Calibration of advanced yield criteria using uniaxial and heterogeneous tensile test data

Andraž Maček (Author), Bojan Starman (Author), Nikolaj Mole (Author), Miroslav Halilovič (Author)

Abstract

Conventionally, plastic anisotropy is calibrated by using standard uniaxial tensile and biaxial test results. Alternatively, heterogeneous strain field specimens in combination with full-field measurements can be used for this purpose. As reported by the literature, such an approach reduces the number of required tests enormously, but it is challenging to obtain reliable results. This paper presents an alternative methodology, which represents a compromise between the conventional and heterogeneous strain field calibration technique. The idea of the method is to use simple tests, which can be conducted on the uniaxial testing machine, and to avoid the use of advanced measuring equipment. The procedure is accomplished by conducting standard tensile tests, which are simple and reliable, and by a novel heterogeneous strain field tensile test, to calibrate the biaxial stress state. Moreover, only two of the parameters required for full characterisation need to be inversely identified from the test response; the other parameters are directly determined from the uniaxial tensile test results. This way, a dimension of optimization space is reduced substantially, which increases the robustness and effectiveness of the optimization algorithm.

Keywords

plasticity;biaxial testing;numerical simulation;identification;full-field measurement;YLD2000-2d;

Data

Language:	English
Year of publishing:	2020
Typology:	1.01 - Original Scientific Article
Organization:	UL FS - Faculty of Mechanical Engineering
UDC:	621.713.3:004.942(045)
COBISS:	17170459
ISSN:	2075-4701
Views:	229
Downloads:	56
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	plastičnost;numerične simulacije;identifikacija;dvoosno preizkušanje;
Type (COBISS):	Article
Pages:	str. 1-17
Volume:	ǂiss. ǂ4
Issue:	ǂVol. ǂ10
Chronology:	2020
DOI:	10.3390/met10040542
ID:	14083846