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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
English Title
Type
Paper in proceedings (conference paper)
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.
English abstract
Keywords
Sensitivity, optimisation, identification, nonlinear material model of concrete, Python.
Key words in English
Authors
RIV year
2018
Released
22.02.2017
Book
Modern Building Materials, Structures and Techniques
ISBN
1877-7058
Periodical
Procedia Engineering
Volume
2017
Number
172
State
United Kingdom of Great Britain and Northern Ireland
Pages from
1
Pages to
8
Pages count
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" }