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NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis
Non-destructive Testing (NDT) provides valuable data about structural elements, supporting the assessment of existing infrastructures without incurring additional structural damage from inspections. Simultaneously, the uncertainty in measurement, which quantifies the quality of measurement results, plays a crucial role in decisions aimed at, e.g., optimizing maintenance strategies, rehabilitation works and Structural Health Monitoring (SHM) implementations. The Guide to the Expression of Uncertainty in Measurement (GUM) framework has already been considered for non-destructive concrete testing. Regarding that, extensive measurements with sophisticated scopes need to be conducted by experts as an obligatory process. This study illustrates how NDT results describing the inner structure of a concrete element can effectively support the reassessment of bridges in operation. To achieve this, the study considers the various measurable positions of the resisting longitudinal tendons of a bridge structure to investigate the displacement change under dynamic service loads. Furthermore, this study aims to simplify and optimize existing NDT data analysis procedures by employing regression analysis, enabling the detection of structural features. This regression analysis yields a modifier for determining the correct depth of an object within the structural element. The method is validated through laboratory experiments, including the use of an ultrasonic measurement system. As a result, it provides unbiased and accurately measured results, while ensuring that the measurement data can remain uncorrelated. Major advantages include efficient computation, a wider scope, and avoiding redundant information about the measuring process. The findings demonstrate that employing the proposed NDT analysis method, with its enhanced practicability, can significantly augment the efficiency of NDT data-supported structural reassessments across various scenarios.
NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis
Non-destructive Testing (NDT) provides valuable data about structural elements, supporting the assessment of existing infrastructures without incurring additional structural damage from inspections. Simultaneously, the uncertainty in measurement, which quantifies the quality of measurement results, plays a crucial role in decisions aimed at, e.g., optimizing maintenance strategies, rehabilitation works and Structural Health Monitoring (SHM) implementations. The Guide to the Expression of Uncertainty in Measurement (GUM) framework has already been considered for non-destructive concrete testing. Regarding that, extensive measurements with sophisticated scopes need to be conducted by experts as an obligatory process. This study illustrates how NDT results describing the inner structure of a concrete element can effectively support the reassessment of bridges in operation. To achieve this, the study considers the various measurable positions of the resisting longitudinal tendons of a bridge structure to investigate the displacement change under dynamic service loads. Furthermore, this study aims to simplify and optimize existing NDT data analysis procedures by employing regression analysis, enabling the detection of structural features. This regression analysis yields a modifier for determining the correct depth of an object within the structural element. The method is validated through laboratory experiments, including the use of an ultrasonic measurement system. As a result, it provides unbiased and accurately measured results, while ensuring that the measurement data can remain uncorrelated. Major advantages include efficient computation, a wider scope, and avoiding redundant information about the measuring process. The findings demonstrate that employing the proposed NDT analysis method, with its enhanced practicability, can significantly augment the efficiency of NDT data-supported structural reassessments across various scenarios.
NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis
Bahrami Eskandari, Ardalan (Autor:in) / Küttenbaum, Stefan (Autor:in)
01.01.2024
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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