Acquirement of True Stress-strain Curve Using True Fracture Strain Obtained by Tensile Test and FE Analysis

2009 ◽  
Vol 33 (10) ◽  
pp. 1054-1064 ◽  
Author(s):  
Kyoung-Yoon Lee ◽  
Tae-Hyung Kim ◽  
Hyung-Yil Lee
2020 ◽  
Vol 55 (3-4) ◽  
pp. 99-108 ◽  
Author(s):  
Yunlu Zhang ◽  
Sreekar Karnati ◽  
Tan Pan ◽  
Frank Liou

The determination of constitutive relation from the miniature tensile test is of high interest in multiple areas. Here, a convenient experimental method is proposed to determine the true stress–strain curve from the miniature tensile test. The instantaneous cross-sectional area is estimated by only one camera in aid of digital image correlation technique. This method was applied on commercial pure titanium and aluminum 6061 alloys, and the results indicate that the extracted true stress–strain curves are not scale-dependent. The derived mechanical properties from miniature specimens match well with the results of standard specimens. The correctness of the true stress–strain curve was evaluated by the finite element analysis method. The results suggest that the derived true stress–strain curve is capable to represent the constitutive behavior of the tested materials.


2021 ◽  
Author(s):  
Ming Song ◽  
Xuyang Li ◽  
Wenchun Jiang ◽  
Jiru Zhong ◽  
Kaishu Guan

Abstract Evaluating the strength properties of materials of an in-service pipeline without shutting down transportation has been always a challenge. A novel and non-destructive method for determining the true stress-strain curve of pipeline steel based on backpropagation artificial neural network and small punch test is proposed in this study. The elastoplastic mechanical properties of the pipeline steels could be obtained by this method. The load-displacement curves of 2261 groups of different hypothetical materials were obtained by the finite element model of small punch test within Gurson-Tvergaard-Needleman (GTN) damage parameters and used to train the neural network. The relationship between the load-displacement curve of small punch test and the true stress-strain curve of the conventional uniaxial tensile test was established based on the trained neural network. The accuracy and wide applicability of the trained neural network were verified by the experimental data of four types of materials obtained by small punch test and standard tensile test, respectively. The established relationship can be used to predict the true stress-strain curve of the pipeline steels to determine the elastoplastic mechanical properties only by the load-displacement curve of the small punch test without performing the conventional tensile test.


Author(s):  
C. F. Elam ◽  
Henry Cort Harold Carpenter

The following experiments were carried out with two principal objects in view: (1) to investigate the deformation of those metals, particularly iron and steel, in which the stress-strain curve does not immediately rise at the onset of plastic distortion; (2) to determine the effect of rate of deformation on the yield and subsequent stress-strain curve. It is impossible to give an adequate summary of the literature which deals with this subject, but a bibliography is included in an appendix and some of the most important results are referred to briefly below.


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