Publication result detail

Determination of concrete fracture parameters using inverse analysis: Influence of the tensile softening model

ŠOMODÍKOVÁ, M.; LIPOWCZAN, M.; LEHKÝ, D.

Original Title

Determination of concrete fracture parameters using inverse analysis: Influence of the tensile softening model

English Title

Determination of concrete fracture parameters using inverse analysis: Influence of the tensile softening model

Type

Paper in proceedings (conference paper)

Original Abstract

The paper is focused on the identification of selected mechanical fracture parameters of concrete. An inverse analysis based on an artificial neural network is used for this purpose. In this approach the laboratory measurements are matched with the results gained by reproducing the same test numerically. The identification of mechanical fracture parameters is carried out from the records of three-point bending and wedge-splitting tests performed using three specimen sizes. The ATENA software is employed for the numerical simulation of the fracture tests. The material model with the exponential and bilinear tensile softening law is selected to govern the gradual evolution of localized damage. The obtained parameters are finally analyzed and discussed in terms of their dependence on the size of the initial uncracked ligament. The results show that both tensile softening models are able to capture the behavior of the specimens in the softening phase reasonably well. The tensile softening model does not affect the modulus of elasticity values but has a slight effect on the tensile strength and fracture energy. For the latter two parameters, both models detected the influence of specimen size on their values.

English abstract

The paper is focused on the identification of selected mechanical fracture parameters of concrete. An inverse analysis based on an artificial neural network is used for this purpose. In this approach the laboratory measurements are matched with the results gained by reproducing the same test numerically. The identification of mechanical fracture parameters is carried out from the records of three-point bending and wedge-splitting tests performed using three specimen sizes. The ATENA software is employed for the numerical simulation of the fracture tests. The material model with the exponential and bilinear tensile softening law is selected to govern the gradual evolution of localized damage. The obtained parameters are finally analyzed and discussed in terms of their dependence on the size of the initial uncracked ligament. The results show that both tensile softening models are able to capture the behavior of the specimens in the softening phase reasonably well. The tensile softening model does not affect the modulus of elasticity values but has a slight effect on the tensile strength and fracture energy. For the latter two parameters, both models detected the influence of specimen size on their values.

Keywords

Inverse analysis, mechanical fracture parameters, numerical simulation, size effect, exponential and tensile softening model

Key words in English

Inverse analysis, mechanical fracture parameters, numerical simulation, size effect, exponential and tensile softening model

Authors

ŠOMODÍKOVÁ, M.; LIPOWCZAN, M.; LEHKÝ, D.

RIV year

2024

Released

13.01.2023

Publisher

Elsevier

Book

Procedia Structural Integrity

Edition

Materials Structure & Micromechanicas of Fracture

ISBN

2452-3216

Periodical

Procedia Structural Integrity

Volume

43

Number

1

State

Kingdom of the Netherlands

Pages from

258

Pages to

263

Pages count

6

URL

Full text in the Digital Library

BibTex

@inproceedings{BUT181355,
  author="Martina {Sadílková Šomodíková} and Martin {Lipowczan} and David {Lehký}",
  title="Determination of concrete fracture parameters using inverse analysis: Influence of the tensile softening model",
  booktitle="Procedia Structural Integrity",
  year="2023",
  series="Materials Structure & Micromechanicas of Fracture",
  journal="Procedia Structural Integrity",
  volume="43",
  number="1",
  pages="258--263",
  publisher="Elsevier",
  doi="10.1016/j.prostr.2022.12.268",
  url="https://www.sciencedirect.com/science/article/pii/S2452321622008319"
}

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