Fracture toughness and absorbed energy measurements in impact tests on brittle materials

1973 ◽  
Vol 8 (7) ◽  
pp. 949-956 ◽  
Author(s):  
G. P. Marshall ◽  
J. G. Williams ◽  
C. E. Turner
Keyword(s):  
Fracture Toughness ◽  
Brittle Materials ◽  
Absorbed Energy ◽  
Impact Tests

Effect of toughened polyamide-coated carbon fiber fabric on the mechanical performance and fracture toughness of CFRP

2021 ◽  
pp. 002199832199945
Author(s):  
Jong H Eun ◽  
Bo K Choi ◽  
Sun M Sung ◽  
Min S Kim ◽  
Joon S Lee
Keyword(s):  
Mechanical Properties ◽  
Fracture Toughness ◽  
Photoelectron Spectroscopy ◽  
Mechanical Performance ◽  
Epoxy Composites ◽  
Scanning Calorimetry ◽  
Internal Damage ◽  
Impact Tests ◽  
Flexural Tests ◽  
The Impact

In this study, carbon/epoxy composites were manufactured by coating with a polyamide at different weight percentages (5 wt.%, 10 wt.%, 15 wt.%, and 20 wt.%) to improve their impact resistance and fracture toughness. The chemical reaction between the polyamide and epoxy resin were examined by fourier transform infrared spectroscopy, differential scanning calorimetry and X-ray photoelectron spectroscopy. The mechanical properties and fracture toughness of the carbon/epoxy composites were analyzed. The mechanical properties of the carbon/epoxy composites, such as transverse flexural tests, longitudinal flexural tests, and impact tests, were investigated. After the impact tests, an ultrasonic C-scan was performed to reveal the internal damage area. The interlaminar fracture toughness of the carbon/epoxy composites was measured using a mode I test. The critical energy release rates were increased by 77% compared to the virgin carbon/epoxy composites. The surface morphology of the fractured surface was observed. The toughening mechanism of the carbon/epoxy composites was suggested based on the confirmed experimental data.

scholarly journals On the Use of Approximation Methods for Microcrack Shielding Problems

1992 ◽  
Vol 59 (3) ◽  
pp. 497-501 ◽  
Author(s):  
H. Cai ◽  
K. T. Faber
Keyword(s):  
Fracture Toughness ◽  
Numerical Solution ◽  
Experimental Evidence ◽  
Discrete Model ◽  
Brittle Materials ◽  
Approximation Methods ◽  
Exact Formulation

There is experimental evidence that stress-induced microcracking near a macrocrack tip enhances the fracture toughness of brittle materials. In considering the interaction of the macrocrack with multiple microcracks using a discrete model, it is essential to use approximation methods in order to keep the amount of the computation to a tractable level. However, when crack distances are small, the results of the approximation methods can be significantly different from the numerical solution based upon the exact formulation. The results obtained by these approximation methods will be compared with the numerical solution to show the applicability ranges in which the errors are acceptably small. The use of results obtained by the approximation methods outside applicability ranges in literature is shown to lead to incorrect conclusions concerning microcrack shielding.

Modified Equation to Predict Leak/Rupture Criteria for Axially Through-Wall Notched X80 and X100 Linepipes Having Higher Charpy Energy

2004 ◽  
Author(s):  
Shinobu Kawaguchi ◽  
Naoto Hagiwara ◽  
Mitsuru Ohata ◽  
Masao Toyoda
Keyword(s):  
Fracture Toughness ◽  
Flow Stress ◽  
Pipe Material ◽  
Test Results ◽  
Absorbed Energy ◽  
Bending Tests ◽  
Full Scale Tests ◽  
Hoop Stresses ◽  
The Relationship ◽  
Modified Equation

A method of predicting the leak/rupture criteria for API 5L X80 and X100 linepipes was evaluated, based on the results of hydrostatic full-scale tests for X60, X65, X80 and X100 linepipes with an axially through-wall (TW) notch. The TW notch test results clarified the leak/rupture criteria, that is, the relationship between the initial notch lengths and the maximum hoop stresses during the TW notch tests. The obtained leak/rupture criteria were then compared to the prediction of the Charpy V-notch (CVN) absorbed energy-based equation, which has been proposed by Kiefner et al. The comparison revealed that the CVN-based equation was not applicable to the pipes having a CVN energy (Cv) greater than 130 J and flow stress greater than X65. In order to predict the leak/rupture criteria for these linepipes, the static absorbed energy for ductile cracking, (Cvs)i, was introduced as representing the fracture toughness of a pipe material. The (Cvs)i value was determined from the microscopic observation of the cut and buffed Charpy V-notch specimens after static 3-point bending tests. The CVN energy in the original CVN-based equation was replaced by an equivalent CVN energy, (Cv)eq’ which was defined as follows: (Cv)eq = 4.5 (Cvs)i. The leak/rupture criteria for the X80 and X100 linepipes with higher CVN energies were reasonably predicted by the modified equation using the (Cvs)i value.

Machine learning predictions on fracture toughness of multiscale bio-nano-composites

2020 ◽  
Vol 39 (15-16) ◽  
pp. 587-598 ◽  
Author(s):  
Vahid Daghigh ◽  
Thomas E Lacy ◽  
Hamid Daghigh ◽  
Grace Gu ◽  
Kourosh T Baghaei ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Machine Learning ◽  
Fracture Toughness ◽  
Finite Element Analysis ◽  
Finite Element ◽  
Nano Composites ◽  
Natural Material ◽  
Element Analysis ◽  
Adaptive Boosting ◽  
Impact Tests

Tailorability is an important advantage of composites. Incorporating new bio-reinforcements into composites can contribute to using agricultural wastes and creating tougher and more reliable materials. Nevertheless, the huge number of possible natural material combinations works against finding optimal composite designs. Here, machine learning was employed to effectively predict fracture toughness properties of multiscale bio-nano-composites. Charpy impact tests were conducted on composites with various combinations of two new bio fillers, pistachio shell powders, and fractal date seed particles, as well as nano-clays and short latania fibers, all which reinforce a poly(propylene)/ethylene–propylene–diene-monomer matrix. The measured energy absorptions obtained were used to calculate strain energy release rates as a fracture toughness parameter using linear elastic fracture mechanics and finite element analysis approaches. Despite the limited number of training data obtained from these impact tests and finite element analysis, the machine learning results were accurate for prediction and optimal design. This study applied the decision tree regressor and adaptive boosting regressor machine learning methods in contrast to the K-nearest neighbor regressor machine learning approach used in our previous study for heat deflection temperature predictions. Scanning electron microscopy, optical microscopy, and transmission electron microscopy were used to study the nano-clay dispersion and impact fracture morphology.

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