Damage Imaging in Mesoscale Concrete Modeling Based on the Ultrasonic Time-Reversal Technique

Feng, Kan; Zhao, Qian; Ya-ping, Qiu

doi:10.1007/s10338-019-00153-z

Cited by 15 publications

(3 citation statements)

References 21 publications

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“…Significant research efforts have been invested in developing accurate detection methods of defects within the connection using nondestructive testing (NDT) [39][40][41][42][43][44]. Feng et al [45] proposed a time-reversal ultrasonic waves signal analysis to detect the change in the grout compactness in the sleeve. His method efficiently detected the location of the defects.…”

Section: Introductionmentioning

confidence: 99%

Experimental and numerical assessment of the location-based impact of grouting defects on the tensile performance of the fully grouted sleeve connection

Kahama

Xie

Lü

et al. 2022

Frattura Ed Integrità Strutturale

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The presence of grouting defects emanating from construction operations constitutes a major threat to the structural integrity of the grouted sleeve connection of precast concrete members. This work presents a location-based assessment of the impact of grouting defects on the tensile performance of the grouted sleeve connection. Twenty-two specimens with different configurations of defects were subjected to a uniaxial tensile experiment. Corresponding numerical models were proposed, validated and used to conduct a sensitivity analysis of the connection to the defect's location while considering different design confinements of grouting materials. Experimental and numerical studies revealed the following outcome: In consideration of confinement parameters, when the defect of size 3d is located in the mid-span anchorage length, the variation of the sleeve-to-bar diameter (ds/d) from 2.66 (lower design limit) to 3.55 (upper design limit) changed the drop in the ultimate capacity from 19% to 44% below the connection's design requirement. The governing parameters of the grout-bar bond stiffness were the defect's location and degree of confinement. This work proposes a theoretical diagnosis model and a risk assessment catalogue as a promising step toward establishing a computerized diagnosis model of the defective connection to enlighten rational maintenance actions in actual construction.

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Section: Introductionmentioning

confidence: 99%

Experimental and numerical assessment of the location-based impact of grouting defects on the tensile performance of the fully grouted sleeve connection

Kahama

Xie

Lü

et al. 2022

Frattura Ed Integrità Strutturale

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show abstract

“…The development of the sound propagation time as a function of loading cycles and unloading cycles was demonstrated on a reinforced concrete structure. Feng, Zhao and Qiu show in [5] how damage imaging in mesoscale concrete can be performed by using the time-reversal method (TRM) combined with wavelet analysis. Casrellano et al show in [6] the differences between linear and nonlinear ultrasonic techniques for detecting and monitoring damages in concrete.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Deterioration State of Post-Installed Bonded Anchors Using Ultrasonic

et al. 2021

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The assessment of already installed anchorages for a possible exceeding of the service load level is a question that is gaining more and more importance, especially in building maintenance. Bonded anchors are of particular interest here, as the detection of a capacity reduction or load exceedance can cause damage to the concrete-bonded mortar behavior. This article investigates the extent to which ultrasonic methods can be used to make a prediction about the condition of anchorages in concrete and about their load history. A promising innovative assessment method has been developed. The challenges in carrying out the experimental investigations are the arrangement of the transducers, the design of the test set-up and the applicability of direct, indirect or semidirect ultrasonic transmission. The experimental investigations carried out on a test concrete mix and a bonded anchor system show that damage to the concrete structure can be detected by means of ultrasound. The results indicate the formation of cracks and therefore a weakening of the response determined by means of direct, indirect and semidirect ultrasonic transmission. However, for application under non-laboratory conditions and on anchors with unknown load history, the calibration with a reference anchor and the identification of the maximum load is required. This enables a referencing of the other loaded anchors to the unloaded conditions and allows an estimation of the load history of individual anchors.

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“…Conveniently and effectively detecting the fullness of sleeve grouting has always been a difficult problem in prefabricated concrete buildings. The ultrasonic wave method (Feng et al, 2020), the impact-echo method (Chou, 2019), the X-ray CT method (Zelelew et al, 2013;Gao et al, 2017), the damped vibration method (Zhu et al, 2018), the X-ray method (du Plessis and Boshoff, 2019), and the embedded wire-drawing method (Gao et al, 2019) are relatively mature detection technologies, but they are expensive and labor intensive, which means they are not conducive to the full detection of sleeve grouting. Because such defects are typically local, traditional global-based non-destructive dynamic testing methods also face great challenges when used with complex structures, because these technologies are unable to obtain effective local feature information from global dynamical data (Yoon et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Identification of Grout Sleeve Joint Defect in Prefabricated Structures Using Deep Learning

et al. 2020

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A grout sleeve connection is a typical kind of joint in prefabricated structures. However, for construction and manufacturing reasons, defects in this kind of joint are usually inevitable. The joint quality of a prefabricated structure has a significant influence on its overall performance and can lead to structural failure. Due to the complexity of various types of materials used in grout sleeve connections, traditional non-destructive testing methods, such as Acoustic Emission (AE), Ultrasonic Testing (UT), Guided Wave Testing (GW), are facing great challenges. The recent development of deep learning technology provides a new opportunity to solve this problem. Deep learning can learn the inherent rules and abstract hierarchies of sample data, and it has a powerful ability to extract the intrinsic features of training data in complex classification tasks. This paper illustrates a deep learning framework for the identification of joint defects in prefabricated structures. In this method, defect features are extracted from the acceleration time history response of a prefabricated structure using a convolutional neural network. The proposed method is validated by vibration experiments on a half-scaled, two-floor prefabricated frame structure with column rebars spliced by different defective grout sleeves.

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Damage Imaging in Mesoscale Concrete Modeling Based on the Ultrasonic Time-Reversal Technique

Cited by 15 publications

References 21 publications

Experimental and numerical assessment of the location-based impact of grouting defects on the tensile performance of the fully grouted sleeve connection

Experimental and numerical assessment of the location-based impact of grouting defects on the tensile performance of the fully grouted sleeve connection

Assessment of the Deterioration State of Post-Installed Bonded Anchors Using Ultrasonic

Identification of Grout Sleeve Joint Defect in Prefabricated Structures Using Deep Learning

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