Application of ultrasonic models for investigating the properties of the interface between roller compacted concrete (RCC) layers

Ashkar, M; Toufigh, Vahab; Ghaemian, Mohsen; Azizmohammadi, Morteza

doi:10.1016/j.ndteint.2021.102516

Cited by 12 publications

(4 citation statements)

References 20 publications

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“…According to this figure, the β ′ variation with the fundamental frequency of 100 kHz is less than 250 kHz, indicating that high-frequency excitation is more reliable for finding the defects. Similarly, Ashkar et al 19 investigated the effect of frequency on distinguishing nonlinearity in roller compacted concrete (RCC). They found that more nonlinear behavior can be detected in composite materials by increasing excitation frequency.…”

Section: Resultsmentioning

confidence: 99%

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Ultrasonic evaluation for the detection of contact defects of the timber and fiber-reinforced polymer

Kami

Toufigh

2022

Structural Health Monitoring

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Fiber-reinforced polymer (FRP) composites have been used tremendously to repair and rehabilitate timber structures due to their formability, ease of use, and high specific strength. The bond quality between FRP and timber substrate is critical for complete composite action. In this paper, a comprehensive set of linear and nonlinear ultrasonic methods was performed to investigate the bond between carbon-FRP (CFRP) and timber. For this purpose, 126 specimens of reinforced timber were prepared. Two techniques were considered to bond CFRP and timber: (1) externally bonded reinforcement (EBR), and (2) externally bonded reinforcement on the groove (EBROG). The effect of the number of CFRP layers, adhesive types, the extent of artificial surface defects, and the depth of the groove were contemplated. By analyzing linear methods, differences in stiffness and modulus of elasticity of CFRP and timber led to velocity variation and attenuation phenomena. Higher-order harmonics were also used to investigate the nonlinear behavior of ultrasonic waves at the bond. The second harmonic generation detected surface damage at CFRP and timber bond. Single-lap shear tests were employed to determine the bond strength of CFRP and timber and evaluate the accuracy of the linear and nonlinear methods. Finally, using the linear and nonlinear features extracted from the ultrasonic response signals and available physical parameters, three artificial neural networks (ANNs) were developed to predict three important CFRP-to-timber bond characteristics quantitively: (1) to predict the groove depth, (2) to predict the volume of voids, and (3) to predict the CFRP-to-timber bond strength. The three proposed models achieved an average [Formula: see text] of 0.95, 0.96, and 0.92 in predicting the groove depth, voids volume, and bond strength, respectively.

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Section: Resultsmentioning

confidence: 99%

“…The maximum amplitude decreases at the fundamental frequency and is transmitted to higher harmonics. 19 Therefore, damage can be assessed by nonlinear analysis of ultrasonic tests. Ng et al 20 studied the higher harmonic generation of Rayleigh waves by passing them through the interface between FRP and concrete.…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic evaluation for the detection of contact defects of the timber and fiber-reinforced polymer

Kami

Toufigh

2022

Structural Health Monitoring

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“…Among these features, ultrasonic pulse velocity (UPV) has been successfully implemented for many ND applications. 9–11 However, it has been widely reported that UPV demonstrates low sensitivity to damage in concrete. 12 Other linear features, such as the attenuation of the time-domain signal’s amplitude 13 and the attenuation of the fundamental amplitude in the frequency domain, 14 have been shown to be sensitive to damage.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised deep learning framework for ultrasonic-based distributed damage detection in concrete: integration of a deep auto-encoder and Isolation Forest for anomaly detection

Toufigh

Ranjbar

2023

Structural Health Monitoring

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This study presented an unsupervised anomaly detection-based framework for distributed damage detection in concrete using ultrasonic response signals. A deep fully connected auto-encoder was employed to reconstruct the ultrasonic response signals. This model was trained on the intact specimen’s responses. The auto-encoder demonstrated a relatively high prediction error encountering the damaged specimen’s responses. Two time-domain features (mean squared error and reconstructed-to-original signal ratio) and one frequency-domain feature (fundamental amplitude ratio) were defined to measure the reconstruction error of the auto-encoder (the damage-sensitive features). Finally, the Isolation Forest algorithm was implemented for anomaly (damage) detection. The beauty of this framework is that it requires a few numbers of data only from the intact specimen for training the auto-encoder and collecting the binary decision trees of the Isolation Forest. The framework was successfully implemented for damage detection in five geopolymer concrete specimens with different mix proportions. Using all three introduced damage-sensitive features, the framework demonstrated an average prediction accuracy of 95.0% and 93.0% for damaged and intact stages, respectively.

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“…The hydration degrees vary with different water cement ratios and curing temperatures. Ashkar et al 21 and Zhang et al 22 used ultrasonic to detect the internal structure of concrete and predict the strength of concrete. Using NMR and ultrasonic testing technology to detect the internal pores and damage of concrete is an effective means and is a method to analyze the mesoscopic mechanism of concrete.…”

Section: Introductionmentioning

confidence: 99%

Triaxial tests on high ductile concrete under different environmental conditions

Shi

Yan

Kou

2022

Structural Concrete

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Triaxial compression tests were conducted on high ductile concrete (HDC) under three curing conditions to study its triaxial mechanical properties under different curing environments. The three different curing conditions are as follows: standard curing (temperature 20 ± 2°C, humidity ≥95%), water curing (temperature 15 ± 2°C, humidity ≥95%), and −20°C (−20 ± 2°C, humidity ≥85%). The variation laws of stress–strain response, peak stress, peak strain, and volume strain were analyzed for HDC under different environmental conditions. The mechanism of the effect of HDC mesostructure on strength under different curing conditions was revealed using ultrasonic and nuclear magnetic resonance detection technology. The relationship between HDC uniaxial compressive strength and ultrasonic speed was obtained by fitting the test data, and the relationship between the shear strength and temperature was provided. Results show that the peak stress of HDC under the same confining pressure increases with the rise in the curing temperature. The peak strain also decreases, and the HDC exhibits better ductility under −20°C curing. The peak stress and peak strain of HDC under the same curing conditions increase with the rise in confining pressure. HDC specimen fracture is in the composite failure mode of shear and splitting, and it cracks but does not disintegrate. The pore size is larger and the strength is lower when the pores are more harmful.

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Application of ultrasonic models for investigating the properties of the interface between roller compacted concrete (RCC) layers

Cited by 12 publications

References 20 publications

Ultrasonic evaluation for the detection of contact defects of the timber and fiber-reinforced polymer

Ultrasonic evaluation for the detection of contact defects of the timber and fiber-reinforced polymer

Unsupervised deep learning framework for ultrasonic-based distributed damage detection in concrete: integration of a deep auto-encoder and Isolation Forest for anomaly detection

Triaxial tests on high ductile concrete under different environmental conditions

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