  year="2019",
  pages="1--9",
  doi="10.21012/FC10.234717"
}