Effects of temperature on superplastic and fracture behaviors of a Ni-Co-based superalloy

Al-Hammadi, Rashad A.; Zhang, Rui; Cui, Chuanyong; ZHOU, Zijian; Zhou, Yizhou

doi:10.1016/j.jallcom.2023.170524

Cited by 9 publications

(1 citation statement)

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“…Generally, a small fracture section diameter indicates a good plastic deformation sidering local holes to bridge micro-cracks, the internal damage of the material is intensified, and the fracture of the alloy is easily induced. In addition, with an increasing strain rate, the degree of recrystallization decreases, and DRX behavior can aggravate the microvoid coalescence [43]. Therefore, the internal necking capability of the material and the progression of grain morphology collectively govern the initiation, and bonding mechanisms of the microvoids, which finally induces the rupturing of the sample.…”

Section: Influences Of Strain Ratementioning

confidence: 99%

Analysis of Hot Tensile Fracture and Flow Behaviors of Inconel 625 Superalloy

Pan,

Chen,

Ning

2024

Materials

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In this work, Inconel 625 alloy is explored regarding high-temperature tensile deformation and fracture behaviors at a strain rate of 0.005–0.01 s−1 under a deformation temperature ranging from 700–800 °C. The subsequent analysis focuses on the impact of deformation parameters on flow and fracture characteristics. The fractured surface reveals that ductile fracture is dominated by the nucleation, growth, and coalescence of microvoids as the primary failure mechanisms. The elevated deformation temperature and reduced strain rate stimulate the level of dynamically recrystallized (DRX) structures, resulting in intergranular fractures. The Arrhenius model and the particle swarm optimization-artificial neural network (PSO-ANN) model are developed to predict the hot tensile behavior of the superalloy. It indicates that the PSO-ANN model exhibits a correlation coefficient (R) as high as 0.9967, surpassing the corresponding coefficient of 0.9344 for the Arrhenius model. Furthermore, the relative absolute error of 9.13% (Arrhenius) and 1.85% (PSO-ANN model) are recorded. The developed PSO-ANN model accurately characterizes the flow features of the Inconel 625 superalloy with high precision and reliability.

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Section: Influences Of Strain Ratementioning

confidence: 99%