Publication detail

Surrogate models for the damage responses of a reinforced concrete beam under explosive charges utilizing coupled finite element-stochastic methods

NARIMAN, N. HUŠEK, M. RAMADAN, A.

Original Title

Surrogate models for the damage responses of a reinforced concrete beam under explosive charges utilizing coupled finite element-stochastic methods

Type

journal article in Web of Science

Language

English

Original Abstract

Numerical evaluation of experimental test in which reinforced concrete beam is subjected to TNT explosions is the subject of the paper. Prediction of damage responses is being conducted by utilizing both numerical analyses and stochastic experimental methods where ABAQUS and LS-DYNA are being used. Material parameters of concrete and reinforcement, together with the mass of the TNT charge are considered in sensitivity study which is further used for metamodel creation. The Box-Behnken experimental method is used to construct both the samples and the surrogate models for the prediction process by employing the least-squares method and MATLAB codes. The results demonstrate the high capability of the coupled finite element-stochastic methods to predict damages of the reinforced concrete beam. Results of the numerical simulations were verified by reference cases. Introduced coupled methods can be, therefore, considered a tool for not only structural response prediction but optimization as well.

Keywords

TNT; Box-Behnken method; Coefficient of regression; ABAQUS; LS-DYNA

Authors

NARIMAN, N.; HUŠEK, M.; RAMADAN, A.

Released

13. 1. 2022

Publisher

SPRINGER

Location

NEW YORK

ISBN

0177-0667

Periodical

ENGINEERING WITH COMPUTERS

Year of study

1

Number

1

State

Federal Republic of Germany

Pages from

1

Pages to

21

Pages count

21

URL

BibTex

@article{BUT177118,
  author="Nazim Abdul {Nariman} and Martin {Hušek} and Ayad Mohammad {Ramadan}",
  title="Surrogate models for the damage responses of a reinforced concrete beam under explosive charges utilizing coupled finite element-stochastic methods",
  journal="ENGINEERING WITH COMPUTERS",
  year="2022",
  volume="1",
  number="1",
  pages="1--21",
  doi="10.1007/s00366-021-01550-0",
  issn="0177-0667",
  url="https://link.springer.com/article/10.1007/s00366-021-01550-0"
}