Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process

Fan, Y.S.; Yang, Xiaoguang; Shi, Duoqi; Tan, Ling; Huang, Weiqing

doi:10.1016/j.matdes.2021.109561

Cited by 29 publications

(9 citation statements)

References 55 publications

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“…However, researchers have focused on developing physical models for establishing quantitative relationships between the states of microstructures, aging or service processes, and the corresponding phases of physical properties. A data-driven model for small data can be an alternative to developing quantitative relationships beyond the conventional method [8].…”

Section: Yearmentioning

confidence: 99%

“…However, researchers have focused on developing physical model quantitative relationships between the states of microstructures, agin cesses, and the corresponding phases of physical properties. A data-d small data can be an alternative to developing quantitative relationships ventional method [8]. The gas path analysis (GPA) method is traditionally used for gas t This is a method of calculating component characteristic parameters su and turbine efficiency, heat of combustion of fuel, and unmeasured v temperature and pressure from measured data [9].…”

Section: Yearmentioning

confidence: 99%

“…Authors of another study [8] used SEM image data of the nickel-based superalloy in a method for quantifying and connecting the degradation of the service process microstructure and the degradation of physical properties for a nickel-based superalloy based on the imaging process of the length distribution of the strings. The feature descriptor for extracting the tissue shape and size information from the microstructure image obtained from the SEM image was quantified based on the TP-CLD (two phase rotary chord length distributions) method.…”

Section: Related Workmentioning

confidence: 99%

“…As a result, the predictive power at unobserved points may be poor. It is difficult to intuitively judge the shape of the microstructure using the dimensionally reduced principal component from TP-CLD as the response variable of the regression model [8].…”

Section: Related Workmentioning

confidence: 99%

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AI-Based Degradation Index from the Microstructure Image and Life Prediction Models Based on Bayesian Inference

2023

Sustainability

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In this study, we propose a consistent and explainable degradation indexing method and a non-destructive-based degradation and creep-life prediction method from extensive destructive test (creep-rupture) data of a nickel-based superalloy (DA-5161 SX), an extreme-environment material. High-temperature components made of nickel-based superalloys that operate in extreme environments (e.g., gas turbine blades) deteriorate over time and shorten the life of the device. To ensure the safety and efficiency of the equipment, it is important to predict the lifetime of high-temperature parts, and a consistent and explanatory degradation index and a reliable predictive model that can predict the degree of degradation and life without destructive testing of high-temperature parts are needed. As the degradation of nickel-based superalloys progresses, degradation indices reflecting the geometrical characteristics are required that focus on the fact that the shape of the gamma-prime phase becomes longer and larger. A representative value of the degradation index was selected through parameter inference based on a Bayesian method, and the high-dimensional degradation index of previous studies was simplified to only one dimension. The robustness of the degradation index quantification model was verified by confirming that the degradation index obtained from 20% of the test images had the lowest change rate of the degradation index obtained from 80% of the training images at 6.9%. The basis for predicting the life of high-temperature parts without destructive testing was established in the degradation index and life prediction model by connecting environmental conditions and degradation indices/the LMP (Larson–Miller parameter) to represent creep life in regression models. Gaussian process regression (GPR) models based on sampling-based Bayesian inference performed well in terms of both RMSE in the degradation index and the LMP prediction model, demonstrating robust behavior in performance variation. This may be used as a key health factor that indicates the soundness of diagnostic solutions in the future, and it is expected to be a foundational technology for decision-making models for maintenance, repair, and disposal.

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Section: Yearmentioning

confidence: 99%

Section: Yearmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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AI-Based Degradation Index from the Microstructure Image and Life Prediction Models Based on Bayesian Inference

2023

Sustainability

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“…Nickel-based superalloys (Ni 0.25 Al 0.75 , NiAl, Ni 0.75 Al 0.25 , etc.) are key materials in the manufacture of advanced aero engines because of their excellent properties, such as resistance to high-temperature deformation, oxidation and corrosion, especially their ability to work at temperatures as high as 85% to 90% of the melting point [ 1 , 2 , 3 , 4 ]. Ni 3 Al superalloy has a melting point temperature as high as 1395 °C and excellent yield properties in the middle-temperature range of 600–800 °C due to its new two-phase (γ′-γ) microstructure; therefore, it has received significant research attention and has become one of the most promising candidate materials for blades and impellers of the new-generation aero engine [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Transient Liquid Phase Diffusion Bonding of Ni3Al Superalloy with Low-Boron Nickel-Base Powder Interlayer

Wen

Liu

et al. 2023

Materials

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As a technology for micro-deformed solid-phase connection, transient liquid phase (TLP) diffusion bonding plays a key role in the manufacture of heating components of aero engines. However, the harmful brittle phase and high hardness limit the application of TLP diffusion bonding in nickel-based superalloys. In this paper, a new strategy in which a low-boron and high-titanium interlayer can restrain the brittle phase and reduce the hardness of the TLP-diffusion-bonded joint is proposed. With this strategy, the Ni3Al joint can achieve a high strength of 860.84 ± 26.9 MPa under conditions of 1250 °C, 6 h and 5 MPa. The microhardness results show that the average microhardness of the joint area is 420.33 ± 3.15 HV and is only 4.3% higher than that of the Ni3Al base material, which proves that this strategy can effectively inhibit the formation of the harmful brittle phase in the joint area. The results of EBSD show that 7.7% of the twin boundaries exist in the isothermal solidification zone, and only small amounts of secondary precipitates are observed at the grain boundaries in the joint, which indicates that twin boundaries may play a dominant role in crack initiation. This study provides a feasible avenue to suppress the brittle phase in TLP-diffusion-bonded joints.

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Restoring Plasticity in Nickel‐Based Superalloy Using High‐Density Pulsed Electric Current

Yan,

Gu,

Yoon

et al. 2024

Adv Eng Mater

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This study explores the efficacy of high‐density pulsed electric current (HDPEC) in healing plastic deformation damage in single‐crystal Ni‐based superalloys. Single‐crystal specimens are prepared from directionally solidified nickel‐based superalloy to assess the potential of electric current treatment in restoring plastic deformation capability. Experiments involving various current densities and pulse durations reveal that a pulsed electric current of 17 ms at 400 A mm−2 yields optimal results, enhancing fracture elongation from 7.8% to 12.3% without compromising strength. The study conducts a comprehensive analysis of microstructural changes induced by pulsed electric current, employing quasi‐in‐situ electron backscatter diffraction and transmission electron microscopy techniques. The results demonstrate that HDPEC disrupts the planar dislocation network, homogenizes dislocation distribution, and promotes dislocation entanglement. Consequently, microdefects in the alloy are eliminated, restoring the material's ductility. The findings suggest that this technology holds significant promise for repairing fatigued components and underscore the potential for further research in this domain.

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Quantitative mapping of service process-microstructural degradation-property deterioration for a Ni-based superalloy based on chord length distribution imaging process

Cited by 29 publications

References 55 publications

AI-Based Degradation Index from the Microstructure Image and Life Prediction Models Based on Bayesian Inference

AI-Based Degradation Index from the Microstructure Image and Life Prediction Models Based on Bayesian Inference

Transient Liquid Phase Diffusion Bonding of Ni3Al Superalloy with Low-Boron Nickel-Base Powder Interlayer

Restoring Plasticity in Nickel‐Based Superalloy Using High‐Density Pulsed Electric Current

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