Fracture Mechanism of Ferritic Ductile Iron under Instrumented Impact Load at Low Temperatures

Xinning, Zhang; Qu, Yingdong; Li, Rongde

doi:10.2355/isijinternational.54.2309

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…It can be seen from the figure that the sample matrix consists of most pearlite, a certain amount of ferrite and a small amount of cementite. The spheroidal graphite is surrounded by ferrite and has a bull's eye shape, which is favorable for obtaining higher plasticity [8]. Calculated by Image-Pro Plus software, the percentage of pearlite and ferrite in the sample was 80.1% and 18.6%, in addition to a small amount of free cementite.…”

Section: Resultsmentioning

confidence: 99%

Effect of Annealing Treatment on Microstructure, Mechanical and Damping Properties of Ductile Iron

Zhang

Guo

Wang

et al. 2019

MSF

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Ductile iron was prepared through Sandwich Process and annealing treatment was carried out. The effects of annealing treatment on the microstructure, mechanical and damping properties of ductile iron were studied by means of metallographic microscope, scanning electron microscope, transmission electron microscope, universal test machine and dynamic thermal mechanical analyzer. The results show that annealing treatment has little effect on the morphology and distribution of graphite cast iron, but it will lead to the decrease of pearlite content in the matrix, the increase of ferrite content and the disappearance of cementite. Annealing transforms the fracture form of ductile iron from cleavage fracture to quasi-cleavage fracture, which greatly increases the ductile fracture area of the matrix compared with the as-cast, and tends to develop ductile fracture. The annealing treatment results in a decrease in the tensile strength of the ductile iron, but it can increase the plasticity and increase the elongation after fracture to 7.5 times that of the as-cast state. The damping value of as-cast ductile iron increases first and then decreases with the increase of temperature, and peaks at 190 °C when Q-1 is 0.025. The damping value of annealing ductile iron decreases with increasing temperature. The damping value increases with increasing strain amplitude before and after annealing. Annealing treatment will reduce the sensitivity of the damping property of ductile iron to strain amplitude.

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Section: Resultsmentioning

confidence: 99%

Effect of Annealing Treatment on Microstructure, Mechanical and Damping Properties of Ductile Iron

Zhang

Guo

Wang

et al. 2019

MSF

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“…The cleavage fracture mechanism of FDI at low temperatures is mainly 'crack initiation caused by vertical and crossed twins', crack initiation caused by twins is the primary cause of cleavage fracture [5]. Zhang [24] derived that the critical condition for cleavage fracture is determined by the critical size of the deformation twins. Based on Griffith criterion, the critical twin size P c can be expressed as follows: 3.4.…”

Section: Fractography and Crack Initiation Analysis At Low Temperatur...mentioning

confidence: 99%

Study of fractography of ferritic ductile iron at different temperatures and loading conditions

Wang,

Sun

et al. 2024

Mater. Res. Express

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This study characterizes the fractography of ferritic ductile iron under various loads, including tensile, fatigue and bending, and impact conditions. The results indicate that ductile fracture is the primary mechanism observed during tensile testing at room temperature. The fractography resulting from fatigue testing exhibits characteristics similar to cleavage fracture, and explains the formation of fatigue striations caused by the joint effects of dislocation slip and oxidation under crack tip stress. Under impact testing, the main fracture mechanism transitions from ductile to brittle with decreasing temperature. At high temperatures, fractography is mainly characterized by elliptical dimples with graphite nodules at the center that deform along the stress direction. In the ductile-brittle transition temperature range, a mixed fracture mechanism involving both dimples and cleavage patterns is observed. At low temperatures, the fracture mechanism is cleavage fracture, cleavage fracture is mainly caused by the deformation twin, inducing crack nucleation. These findings further validate D.O.Frenandino's quantitative analysis method for determining the main crack propagation direction of ductile fracture and brittle fracture. By employing larger statistical datasets, it is shown that this method yields high accuracy in determining the main crack propagation direction of ferritic ductile iron, thereby promoting its application as a general method for impact fractography anlysis.

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“…In recent years, with the rapid development of infrastructure construction, the demand for ductile iron parts in wind power, high-speed railways, engineering machinery and other industries has gradually increased. These castings work in the harsh environment and require high comprehensive performance of ductile iron, which requires high strength and good plasticity [8,9]. Therefore, improving the tensile strength, yield strength, hardness and elongation of ductile iron at room temperature is of great significance to engineering practice.…”

Section: Introductionmentioning

confidence: 99%

Mechanical properties prediction of ferrite ductile iron via machine learning

Gu,

Yao,

et al. 2023

Phys. Scr.

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The rapid development of the wind power industry requires ductile iron to maintain high toughness while improving strength. Machine learning offers the possibility to accelerate various aspects of material development and performance optimization. In this paper, we established a composition-property dataset for ferritic ductile iron, and a variety of machine learning algorithms are compared to construct a composition-property model for ferritic ductile iron finally. The composition is chosen as the model input, and the outputs are four properties: tensile strength, Brinell hardness, yield strength and elongation. The correlation coefficients of the models constructed are above 0.96, and the mean absolute percentage errors are below 5%. The mean relative error between the model predictions and the experimental values is 4.43%, which effectively verifies the reliability of the composition-properties model of ductile iron constructed. This paper also uses the machine learning model to predict the effect law of each element content on the mechanical properties of ductile iron, and uses thermodynamic prediction of phase composition to verify the reliability of the machine learning method to predict the mechanical properties of ductile iron, which provides strong guidance for the design of new ductile iron with high strength and high plasticity at room temperature.

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Fracture Mechanism of Ferritic Ductile Iron under Instrumented Impact Load at Low Temperatures

Cited by 5 publications

References 10 publications

Effect of Annealing Treatment on Microstructure, Mechanical and Damping Properties of Ductile Iron

Effect of Annealing Treatment on Microstructure, Mechanical and Damping Properties of Ductile Iron

Study of fractography of ferritic ductile iron at different temperatures and loading conditions

Mechanical properties prediction of ferrite ductile iron via machine learning

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