Transfer function approach based on simulation results for the determination of pod curves

Demeyer, Séverine; Jenson, F.; Domínguez, N.; Яковлева, Екатерина

doi:10.1063/1.4716424

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…It's noted that this applies to procedures in which the influence of human factors is primarily on the interpretation of acquired data. Demeyer et al (2012) apply the XFM approach to estimate the POD for fatigue cracks in aluminum plates based on an empirically derived POD for fatigue cracks in titanium plates. CIVA is used to generate NDE response data for notches in both aluminum and titanium plates.…”

Section: Non-bayesian Demonstrationsmentioning

confidence: 99%

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Review of Literature for Model Assisted Probability of Detection

Meyer

Crawford

Lareau

et al. 2014

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This report documents a literature survey of so-called "Model Assisted Probability of Detection" (MAPOD) approaches that may be useful in determining the probability of detection (POD), a metric for quantifying the performance of nondestructive evaluation (NDE) methods. The objective of this report is to summarize MAPOD concepts that have been proposed to date in order to assess specific approaches that may be appropriate for application to improve estimates of POD for field NDE of nuclear power plant components. The limitations of laboratory-based studies to replicate actual field conditions are well-recognized and not limited to the nuclear power industry. Probability of detection estimates based on laboratory studies generally provide ideal environments for performing examinations as compared field settings, which typically will result in non-conservative estimates of POD for field applications. As a consequence of this effort, the authors conclude that use of MAPOD concepts to improve estimates of field NDE performance may require access to certain field data, or alternatively, may require significant laboratory studies to assess the influence of human and environmental shaping factors. If the necessary field data cannot be made available, it is proposed that laboratory efforts will have greater chance of success by focusing on a specific examination technique and component application. The authors also find that MAPOD concepts may have a more immediate contribution to the nuclear power industry through their use in extending personnel and procedure qualifications beyond established limits. Finally, another basis was identified that may be used to adjust POD curves generated in previous reliability studies and performance demonstrations. Many of the previous studies calculated POD as the average of performance data which may be inappropriate for many applications, as the calculation may be nonconservative. A more conservative approach to estimating POD would include basing the calculation on a lower statistical quantile of the data set. v

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Section: Non-bayesian Demonstrationsmentioning

confidence: 99%

“…There can be variations of the â vs. a models to represent different relationships between the response and flaw size. For instance,Demeyer et al (2012) consider an extension of â vs. a models to accommodate piecewise linear relationships between ln â and ln a,…”

mentioning

confidence: 99%

Review of Literature for Model Assisted Probability of Detection

Meyer

Crawford

Lareau

et al. 2014

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“…Then, a physics-based model of the inspection process is employed so the POD curves can be transferred to a similar inspection process on a different component or material. Applications of this method are documented by Harding et al 16 and Demeyer et al, 17 who applied the approach for ultrasonic fatigue crack detection in airplane wings and aluminum plates.…”

Section: Introductionmentioning

confidence: 99%

Predictive probability of detection curves based on data from undamaged structures

Mendler,

Döhler,

Grosse

2023

Structural Health Monitoring

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This paper develops a model-assisted approach for determining predictive probability of detection curves. The approach is “model-assisted,” as the damage-sensitive features are evaluated in combination with a numerical model of the examined structure. It is “predictive” in the sense that probability of detection (POD) curves can be constructed based on measurement records from the undamaged structure, avoiding any destructive tests. The approach can be applied to a wide range of damage-sensitive features in structural health monitoring and non-destructive testing, provided the statistical distribution of the features can be approximated by a normal distribution. In particular, it is suitable for global vibration-based features, such as modal parameters, and evaluates changes in local structural components, for example, changes in material properties, cross-sectional values, prestressing forces, and support conditions. The approach explicitly considers the statistical uncertainties of the features due to measurement noise, unknown excitation, or other noise sources. Moreover, through confidence intervals, it considers model-based uncertainties due to uncertain structural parameters and a possible mismatch between the modeled and the real structure. Experimental studies based on a laboratory beam structure demonstrate that the approach can predict the POD before damage occurs. Ultimately, several ways to utilize predictive POD curves are discussed, for example, for the evaluation of the most suitable measurement equipment, for quality control, for feature selection, or sensor placement optimization.

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