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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
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" }