Identification of fracture damage characteristics in ultra-high performance cement-based composite using digital image correlation and acoustic emission techniques

Chen, Chen; Chen, Xudong; Ning, Yingjie

doi:10.1016/j.compstruct.2022.115612

Cited by 20 publications

(5 citation statements)

References 44 publications

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“…The contribution rate of each component from high to low is shown in Table 3. From the component with the highest contribution rate, several principal components with a cumulative contribution rate greater than 90 % (most often chosen) [16][17] were finally selected for classification: spectrum gravity, peak frequency, energy, and count. According to the new data obtained from PCA, the simplest unsupervised learning algorithm, K-means, was applied for clustering the signals.…”

Section: Clustering By Unsupervised Learningmentioning

confidence: 99%

Hydrogen induced cracks monitored with acoustic emission under the laboratory condition

Liu¹,

Han²,

Wang³

et al. 2023

eJNDT

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Hydrogen induced cracking (HIC) is a common form of failure in steel exposed to hydrogen rich environments, which always occurs inside material making their detection difficult. Acoustic Emission (AE) is a promising Nondestructive Evaluation technique for crack detection. However, it is challenging to distinguish the signals generated from HIC, corrosions and bubbles. In this study, these mixed AE signals were obtained by electrochemical hydrogen charging on A516 carbon steel with the solution of 0.5 mol/L H2SO4 and 0.5 g/L NaAsO2. Microstructures of the sample’s cross-section were observed to verify the existence of HIC. moreover, separate signals of bubbles and corrosions were acquired from just exposures to 0.5 mol/L H2SO4. After analyzing, key parameters from the AE signals, i.e. the peak frequency, the spectrum gravity, the duration and energy, were identified to differentiate the source mechanisms. Results show that the peak frequency and the spectrum gravity of corrosion signals are higher than those of HIC and bubbles, while the duration and energy of HIC signals are higher than those of the other two kinds of signals. To reduce manual operations, the unsupervised learning algorithms, Principal Components Analysis (PCA) and K-means, were used for clustering, for further understanding of these clusters and their evolution with time.

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Section: Clustering By Unsupervised Learningmentioning

confidence: 99%

Hydrogen induced cracks monitored with acoustic emission under the laboratory condition

Liu¹,

Han²,

Wang³

et al. 2023

eJNDT

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“…Therefore, the calculation of its crack initiation toughness consists of two parts. The first part, the cracking fracture toughness caused by the vertical load P ini , can still be determined by using Equation (1). The second part, the crack initiation toughness caused by the crack resistance of FRP, is the core of calculating the crack initiation toughness of concrete beams under the action of FRP, which can be calculated by the following method.…”

Section: Crack Initiation Toughnessmentioning

confidence: 99%

“…The mechanical properties of concrete have been extensively studied as an important engineering material. However, numerous studies on the mechanical properties of concrete have focused on static conditions, [1][2][3][4] and most of the hydraulic structures in practical engineering are subjected to dynamic loads such as dynamic water pressure, wave impact from marine platforms, and earthquake and tsunami, 5,6 which can cause great damage to the hydraulic structures, especially the seismic effects. Therefore, these damaged concrete structures need to be reinforced, or else they will be left to develop at a later stage with costly remediation.…”

mentioning

confidence: 99%

Effect of different loading rates on the fracture behavior of FRP‐reinforced concrete

Liu,

Fan,

Wang

et al. 2023

Fatigue Fract Eng Mat Struct

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In order to study the effect of different loading rates on the fracture behavior of fiber‐reinforced polymer (FRP) reinforced concrete, the fracture experiments of FRP‐reinforced concrete beams under different loading rates were carried out. The calculation method of fracture toughness was given by analytic deduction, and the effects of different loading rates on the fracture parameters were analyzed. The experimental results show that there are three critical points in the fracture process of FRP‐reinforced concrete beam, which are the crack initiation load, crack resistance load, and ultimate load points. The effective crack length at the crack resistance load point increases with the increase of loading rate, and the effective crack length at the ultimate load point does not vary as the loading rate. With the increase of loading rate, the elastic modulus and fracture toughness increase gradually, and there is a logarithmic relationship with the loading rate, which has obvious rate correlation. The fracture process zone (FPZ) length of FRP‐reinforced concrete beams gradually decreases with the increase of loading rate.

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“…It is possible to consider recombining multiple AE feature parameters to identify the damage mode of the material while preserving information in dimensionality reduction. Various clustering methods have been developed, such as the k-Means method [16,24,26], Fuzzy C-Means [20,27], and Self-Organizing Map [28]. Different clustering methods are suitable for different classification scenarios; k-Means is suitable for simple classification.…”

Section: Introductionmentioning

confidence: 99%

A Study on Damage of T800 Carbon Fiber/Epoxy Composites under In-Plane Shear Using Acoustic Emission and Digital Image Correlation

Lin,

Shi,

Huang

et al. 2023

Polymers

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In addition to measuring the strain, stress, and Young’s modulus of materials through tension and compression, in-plane shear modulus measurement is also an important part of parameter testing of composites. Tensile testing of ±45° composite laminates is an economical and effective method for measuring in-plane shear strength. In this paper, the in-plane shear modulus of T800 carbon fiber/epoxy composites were measured through tensile tests of ±45° composite laminates, and acoustic emission (AE) was used to characterize the damage of laminates under in-plane shear loading. Factor analysis (FA) on acoustic emission parameters was performed and the reconstructed factor scores were clustered to obtain three damage patterns. Finally, the development and evolution of the three damage patterns were characterized based on the cumulative hits of acoustic emission. The maximum bearing capacity of the laminated plate is about 17.54 kN, and the average in-plane shear modulus is 5.42 GPa. The damage modes of laminates under in-plane shear behavior were divided into three types: matrix cracking, delamination and fiber/matrix interface debonding, and fiber fracture. The characteristic parameter analysis of AE showed that the damage energy under in-plane shear is relatively low, mostly below 2000 mV × ms, and the frequency is dispersed between 150–350 kHz.

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Identification of fracture damage characteristics in ultra-high performance cement-based composite using digital image correlation and acoustic emission techniques

Cited by 20 publications

References 44 publications

Hydrogen induced cracks monitored with acoustic emission under the laboratory condition

Hydrogen induced cracks monitored with acoustic emission under the laboratory condition

Effect of different loading rates on the fracture behavior of FRP‐reinforced concrete

A Study on Damage of T800 Carbon Fiber/Epoxy Composites under In-Plane Shear Using Acoustic Emission and Digital Image Correlation

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