Shear Stress‐Strain Curve Generation from Simple Material Parameters

1990 ◽  
Vol 116 (8) ◽  
pp. 1255-1263 ◽  
Author(s):  
Jean H. Prevost ◽  
Catherine M. Keane
Keyword(s):  
Shear Stress ◽  
Strain Curve ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Simple Material ◽  
Material Parameters

Model for predicting the variation of shear stress in unsaturated soils during strain-softening

2020 ◽  
Author(s):  
Xiuhan Yang ◽  
Sai Vanapalli
Keyword(s):  
Shear Stress ◽  
Large Deformation ◽  
Unsaturated Soils ◽  
Strain Softening ◽  
Strain Curve ◽  
Published Data ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Strain Relationship ◽  
State Stress

Several of the geotechnical structures constructed with unsaturated soils undergo a large deformation prior to reaching failure conditions (e.g. progressive failure of a soil slope). During this process, the shear stress in soils typically increases initially and then reduces with an increase in the shear strain. The prediction of the stress-strain relationship is critical for reasonable interpretation of the mechanical behavior of those geo-structures that undergo large deformation. This paper introduces a model based on the disturbed state concept (DSC) to predict the variation of shear stress in unsaturated soils during strain-softening process under consolidated drained triaxial compression condition. In this model, the apparent stress-strain relationship is formulated as a weighted average of a hyperbolic hardening response extending the pre-peak state stress-strain curve and a linear response extending the critical state stress-strain curve with an assumed disturbance function as the weight. The prediction procedure is described in detail and the proposed model is validated using several sets of published data on unsaturated soils varying from coarse- to fine-grained soils. Finally, a comprehensive error analysis is undertaken based on an index of agreement approach.

The Effects of Strain Rate and Thickness on the Response of Thin Layers of Solder Loaded in Pure Shear

1997 ◽  
Vol 119 (2) ◽  
pp. 81-84 ◽  
Author(s):  
A. Gilat ◽  
K. Krishna
Keyword(s):  
Plastic Deformation ◽  
Shear Stress ◽  
Strain Rate ◽  
Mechanical Response ◽  
Pure Shear ◽  
Strain Curve ◽  
Thin Layers ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Stress And Deformation

A new configuration for testing thin layers of solder is introduced and employed to study the effects of strain rate and thickness on the mechanical response of eutectic Sn-Pb solder. The solder in the test is loaded under a well defined state of pure shear stress. The stress and deformation in the solder are measured very accurately to produce a reliable stress-strain curve. The results show that both the stress needed for plastic deformation and ductility increase with increasing strain rate.

scholarly journals A New S-Shape Specimen for Studying the Dynamic Shear Behavior of Metals

Metals ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 838 ◽  
Author(s):  
Ali Arab ◽  
Yansong Guo ◽  
Qiang Zhou ◽  
Pengwan Chen
Keyword(s):  
Shear Stress ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Strain Curve ◽  
Shear Behavior ◽  
Image Correlation ◽  
Specimen Geometry ◽  
Dynamic Shear ◽  
Stress Strain Curve ◽  
Stress Strain

A new S-shaped specimen geometry is developed in this study to investigate the shear behavior of materials under dynamic shear condition. Traditionally, hat-shaped geometry is used to study the dynamic shear of materials by a conventional split Hopkinson pressure bar apparatus. However, in this geometry, the force equilibrium on the two sides of the sample is difficult to fulfill, and the stress field in the shear region is not homogeneous. Hence, the calculated shear stress–strain curve from this geometry is not precise. To overcome this problem, the new S-shaped specimen is designed to achieve accurate shear stress–strain curve. This geometry can be used in a wide range of strain rates and does not require additional machining process for microstructure observation. The new S-shaped specimen is successfully coupled with digital image correlation method because of the flat surface. Digital image correlation results indicate that the fracture patterns of the new S-shaped specimen occur with maximum shear strains in the shear region in the middle of the sample. This result is also validated by finite element model simulation. The new S-shaped specimen geometry can be used to study the dynamic shear behavior of various metals.

Determination of Shear Stress-Strain Curve From Torsion Tests for Loading-Unloading and Cyclic Loading

1997 ◽  
Vol 119 (1) ◽  
pp. 113-115 ◽  
Author(s):  
Han-Chin Wu ◽  
Zhiyou Xu ◽  
Paul T. Wang
Keyword(s):  
Shear Stress ◽  
Cyclic Loading ◽  
Large Strain ◽  
Strain Curve ◽  
Strain Range ◽  
Torsion Test ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Modified Method ◽  
Fixed End

This paper discusses a method, based on Nadai’s solution, which can be used to determine the true (Cauchy) shear stress-strain curve of a material by means of torsion test of a solid shaft. The method is shown to be applicable to loading, unloading and cyclic loading. It is also applicable to fixed-end torsion of a solid shaft in the large shear strain range. A modified method has also been derived for the case of free-end torsion of a tubular specimen in the large strain range.

A modified version of MATLAB application window for predicting the weld bead profile and stress–strain plot of AA5052 CMT weldment using ER4043

SIMULATION ◽  
2021 ◽  
pp. 003754972110315
Author(s):  
B Girinath ◽  
N Siva Shanmugam
Keyword(s):  
Strain Curve ◽  
Weld Bead ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Hybrid Technique ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Weld Bead Geometry ◽  
Inference System ◽  
Engineering Stress

The present study deals with the extended version of our previous research work. In this article, for predicting the entire weld bead geometry and engineering stress–strain curve of the cold metal transfer (CMT) weldment, a MATLAB based application window (second version) is developed with certain modifications. In the first version, for predicting the entire weld bead geometry, apart from weld bead characteristics, x and y coordinates (24 from each) of the extracted points are considered. Finally, in the first version, 53 output values (five for weld bead characteristics and 48 for x and y coordinates) are predicted using both multiple regression analysis (MRA) and adaptive neuro fuzzy inference system (ANFIS) technique to get an idea related to the complete weld bead geometry without performing the actual welding process. The obtained weld bead shapes using both the techniques are compared with the experimentally obtained bead shapes. Based on the results obtained from the first version and the knowledge acquired from literature, the complete shape of weld bead obtained using ANFIS is in good agreement with the experimentally obtained weld bead shape. This motivated us to adopt a hybrid technique known as ANFIS (combined artificial neural network and fuzzy features) alone in this paper for predicting the weld bead shape and engineering stress–strain curve of the welded joint. In the present study, an attempt is made to evaluate the accuracy of the prediction when the number of trials is reduced to half and increasing the number of data points from the macrograph to twice. Complete weld bead geometry and the engineering stress–strain curves were predicted against the input welding parameters (welding current and welding speed), fed by the user in the MATLAB application window. Finally, the entire weld bead geometries were predicted by both the first and the second version are compared and validated with the experimentally obtained weld bead shapes. The similar procedure was followed for predicting the engineering stress–strain curve to compare with experimental outcomes.

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