Publication detail

Improved Sensitivity Analysis in the Inverse Identification of the Parameters of a Nonlinear Material Model

HOKEŠ, F. KRÁL, P. KRŇÁVEK, O. HUŠEK, M.

Original Title

Improved Sensitivity Analysis in the Inverse Identification of the Parameters of a Nonlinear Material Model

Type

conference paper

Language

English

Original Abstract

During the inverse identification of the parameters of a nonlinear material model via an optimization algorithm, it is advantageous to utilize sensitivity analysis as a pre-processing tool to decrease the dimensions of the design vector by removing insignificant parameters. As regards the optimization and sensitivity analysis, a crucial aspect consists in the choice of the objective function. It is possible to derive special forms of objective functions for better understanding of the functionality of the given complex material model. The present article discusses three types of Python scripts that facilitate the calculation of different objective functions from the numerically and experimentally obtained load-displacement curves.

Keywords

Sensitivity, optimisation, identification, nonlinear material model of concrete, Python.

Authors

HOKEŠ, F.; KRÁL, P.; KRŇÁVEK, O.; HUŠEK, M.

Released

22. 2. 2017

ISBN

1877-7058

Periodical

Procedia Engineering

Year of study

2017

Number

172

State

Kingdom of the Netherlands

Pages from

1

Pages to

8

Pages count

8

BibTex

@inproceedings{BUT133260,
  author="Filip {Hokeš} and Petr {Král} and Ondřej {Krňávek} and Martin {Hušek}",
  title="Improved Sensitivity Analysis in the Inverse Identification of the Parameters of a Nonlinear Material Model",
  booktitle="Modern Building Materials, Structures and Techniques",
  year="2017",
  journal="Procedia Engineering",
  volume="2017",
  number="172",
  pages="1--8",
  doi="10.1016/j.proeng.2017.02.039",
  issn="1877-7058"
}