Effect of Shape on the Static and Dynamic Stress–Strain Relationship of Bonded Rubber in Compression

Nature ◽  
1956 ◽  
Vol 177 (4521) ◽  
pp. 1174-1175 ◽  
Author(s):  
A. R. PAYNE
Keyword(s):  
Dynamic Stress ◽  
Stress Strain ◽  
Strain Relationship ◽  
Relationship Of

Dynamic Stress-Strain Relationship of Saturated Clay by Dynamic Triaxial Test

2011 ◽  
Vol 250-253 ◽  
pp. 3183-3186
Author(s):  
Jian Yi Yuan
Keyword(s):  
Triaxial Test ◽  
Dynamic Stress ◽  
Soft Clay ◽  
Confining Pressure ◽  
Dynamic Shear ◽  
Stress Strain ◽  
Dynamic Triaxial Test ◽  
Wide Range ◽  
Strain Relationship ◽  
Relationship Of

Subgrade diseases are exposed more and more serious with raising speed of existing railway in wide range. Fro the complexity of dynamic stress-strain relationship of soil, dynamic triaxial test was used to analyze .the dynamic mechanics behavior under cyclic train load for saturated soft clay in Yangtze Delta region. Compaction coefficient, confining pressure, dynamic shear strsss ratio, inputing stimulus and loading frequence were taken into account in test. The results show that the dynamic stress-strain curves of soil specimen are provided with prominent hysteretic characteristics and area surrounded by hysteretic curves gradually augment and slope of hysteretic curve decreases with the increase of dynamic shear train amplitude. The strong correlation exists between dynamical stress and strain.

Semi-inverse method for predicting stress–strain relationship from cone indentations

2003 ◽  
Vol 18 (9) ◽  
pp. 2068-2078 ◽  
Author(s):  
A. DiCarlo ◽  
H. T. Y. Yang ◽  
S. Chandrasekar
Keyword(s):  
A Priori ◽  
Model Material ◽  
Material Behavior ◽  
The Finite Element Method ◽  
Stress Strain ◽  
Indentation Tests ◽  
Strain Relationship ◽  
Initial Force ◽  
Relationship Of ◽  
Force Displacement

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.

Study on Stress-Strain Relationship of Loess

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

scholarly journals Simulating the Stress-Strain Relationship of Geomaterials by Support Vector Machine

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Hongbo Zhao ◽  
Zenghui Huang ◽  
Zhengsheng Zou
Keyword(s):  
Support Vector Machine ◽  
Constitutive Relationship ◽  
Support Vector ◽  
Nonlinear Relationship ◽  
Ann Model ◽  
Stress Strain ◽  
Svm Model ◽  
Strain Relationship ◽  
Artificial Neural Network Ann ◽  
Relationship Of

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.

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