The shear punch measurement of the mechanical properties of selected unirradiated and irradiated alloys

Kullen, P.S.; Smith, H. L.; Michel, D.J.

doi:10.1016/0022-3115(88)90154-7

Cited by 15 publications

(11 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Punch shear experiments measure the perforation resistance of materials such as metal and concrete. [1][2][3][4][5][6][7][8][9][10] These punch shear experimental techniques have been adopted by the authors (Figure 1(a)) [11][12][13][14][15][16] in quantifying the quasistatic penetration and perforation of composites. Perforation resistance is reported as punch shear strength (PSS, X PS ) and is defined as the maximum failure load divided by the punch shear area.…”

Section: Introductionmentioning

confidence: 99%

Stochastic micromechanical modeling of transverse punch shear damage behavior of unidirectional composites

Haque

Ali

Ganesh

et al. 2018

Journal of Composite Materials

View full text Add to dashboard Cite

Punch shear in unidirectional composites is induced by transverse shear loading that progressively perforates the laminate within a narrow shear annulus. At lower micromechanical length scales, punch shear loading creates unique micromechanical damage mechanisms dominated by transverse fiber shear failure, fiber-matrix interphase debonding and large inelastic deformation and cracking of the matrix. A new punch shear experimental method has been developed to test unidirectional S glass/DER353 epoxy composite ribbons at sub-millimeter length scale. The experimental data consist of a statistical measurement of the continuum response (load-deformation and punch shear strength) and the characterization of micromechanical damage modes. A simplified 2D micromechanical finite element model incorporating Weibull fiber strength distribution has been developed and correlated with the experimental data. The 2D micromechanical finite element model can simulate the punch shear failure of the ribbon incorporating mixed mode fiber fracture, and fiber-matrix debonding mechanisms using zero thickness cohesive elements. Results from stochastic simulations of punch shear experiments show that an equivalent 2D micromechanical finite element model can predict the micromechanical damage mechanisms and the statistical distribution of punch shear strength of the continuum with favorable correlation with the experiments. This paper presents a combined experimental and computational approach in simulating the stochastic non-linear progressive punch shear behavior of unidirectional composites for the first time in the literature.

show abstract

Section: Introductionmentioning

confidence: 99%

Stochastic micromechanical modeling of transverse punch shear damage behavior of unidirectional composites

Haque

Ali

Ganesh

et al. 2018

Journal of Composite Materials

View full text Add to dashboard Cite

show abstract

“…Mao and Takahashi [5] and Mao et al [6] investigated the deformation behaviour using small punch test. Kullen et al [7] employed a shear punch test technique to determine the mechanical properties of neutron irradiated 9Cr-1Mo and 12Cr-1Mo steels. Pandey and Bhowmick [8] further used the disk bend test specimen to predict tensile properties and fracture toughness (J IC ) for a number of steels.…”

Section: Introductionmentioning

confidence: 99%

Quasi‐Non‐Destructive Evaluation of Yield Strength Using Neural Networks

Partheepan

Sehgal

Pandey

2011

Advances in Artificial Neural Systems

View full text Add to dashboard Cite

The objective of this paper is to delineate a method for determining the yield strength of a material in a virtually nondestructive manner. Conventional test methods for predicting the yield strength require the removal of large material samples from the in-service component, which is impractical. In this paper, the power of neural networks in predicting the yield strength from the data obtained by conducting tension test on newly developed dumb-bell-shaped miniature specimen is demonstrated using the self-organizing capabilities of the ANN. The input to the neural network is the breakaway load obtained from the miniature test, and the output obtained from the model is yield strength value. The value of the yield strength estimated by neural network is found to be in good agreement (<5% error) with that of the actual value from the standard test. The neural network models are convenient and powerful tools for practical applications in solving various problems in engineering.

show abstract

“…[1][2][3][4] More recently, these technologies have been utilised also when only a small specimen volume is available. [5][6][7][8] The numerous approaches that have been considered range from a simple scale down of some standard specimen geometry to developing methods that utilise a pre-existing, small volume specimen.…”

Section: Introductionmentioning

confidence: 99%

“…Small specimen testing techniques were initially developed because of the need to determine the effects of irradiation on the material properties using a volume of specimen small enough to fit into irradiation test assemblies. [1][2][3][4] More recently, these technologies have been utilised also when only a small specimen volume is available. [5][6][7][8] The numerous approaches that have been considered range from a simple scale down of some standard specimen geometry to developing methods that utilise a pre-existing, small volume specimen.…”

Section: Introductionmentioning

confidence: 99%

Application of small specimen testing technique for mechanical property assessment of discontinuously reinforced composites

Wanjara¹,

Drew²,

Yue³

2006

Materials Science and Technology

View full text Add to dashboard Cite

The shear punch experiment is a small specimen testing technique that has been used to assess the flow properties, such as strength and ductility, of traditional engineering alloys when material availability is limited. In the present study, the applicability of a laboratory shear punch testing system, which was fabricated to evaluate the mechanical properties of different materials (steels, aluminium alloys, copper alloys, titanium alloys and cobalt alloys), was extended to include tensile mechanical property assessment of discontinuously reinforced metal matrix composites. In employing this testing technique to discontinuously reinforced composites, the shear punch loaddisplacement data were examined to identify the critical regions of the flow curve, i.e. elasticity followed by yielding, work hardening, ultimate tensile strength and fracture. The loaddisplacement curves and the fracture characteristics generated by shear punch testing were then compared with the conventional tensile data and failure behaviour in order to calibrate the method for composite materials. It was determined that the flow characteristics from shear punch testing can be used to predict the mechanical properties of discontinuously reinforced metal matrix composites through linear correlations for the yield strength, ultimate tensile strength and percent elongation.

show abstract

The shear punch measurement of the mechanical properties of selected unirradiated and irradiated alloys

Cited by 15 publications

References 4 publications

Stochastic micromechanical modeling of transverse punch shear damage behavior of unidirectional composites

Stochastic micromechanical modeling of transverse punch shear damage behavior of unidirectional composites

Quasi‐Non‐Destructive Evaluation of Yield Strength Using Neural Networks

Application of small specimen testing technique for mechanical property assessment of discontinuously reinforced composites

Contact Info

Product

Resources

About