Study on the tension and compression stress-strain relationship of Phyllostachys Edulis bamboo parallel to the grain

2022 ◽  
Vol 177 ◽  
pp. 114548
Author(s):  
Xuhong Zhou ◽  
Pengcheng Liu ◽  
Qishi Zhou ◽  
Ping Xiang ◽  
Hai Zhang ◽  
...  
2003 ◽  
Vol 18 (9) ◽  
pp. 2068-2078 ◽  
Author(s):  
A. DiCarlo ◽  
H. T. Y. Yang ◽  
S. Chandrasekar

A method for determining the stress–strain relationship of a material from hardness values H obtained from cone indentation tests with various apical angles is presented. The materials studied were assumed to exhibit power-law hardening. As a result, the properties of importance are the Young's modulus E, yield strength Y, and the work-hardening exponent n. Previous work [W.C. Oliver and G.M. Pharr, J. Mater. Res. 7, 1564 (1992)] showed that E can be determined from initial force–displacement data collected while unloading the indenter from the material. Consequently, the properties that need to be determined are Y and n. Dimensional analysis was used to generalize H/E so that it was a function of Y/E and n [Y-T. Cheng and C-M. Cheng, J. Appl. Phys. 84, 1284 (1999); Philos. Mag. Lett. 77, 39 (1998)]. A parametric study of Y/E and n was conducted using the finite element method to model material behavior. Regression analysis was used to correlate the H/E findings from the simulations to Y/E and n. With the a priori knowledge of E, this correlation was used to estimate Y and n.


2004 ◽  
Vol 274-276 ◽  
pp. 241-246 ◽  
Author(s):  
Bo Han ◽  
Hong Jian Liao ◽  
Wuchuan Pu ◽  
Zheng Hua Xiao

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hongbo Zhao ◽  
Zenghui Huang ◽  
Zhengsheng Zou

Stress-strain relationship of geomaterials is important to numerical analysis in geotechnical engineering. It is difficult to be represented by conventional constitutive model accurately. Artificial neural network (ANN) has been proposed as a more effective approach to represent this complex and nonlinear relationship, but ANN itself still has some limitations that restrict the applicability of the method. In this paper, an alternative method, support vector machine (SVM), is proposed to simulate this type of complex constitutive relationship. The SVM model can overcome the limitations of ANN model while still processing the advantages over the traditional model. The application examples show that it is an effective and accurate modeling approach for stress-strain relationship representation for geomaterials.


Author(s):  
K. J. Thompson ◽  
R. Park

The stress-strain relationship of Grade 275 steel reinforcing bar under cyclic (reversed) loading is examined using experimental results obtained previously from eleven test specimens to which a variety of axial loading cycles has been applied. A Ramberg-Osgood function is fitted to the experimental stress-strain curves to follow the cyclic stress-strain behaviour after the first load run in the plastic range. The empirical constants in the function are determined by regression analysis and are found to depend mainly on the plastic strain imposed
in the previous loading run. The monotonic stress-strain curve for the steel, with origin of strains suitably adjusted, is assumed to be the envelope curve giving the upper limit of stress. The resulting Ramberg-Osgood expression and envelope is found to give good agreement with the experimentally measured cyclic stress-strain curves.


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