Ultrasonic Benchmarking Study: Overview Up to Year 2005

Song, Sung‐Jin; Schmerr, Lester W.; Thompson, R. B.

doi:10.1063/1.2184744

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…This can avoid frequency dependent assumptions in simpler models such as the Kirchhoff approximation. The output is a time domain waveform, which has been shown to compare well with experiment in a variety of validations [5,7]. Two examples will be given to illustrate applications of the small flaw model.…”

Section: Small Flaw Modelmentioning

confidence: 99%

Utsim: Overview and Application

Garton

Gray

Thompson

et al. 2010

AIP Conference Proceedings

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UTSim is a software package developed to help plan and refine ultrasonic inspections for complex shaped components. The software reads 3D solid-model CAD representations of the components. Virtually any shape or complexity of object can be loaded and examined using the ultrasonic ray tracing tools in UTSim. For many applications, the software can also be used to model ultrasonic beam propagation as well as the response from flaws within a component. This presentation will give an overview of UTSim and its features and will demonstrate examples of its ultrasonic simulation capabilities. ABSTRACT. UTSim is a software package developed to help plan and refine ultrasonic inspections for complex shaped components. The software reads 3D solid-model CAD representations of the components. Virtually any shape or complexity of object can be loaded and examined using the ultrasonic ray tracing tools in UTSim. For many applications, the software can also be used to model ultrasonic beam propagation as well as the response from flaws within a component. This presentation will give an overview of UTSim and its features and will demonstrate examples of its ultrasonic simulation capabilities.

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Section: Small Flaw Modelmentioning

confidence: 99%

Utsim: Overview and Application

Garton

Gray

Thompson

et al. 2010

AIP Conference Proceedings

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“…Ordinary least-square fitting techniques can provide clear empirical formulas for linking ultrasonic characteristics to microstructure parameters, and their connection can even be non-causal, as principal components analysis or specialized signal analysis methodologies are used (Lyapunov exponent, fractal dimension, recurrence analysis, etc.). The resultant models, however, are oversimplified due to the omission of many uncertainties [16][17][18], and the impacts of coupling factors or multi-variable factors on ultrasonic characteristics cannot be eliminated [19]. Machine learning methods are data-driven, which reduces the need for artificial selection of ultrasonic characteristics.…”

Section: Introductionmentioning

confidence: 99%

Long-Term Ultrasonic Benchmarking for Microstructure Characterization with Bayesian Updating

Zhang

Song

et al. 2022

Metals

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Ultrasonic non-destructive characterization is an appealing technique for identifying the microstructures of materials in place of destructive testing. However, the existing ultrasonic characterization techniques do not have sufficient long-term gage repeatability and reproducibility (GR&R), since benchmarking data are not updated. In this study, a hierarchical Bayesian regression model was utilized to provide a long-term ultrasonic benchmarking method for microstructure characterization, suitable for analyzing the impacts of experimental setups, human factors, and environmental factors on microstructure characterization. The priori distributions of regression parameters and hyperparameters of the hierarchical model were assumed and the Hamilton Monte Carlo (HMC) algorithm was used to calculate the posterior distributions. Characterizing the nodularity of cast iron was used as an example, and the benchmarking experiments were conducted over a 13-week transition period. The results show that updating a hierarchical model can increase its performance and robustness. The outcome of this study is expected to pave the way for the industrial uptake of ultrasonic microstructure characterization techniques by organizing a gradual transition from destructive sampling inspection to non-destructive one-hundred-percent inspection.

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Ultrasonic measurement model-based non-destructive detection method for curved components using an immersion spherically focused transducer

Lyu

Zhang³

et al. 2021

Nondestructive Testing and Evaluation

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Ultrasonic Benchmarking Study: Overview Up to Year 2005

Cited by 4 publications

References 19 publications

Utsim: Overview and Application

Utsim: Overview and Application

Long-Term Ultrasonic Benchmarking for Microstructure Characterization with Bayesian Updating

Ultrasonic measurement model-based non-destructive detection method for curved components using an immersion spherically focused transducer

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