A contribution on the velocity of longitudinal elastic vibrations in cylindrical rods, and on the relationship between Young’s modulus and temperature for aluminium

1950 ◽  
Vol 7 (S2) ◽  
pp. 332-340 ◽  
Author(s):  
E. G. Stanford
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Elastic Vibrations ◽  
The Relationship

Transverse Young's Moduli and Cell Shapes in Coniferous Early Wood

Holzforschung ◽  
2002 ◽  
Vol 56 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Ugai Watanabe ◽  
Minoru Fujita ◽  
Misato Norimoto
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Bending Moment ◽  
Cell Models ◽  
Young’S Moduli ◽  
Cell Shapes ◽  
The Difference ◽  
Square Cells ◽  
Experimental Values ◽  
The Relationship

Summary The relationship between transverse Young's moduli and cell shapes in coniferous early wood was investigated using cell models constructed by two dimensional power spectrum analysis. The calculated values of tangential Young's modulus qualitatively explained the relationship between experimental values and density as well as the difference in experimental values among species. The calculated values of radial Young's modulus for the species having hexagonal cells agreed well with the experimental values, whereas, for the species having square cells, the calculated values were much larger than the experimental values. This result was ascribed to the fact that the bending moment on the radial cell wall of square cell models was calculated to be small. It is suggested that the asymmetrical shape of real wood cells or the behavior of nodes during ell deformation is an important factor in the mechanism of linear elastic deformation of wood cells.

Prediction of Springback in Metal Forming of Diaphragm of Automotive Horn Based on BPANN

2010 ◽  
Vol 139-141 ◽  
pp. 594-599
Author(s):  
Yan Qiu Zhang ◽  
Shu Yong Jiang ◽  
Yu Feng Zheng
Keyword(s):  
Young’S Modulus ◽  
Metal Forming ◽  
Young's Modulus ◽  
Steel Strip ◽  
Back Propagation ◽  
Spring Steel ◽  
Yield Ratio ◽  
Punch Radius ◽  
Cold Rolled ◽  
The Relationship

The spring steel strip 50CrVA which is cold rolled was applied to manufacture the diaphragm of the automotive horn by means of sheet metal forming. The combination of the experiments with back-propagation artificial neural network (BPANN) is used to solve the springback problem of the diaphragm. Experiments have shown that a 4-8-1 BPANN is able to predict the springback of the diaphragm successfully, and the network is able to model the relationship between the springback of the diaphragm and the process parameters rationally. BPANN simulation results and experimental ones have shown that the springback of the diaphragm is particularly influenced by such parameters as blank thickness, Young’s modulus, punch radius and yield ratio. Furthermore, the springback of the diaphragm decreases with the increase of blank thickness and Young’s modulus, but increases with the increase of punch radius and yield ratio.

Modified Model for Static Behavior of Microcantilever Gas Sensor Adsorbed with Monolayer Molecules

2011 ◽  
Vol 415-417 ◽  
pp. 455-459
Author(s):  
Xiao Ming Wang ◽  
Fei Wang ◽  
Xue Zeng Zhao ◽  
Da Lei Jing
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Curvature Radius ◽  
Static Behavior ◽  
Neutral Layer ◽  
Modified Model ◽  
Adsorbed Molecules ◽  
Microcantilever Sensors ◽  
The Relationship ◽  
Layer Position

The modified static bending model of microcantilever with monolayer molecules has been established based on energy method, in which the change in neutral layer position caused by adsorption-induced stress has been considered. On this basis, we have analyzed the relationship between the bending curvature radius of a microcantilever with its thickness, Young’s modulus and molecule-molecule distance of adsorbed molecules when it is adsorbed with monolayer water molecules. Additionally, we have investigated the effect of change in neutral layer position on the static behavior of microcantilever sensors and have found that: 1) the bending curvature radius of microcantilever is affected by its Young’s modulus, thickness and distance of adsorbed molecules respectively; 2)the predicted error of bending curvature radius caused by the change in neutral layer position slightly increases with decreasing Young’s modulus and thickness, whereas the effect of distance between adsorbed molecules on the error is significant.

Effect of the Quenching Temperature on the Phase Composition and Youngʹs Modulus of Corrosion-Resistant and Biocompatible Titanium Alloys

2019 ◽  
Vol 946 ◽  
pp. 309-314 ◽  
Author(s):  
Anatoly G. Illarionov ◽  
S.V. Grib ◽  
A.V. Huppeev
Keyword(s):  
Phase Composition ◽  
Titanium Alloys ◽  
Young’S Modulus ◽  
Young's Modulus ◽  
Two Phase ◽  
Quenching Temperature ◽  
Thermo Calc Software ◽  
Extreme Change ◽  
The Relationship ◽  
Micro Indentation

The relationship between the phase composition and the Young’s modulus in quenched PT-7M, Ti-6Al-7Nb, BT16 titanium alloys has been studied using the structural analysis, thermodynamic calculations in the Thermo-Calc software and micro-indentation. It is found that the nature of the change in the Young’s modulus in the investigated titanium alloys after quenching from the two-phase α+β-region depends on the chemical composition of the alloy, which determines the nature of the observed metastable phases (α', α", ω, β). The correlation between the extreme change in the Young’s modulus from the quenching temperature and the so-called interatomic bonding force (Fb) calculated from the electronic structure parameters of the α, α', β phases was shown for the Ti-6Al-7Nb alloy. The relationship between the limits of the Young’s modulus of the investigated alloys during quenching with the level of their alloying with α-and β-stabilizers is shown.

scholarly journals The relationship between the Young’s modulus and dry etching rate of polydimethylsiloxane (PDMS)

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Matthew L. Fitzgerald ◽  
Sara Tsai ◽  
Leon M. Bellan ◽  
Rebecca Sappington ◽  
Yaqiong Xu ◽  
...  
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Etching Rate ◽  
Dry Etching ◽  
The Relationship

Correlations among Physical and Mechanical Parameters of Rocks

2017 ◽  
Vol 865 ◽  
pp. 366-372
Author(s):  
Jing Sen Liu ◽  
Hai Bo Li ◽  
Guo Kai Zhang ◽  
Jian Deng
Keyword(s):  
Shear Modulus ◽  
Young’S Modulus ◽  
Young's Modulus ◽  
P Wave ◽  
Physical Parameters ◽  
Dynamic Shear Modulus ◽  
Regression Equations ◽  
Mechanical Parameters ◽  
P Wave Velocity ◽  
The Relationship

In order to improve the accuracy of the rock mechanical parameters, the correlations among physical and mechanical parameters were investigated. A large number of laboratory testing results curried out on 408 rock specimens including metamorphic rocks, sedimentary rocks and igneous rocks. Through the statistical analysis of the laboratory test data, several regression equations among rock material parameters were established. The research suggests that, in addition to Poisson's ratio, the mechanical parameters (unconfined compressive strength (UCS), elastic Young’s modulus, shear modulus) relate well to physical parameters (porosity, P-wave velocity), and the relationships are mainly described by power and exponential correlations which have good squared regression coefficients. The correlation between elastic Young’s modulus and dynamic elastic modulus was established, as well as the relationship between shear modulus and dynamic shear modulus.

Analysis of nanoindentation load-displacement loading curves

1996 ◽  
Vol 11 (8) ◽  
pp. 1987-1995 ◽  
Author(s):  
S. V. Hainsworth ◽  
H. W. Chandler ◽  
T. F. Page
Keyword(s):  
Young’S Modulus ◽  
Young's Modulus ◽  
Elastic Recovery ◽  
Hard Coatings ◽  
Attractive Alternative ◽  
Indentation Hardness ◽  
Test Volume ◽  
Considerable Difficulty ◽  
Load Displacement ◽  
The Relationship

Nanoindentation load-displacement curves provide a “mechanical fingerprint” of a materials response to contact deformation. Over the last few years, much attention has been focused on understanding the factors controlling the detailed shape of unloading curves so that parameters such as true contact area, Young's modulus, and an indentation hardness number can be derived. When the unloading curve is well behaved (by which we mean approximating to linear behavior, or alternatively, fitting a power-law relationship), then this approach can be very successful. However, when the test volume displays considerable elastic recovery as the load is removed [e.g., for many stiff hard materials and many inhomogeneous systems (e.g., those employing thin hard coatings)], then the unloading curve fits no existing model particularly well. This results in considerable difficulty in obtaining valid mechanical property data for these types of materials. An alternative approach, described here, is to attempt to understand the shapes of nanoindentation loading curve and thus quantitatively model the relationship between Young's modulus, indentation hardness, indenter geometry, and the resultant maximum displacement for a given load. This paper describes the development and refinement of a previous approach by Loubet et al1 originally suggested for a Vickers indenter, but applied here to understand the factors that control the shape of the loading curve during nanoindentation experiments with a pointed, trigonal (Berkovich) indenter. For a range of materials, the relationship P = Kmδ2 was found to describe the indenter displacement, δ, in terms of the applied load P. For each material, Km can be predicted from the Young's modulus (E) and the hardness (H). The result is that if either E or H is known, then the other may be calculated from the experimental loading curve. This approach provides an attractive alternative to finite element modeling and is a tractable approach for those cases where analysis of unloading curves is infeasible.

Sign in / Sign up

Export Citation Format

Share Document