Reliability assessment of existing structures using results of <scp>nondestructive</scp> testing

Küttenbaum, Stefan; Braml, Thomas; Taffe, Alexander; Keßler, Sylvia; Maack, Stefan

doi:10.1002/suco.202100226

Cited by 17 publications

(18 citation statements)

References 27 publications

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“…Thus, the objectivity is assured in the sense that the calculated results as well as the models, input quantities, and assumptions underlying the measurement uncertainty considerations are deniable." [11]. "A good or rather useful measured data-based probabilistic model should cover the uncertainty associated with information acquisition and processing besides the uncertainty quantifying the inherent natural variability of the considered characteristic.…”

Section: Necessity and Calculation Of Measurement Uncertaintiesmentioning

confidence: 99%

“…A stochastic model that has been created based on observations on site and that does not cover the uncertainty to be attributed to the information acquisition and processing appears to be equally useless as a measurement value to which no measurement uncertainty has been attributed to." [11].…”

Section: Necessity and Calculation Of Measurement Uncertaintiesmentioning

confidence: 99%

“…In other cases where inspection results are incorporated into reliability assessment, a noticeable reduction in numerical reliability may also be observed -certainly in favor of a realistic structural assessment and to support the engineer in making reasonable decisions. Further information about the case-study outlined above can be found in [11]. A second study dealing with ultimate limit states was published in [18,19].…”

Section: Demonstration -Measurement Uncertainty In Structural Reliabi...mentioning

confidence: 99%

“…Individual stochastic models of the basic variables used to analyze SLS decompression with FORM; cf. [11]…”

Section: A Appendix Amentioning

confidence: 99%

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On the treatment of measurement uncertainty in stochastic modeling of basic variables

Küttenbaum

Maack²,

Taffe³

et al. 2022

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The acquisition and appropriate processing of relevant information about the considered system remains a major challenge in assessment of existing structures. Both the values and the validity of computed results such as failure probabilities essentially depend on the quantity and quality of the incorporated knowledge. One source of information are onsite measurements of structural or material characteristics to be modeled as basic variables in reliability assessment. The explicit use of (quantitative) measurement results in assessment requires the quantification of the quality of the measured information, i.e., the uncertainty associated with the information acquisition and processing. This uncertainty can be referred to as measurement uncertainty. Another crucial aspect is to ensure the comparability of the measurement results.This contribution attempts to outline the necessity and the advantages of measurement uncertainty calculations in modeling of measurement data-based random variables to be included in reliability assessment. It is shown, how measured data representing time-invariant characteristics, in this case non-destructively measured inner geometrical dimensions, can be transferred into measurement results that are both comparable and quality-evaluated. The calculations are based on the rules provided in the guide to the expression of uncertainty in measurement (GUM). The GUM-framework is internationally accepted in metrology and can serve as starting point for the appropriate processing of measured data to be used in assessment. In conclusion, the effects of incorporating the non-destructively measured data into reliability analysis are presented using a prestressed concrete bridge as case-study.

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Section: Necessity and Calculation Of Measurement Uncertaintiesmentioning

confidence: 99%

Section: Necessity and Calculation Of Measurement Uncertaintiesmentioning

confidence: 99%

Section: Demonstration -Measurement Uncertainty In Structural Reliabi...mentioning

confidence: 99%

“…Individual stochastic models of the basic variables used to analyze SLS decompression with FORM; cf. [11]…”

Section: A Appendix Amentioning

confidence: 99%

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On the treatment of measurement uncertainty in stochastic modeling of basic variables

Küttenbaum

Maack²,

Taffe³

et al. 2022

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“…The slaband-beam cross-section with its two main girders (see Fig. 4) is broader than 23 m. Further information about the structure and the reassessment are given in [17].…”

Section: Definition Of the Measurandmentioning

confidence: 99%

Approach to the development of a model to quantify the quality of tendon localization in concrete using ultrasound

Küttenbaum

Maack²,

Taffe³

2022

MATEC Web Conf.

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Each engineering decision is based on a number of more or less accurate information. In assessment of existing structures, additional relevant information collected with on-site inspections facilitate better decisions. However, observed data basically represents the physical characteristic of interest with an uncertainty. This uncertainty is a measure of the inspection quality and can be quantified by expressing the measurement uncertainty. The internationally accepted rules for calculating measurement uncertainty are well established and can be applied straightforwardly in many practical cases. Nevertheless, the calculations require the occasionally time-consuming development of an individually suitable measurement model. This contribution attempts to emphasize proposals for modelling the non-destructive depth measurement of tendons in concrete using the ultrasonic echo technique. The proposed model can serve as guideline for the determination of the quality of the measured information in future comparable inspection scenarios.

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Fluidic Ultrasound Generation for Non‐Destructive Testing

Bühling,

Maack,

Strangfeld

2024

Advanced Materials

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Air‐coupled ultrasonic testing (ACU) is a pioneering technique in non‐destructive testing (NDT). While contact testing and fluid immersion testing are standard methods in many applications, the adoption of ACU is progressing slowly, especially in the low ultrasonic frequency range. A main reason for this development is the difficulty of generating high amplitude ultrasonic bursts with equipment that is robust enough to be applied outside a laboratory environment. This paper presents the fluidic ultrasonic transducer as a solution to this challenge. This novel aeroacoustic source uses the flow instability of a sonic jet in a bistable fluidic switch to generate ultrasonic bursts up to 60 kHz with a mean peak pressure of 320 Pa. The robust design allows operation in adverse environments, independent of the operating fluid. Non‐contact through‐transmission experiments are conducted on four materials and compared with the results of conventional transducers. For the first time, it is shown that the novel fluidic ultrasonic transducer provides a suitable acoustic signal for NDT tasks and has potential of furthering the implementation of ACU in industrial applications.This article is protected by copyright. All rights reserved

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Reliability assessment of existing structures using results of nondestructive testing

Cited by 17 publications

References 27 publications

On the treatment of measurement uncertainty in stochastic modeling of basic variables

On the treatment of measurement uncertainty in stochastic modeling of basic variables

Approach to the development of a model to quantify the quality of tendon localization in concrete using ultrasound

Fluidic Ultrasound Generation for Non‐Destructive Testing

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