A new elastic characterization method for anisotropic bilayer specimens via Bayesian resonant ultrasound spectroscopy

Goodlet, Brent; Bales, Ben; Pollock, Tresa M.

doi:10.1016/j.ultras.2021.106455

Cited by 5 publications

(2 citation statements)

References 49 publications

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“…The concept of the derivative of a spectrum is widely adopted for enhancing the signal strength in signal processing 50 , 51 . However, neither direct input nor derivative input is robust against missing resonant frequencies, which is a common issue in the experimental RUS data 35 , 52 . This is because the missing resonant frequencies change the sequence of frequencies, and that potentially impacts the accuracy of NN models when retrieving elastic moduli.…”

Section: Resultsmentioning

confidence: 99%

A modulated fingerprint assisted machine learning method for retrieving elastic moduli from resonant ultrasound spectroscopy

Liu

Zhao

et al. 2023

Sci Rep

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We used deep-learning-based models to automatically obtain elastic moduli from resonant ultrasound spectroscopy (RUS) spectra, which conventionally require user intervention of published analysis codes. By strategically converting theoretical RUS spectra into their modulated fingerprints and using them as a dataset to train neural network models, we obtained models that successfully predicted both elastic moduli from theoretical test spectra of an isotropic material and from a measured steel RUS spectrum with up to 9.6% missing resonances. We further trained modulated fingerprint-based models to resolve RUS spectra from yttrium–aluminum-garnet (YAG) ceramic samples with three elastic moduli. The resulting models were capable of retrieving all three elastic moduli from spectra with a maximum of 26% missing frequencies. In summary, our modulated fingerprint method is an efficient tool to transform raw spectroscopy data and train neural network models with high accuracy and resistance to spectra distortion.

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Section: Resultsmentioning

confidence: 99%

A modulated fingerprint assisted machine learning method for retrieving elastic moduli from resonant ultrasound spectroscopy

Liu

Zhao

et al. 2023

Sci Rep

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“…[13] Therefore, the same group distinguished c¢-strengthened superalloys with nearly equal levels of Co and Ni as a novel intriguing subclass of high-temperature alloys and commenced with the detailed investigation of elastic constants. [22,23] Nevertheless, our previous investigations of the oxide scale growth on the multinary ERBOCo-1 superalloy [1] indicated that it may be possible to reach comparable oxidation resistance in compositions with higher Co levels compared to Ni above 1050 °C.…”

Section: Introductionmentioning

confidence: 96%

Influence of the Co/Ni Ratio and Dendritic Segregations on the High-Temperature Oxidation Resistance of Multinary Co-Rich Superalloys at 850 °C and 1050 °C

Hagen

Weiser

Abu-Khousa

et al. 2022

Metall Mater Trans A

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Excellent inherent oxidation resistance is a prerequisite for the use of superalloys in many high-temperature applications. To achieve this goal, typically continuous alumina and chromia scale growths are assured through sufficient Cr and Al additions. Since the intended γ/γ′-microstructure of superalloys is only stable within a certain compositional window, the maximum concentrations of these protective scale forming elements are, however, dependent on the overall alloy composition. The latter is a severe drawback, especially for Co-rich superalloys, as for these the maximum content often is insufficient for reaching the desired continuous scale growth. In recent years, the addition of significant Ni levels was identified to improve the high-temperature oxidation properties in the case of simple model alloy systems. In this study, we compare the high-temperature oxidation behavior of two complex Co-rich multinary single-crystalline γ/γ′-strengthened superalloys that only differ regarding their Co/Ni ratios to the commercial Ni-base superalloy CMSX-4. Therefore, time-resolved isothermal gravimetric analysis (TGA) in synthetic air at 850 °C and 1050 °C for 100 hours, scanning electron microscopy analysis (SEM), and electron probe microanalysis (EPMA) were conducted. The results point out that a high Co-content beneficially affects the oxidation resistance at 850 °C, meaning that the Ni-base CMSX-4 is slightly outmatched by the Co-rich competitors. In contrast, at 1050 °C, the commercial (most Ni-rich) alloy performed best and, clearly, an increasing Co-content was identified to deteriorate the oxidation resistance. This temperature-dependent influence of the nominal Co/Ni ratio on oxidation resistance is shown to be especially pronounced for dendritic regions. Consequently, the latter could be identified to especially determine the overall oxidation kinetics.

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Inverse identification of geometric and acoustic parameters of inhomogeneous coatings through URCAS-based least-squares coupled cross-correlation algorithm

Lin

et al. 2022

Ultrasonics

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A new elastic characterization method for anisotropic bilayer specimens via Bayesian resonant ultrasound spectroscopy

Cited by 5 publications

References 49 publications

A modulated fingerprint assisted machine learning method for retrieving elastic moduli from resonant ultrasound spectroscopy

A modulated fingerprint assisted machine learning method for retrieving elastic moduli from resonant ultrasound spectroscopy

Influence of the Co/Ni Ratio and Dendritic Segregations on the High-Temperature Oxidation Resistance of Multinary Co-Rich Superalloys at 850 °C and 1050 °C

Inverse identification of geometric and acoustic parameters of inhomogeneous coatings through URCAS-based least-squares coupled cross-correlation algorithm

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