Crack Damage Research Articles

Study on the mechanical properties and microstructure of recycled concrete reinforced with basalt fibers and nano-silica in early low-temperature environments

Abstract The effects of basalt fibers (BF) and nano-silica (NS) on the mechanical properties and microstructure of recycled concrete (RC) in early low-temperature environments were investigated by placing the BF and NS modified RC specimens in the environments of −20, −10, 0, and 25°C for curing for 6 h, followed by standardized maintenance. The damage morphology and mechanical properties of modified RC were analyzed in such environments. The formulae for the compressive strength of RC, which was affected by BF and NS, were fitted using statistical product and service solutions, and a micromorphological analysis of the modified RC was conducted using scanning electron microscope. The mechanical properties of RC decreased owing to the influence of early low temperatures, among which 0°C caused the largest damage crack and the most serious effects. In the early low-temperature environments, the physical properties of RC generally increased and then decreased with the increase in BF dosage; however, increasing NS dosages improved its mechanical properties. The composite doping of BF and NS was more obvious than the single doping of BF or NS to enhance the performance of RC, and the internal pore structure was considerably improved. The preferred doping amounts were 3 kg m−3 of BF and 2% NS.

Quantitative Analysis and 3D Visualization of Crack Behavior in 3D-Printed Rock-Like Specimens with Single Flaw Using In-Situ Micro-CT Imaging

3D printing technology allows for precise control of preparing complex geometries and internal defects in printed rock analogs, while in-situ Micro-CT imaging enables real-time observation of crack behavior. The combination of these technologies offers a new research approach for studying rock crack behavior. In this study, 3D-printed rock-like specimens containing a pre-existing flaw were prepared using a gypsum powder-based 3D printer. An advanced in-situ Micro-CT system equipped with a loading device was used to quantitatively and visually investigate the crack behavior in 3D-printed specimens under uniaxial compression testing. 2D CT images obtained from in-situ compression testing at different deformations could be used to reconstruct a 3D model and visually identify the crack patterns of the extracted cracks in 3D-printed specimens. The initiation angle of cracks, volume of the pre-existing flaw, volume of newly formed cracks, and damage value with respect to strains were analyzed to quantitatively investigate crack behavior. The results indicated that within the 3D-printed specimens, tensile cracks were first initiated near the internal flaw, followed by the occurrence of shear cracks or tensile-shear mixed cracks at the flaw tips. Additionally, there was a negative linear correlation between the initiation angle of newly formed cracks and the initial flaw angle. For flaw angles in the range of 0° ≤ α ≤ 45°, a higher number of newly formed cracks were observed in the 3D-printed specimens, and the rates of increase in crack volume and damage values with strain were faster. However, for flaw angles in the range of 45° < α ≤ 90°, the results showed the opposite trend. Furthermore, through comparison with the crack behavior of natural rocks containing a single flaw, it was found that the failure modes and crack behavior of the 3D-printed specimens exhibit certain similarities with natural rocks.

A New Rock Brittleness Index Based on Crack Initiation and Crack Damage Stress Thresholds

A New Rock Brittleness Index Based on Crack Initiation and Crack Damage Stress Thresholds

Recycling of copper tailing as filler material in asphalt paving mastic: A sustainable solution for mining waste recovery

Copper tailings are a category of solid waste discharged after the beneficiation process in mining plants. The significant concern raising stringent environmental issues give impetus to explore the multi-channel utilization of copper tailings in a sustainable manner. Concerning the fact that no study has systematically compared properties of copper tailings filled (CTP) asphalt mastic with conventional limestone filler mastic (LP) at different filler-to-asphalt ratios, multiscale and multi-dimensional comparisons between the characteristics of CTP-asphalt and LP-asphalt mastics were made in this study to thoroughly explore the feasibility and potential of recycling CTP as alternative filler in asphalt materials. Four ratios from 0.3 to 1.2 were used to manufacture asphalt mastics. The in-service pavement performance of asphalt mastics including resistances to rutting, low-temperature cracking and moisture damage was explored. Finally, the environmental and economic perspectives regarding the recycling of copper tailings are analyzed. Results indicate that CTP possesses a rougher surface, a larger specific surface area, and a more uniform pore size distribution than LP, particularly across the mesopores range. These characteristics could promote the adsorption of asphalt on its particle surface, potentially leading to enhanced filler-particle interaction. Regarding pavement performance, CTP-asphalt mastic outperforms LP-asphalt mastic in terms of high-temperature performance. Meanwhile, its low-temperature performance and moisture stability are only limitedly declined with the acceptable performance. Further, heavy metals leaching tests suggest that the risk for the substantial utilization of CTP in paving asphalt is absent. The related outcomes have verified the promising potential of CTP as an alternative candidate to substitute the conventional filler in paving asphalt from comprehensive consideration of in-service performance, and environmental and economic benefits.

CNN-Transformer hybrid network for concrete dam crack patrol inspection

Regular patrol inspection of concrete dams can detect cracks at an early stage. However, conventional crack segmentation models based on deep learning (DL) are difficult to be deployed in resource-constrained mobile devices due to the large number of parameters. This paper describes a lightweight semantic segmentation model, termed as CrackTrNet, for images of concrete dam cracks. CrackTrNet is a hybrid U-shaped model based on convolutional neural network (CNN) and Vision Transformer. The CNN is adopted to extract low-level visual features and the Transformer focuses on learning the global contextual information. The results demonstrate that its segmentation accuracy can reach 97.60%, while the model size is only 34.86 MB, which is 66.12%–87.85% lower than that of current mainstream DL-based models. To make the model more practical, a crack inspection mobile application (APP) is developed using Android Studio. The integration of lightweight CrackTrNet and APP can effectively assist the intelligent inspection of dam cracks to ensure structural safety.

Underwater dam crack image generation based on unsupervised image-to-image translation

Underwater crack detection is necessary for the safe operation of concrete dams. Current deep-learning-based underwater crack detection methods rely heavily on a large number of crack images; these images are difficult to collect because of complex and dangerous underwater environments. This study proposes a method that can generate underwater dam crack images using above-water dam crack images through an image-to-image translation method. CycleGAN, which is more powerful than other models, was optimized to generate underwater dam crack images by translating existing above-water dam crack images into underwater styles. The generated underwater images were validated using the following major computer vision tasks: classification, object detection, and semantic segmentation. The results demonstrate the potential of these generated images for training and optimizing deep-learning-based crack-detection methods. This method is expected to solve the problem of insufficient data and enhance deep-learning-based detection networks.

Delamination and crack detection and localization of a laminated composite plate structure using regression and regression-based neural network methods

Despite significant progress, a comprehensive analysis of Machine learning algorithms for detecting delamination and crack damage in composite laminate plates is noticeably absent in the literature. This study aims to bridge this gap by meticulously help spectrum of six regression algorithms. By utilizing simulated displacement-time responses from a 16-layer laminated composite plate structure subjected to a random force, a robust dataset is constructed to evaluate the efficacy of these machine learning paradigms. Performance assessments rely on critical metrics: coefficient of determination (R2), mean absolute error (MAE), root mean squared error (RMSE), and mean absolute percentage error (MAPE).

Interface cracking damage of W/Cu monoblocks as divertor target after high-cyclic plasma discharges in EAST

W/Cu monoblocks will be employed in ITER as divertor targets for high heat loads. Experimental results of W/Cu monoblocks in high heat flux (HHF) tests have demonstrated their endurance on 5000 cycles at 10 MW/m2 and occasionally 300 cycles at 20 MW/m2. However, plasma-facing units (PFUs) serve in a harsh and complex environment in tokamaks and whether W/Cu monoblocks can show the same excellent properties in tokamaks needs to be further tested. Experimentally evaluating the evolution of ITER-like PFUs is one of the main missions for the EAST tokamak. The ITER-like actively cooled W/Cu monoblocks installed in the EAST lower divertor in 2021 exhibited abnormal behavior after 13,346 plasma discharges. The abnormal temperature evolution of the component was observed via infrared cameras (IR). Subsequent non-destructive testing (NDT) indicated that it might primarily arise from interface damage and scanning electron microscopy (SEM) confirmed that there were obvious cracks at the interface. The cracking center was also found above the interface. Simulation of the structural characteristics of W/Cu monoblocks under heat load in EAST can obtain temperature distribution and stress–strain distribution, which can be used to analyze the causes of material interface cracks. These findings unveil the phenomenon and mechanism of interface damage in W/Cu monoblocks after enduring over 10,000 plasma discharges in EAST, providing valuable insights for the future long-term application of W/Cu monoblocks in ITER and fusion reactors.

Crack propagation and damage evolution of metallic cylindrical shells under internal explosive loading

This paper investigates the three-dimensional crack propagation and damage evolution process of metallic column shells under internal explosive loading. The calibration of four typical failure parameters for 40CrMnSiB steel was conducted through experiments and subsequently applied to simulations. The numerical simulation results employing the four failure criteria were compared with the differences and similarities observed in freeze-recovery tests and ultra-high-speed tests. This analysis addressed the critical issue of determining failure criteria for the fracture of a metal shell under internal explosive loads. Building upon this foundation, the damage parameter Dc, linked to the cumulative crack density, was defined based on the evolution characteristics of a substantial number of cracks. The relationship between the damage parameter and crack velocity over time was established, and the influence of the internal central pressure on the damage parameter and crack velocity was investigated. Variations in the fracture modes were found under different failure criteria, with the principal strain failure criterion proving to be the most effective for simulating 3D crack propagation in a pure shear fracture mode. Through statistical analysis of the shell penetration fracture radius data, it was determined that the fracture radius remained essentially constant during the crack evolution process and could be considered a constant. The propagation velocity of axial cracks ranged between 5300 m/s and 12600 m/s, surpassing the Rayleigh wave velocity of the shell material and decreasing linearly with time. The increase in shell damage exhibited an initial rapid phase, followed by deceleration, demonstrating accelerated damage during the propagation stage of the blast wave and decelerated damage after the arrival of the rarefaction wave. This study provides an effective approach for investigating crack propagation and damage evolution. The derived crack propagation and damage evolution law serves as a valuable reference for the development of crack velocity theory and the construction of shell damage evolution modes.

Deep learning-based three-dimensional crack damage detection method using point clouds without color information

Automated high-precision crack detection on building structures under poor lighting conditions poses a significant challenge for traditional image-based methods. Overcoming this challenge is crucial to enhance the practical applicability of structural health monitoring and rapid damage assessment, especially in post-disaster scenarios like earthquakes. To address this challenge, this paper presents a deep learning-based three-dimensional crack detection method that utilizes light detection and ranging (LiDAR) point cloud data. Our method is specifically designed to address crack detection without relying on color information input, resulting in high-precision and robust apparent damage detection. The key contribution of this paper is the NL-3DCrack model, which enables automated three-dimensional crack semantic segmentation. This model comprises a feature embedding module, an incomplete neighbor feature extraction module, a decoder, and morphological filtering. Notably, we introduce an innovative incomplete neighbor mechanism to effectively mitigate the impact of outliers. To validate the effectiveness of our proposed method, we establish two three-dimensional crack detection datasets, namely the Luding dataset and the terrestrial laser scanner dataset, which are based on earthquake disasters. Experimental results demonstrate that our method achieves remarkable performance, with an intersection-over-union of 39.62% and 51.33% on the respective test sets, surpassing existing point cloud-based semantic segmentation models. Ablation experiments further confirm the effectiveness of our approach. In summary, our method showcases exceptional crack detection performance on LiDAR data using only XYZI channels. With its high precision and reliable results, it offers significant utility in real-world applications, contributing to improved structural health monitoring and rapid damage assessment after disasters, particularly in post-earthquake scenarios.

Numerical simulation of rock blasting under different in-situ stresses and joint conditions.

High primary rock stress can limit the generation of rock cracks caused by blasting, and blasting usually shows different rock breaking states under different primary rock stress conditions. There are a large number of naturally formed joints in rock mass, due to the limitations of laboratory tests, a numerical model of jointed rock mass was established using LS-DYNA software to investigate the evolution of blasting damage under various in-situ stresses and open joints. In this simulation, using the Lagrange-Euler (ALE) procedure and the equation of state (JWL) that defines explosive materials, the study considered different joint thicknesses (2cm, 4cm, and 6cm), joint angles (0°, 30°, 60°, and 90°), and in-situ stress conditions (lateral stress coefficients of 0.5, 1, and 2, with vertical in-situ stresses of 10MPa and 20MPa), through stress analysis and damage area comparison, the relationship between damage crack propagation and horizontal and vertical stress difference is explored. The research aimed to understand the mechanisms underlying crack initiation and propagation. The results show that: (1) The presence of joints exerts a barrier effect on the expansion and penetration of cracks. When explosion stress waves reach the joint surface, their propagation is impeded, leading to the diffusion of wing cracks at the joint ends. When the lateral stress coefficient and joint angle are the same, an increase in initial in-situ stress results in a reduction in the area of the blasting damage zone. (2) Under the same initial in-situ stress conditions, the area of the blasting damage zone initially increases and then decreases with an increasing joint angle. However, it remains larger than that without a joint, and there exists an optimal angle that maximizes the damage area. In the simulated conditions, the area of damage cracks is greatest when the joint angle is 60° dip angle. (3) The presence of initial in-situ stress has a certain impact on the initiation and expansion of blasting cracks. The degree and nature of this influence are not solely related to the lateral stress coefficient but also depend on the joint's angle and thickness. When in-situ stress is present, the initial in-situ stress field's pressure is not conducive to the initiation and propagation of blasting cracks. However, the existence of a joint has a noticeable guiding and promoting effect on crack propagation, and the pattern of crack propagation is influenced by both joint and in-situ stress conditions.

Dynamic compressive properties of UHPC under one-dimensional stress wave: The influence of steel fiber morphology and curing regime

The low matrix strength and insufficient toughness of conventional concrete structures seriously threaten the service performance when subjected to intensive compressive waves. This study aims to comprehensively investigate the impact of steel fiber morphology and curing regime on the dynamic compressive properties of Ultra-high performance concrete (UHPC) under one-dimensional stress wave. Seeking to improve its impact resistance without changing the mix ratio. Three steel fiber types (straight, wave, hooked) and two curing regimes (steam at 90 °C, dry heat at 180 °C) were selected as experimental variables. Quasi-static mechanical properties of UHPC were initially calibrated, followed by dynamic compressive tests utilizing the Split Hopkinson Pressure Bar (SHPB) system. The compressive stress-strain relationships and corresponding dynamic mechanical parameters of six types of UHPC were calculated under five impact velocities (8.5 m/s, 10.8 m/s, 13.1 m/s, 15.2 m/s, 17.3 m/s). Furthermore, the dynamic failure mode and evolutionary process of UHPC under high-speed impact was meticulously captured by a high-speed camera. CT scanning was utilized to observe the crack propagation path and damage patterns under low strain rate. Finally, SEM and EDS testing was conducted to unravel the underlying mechanisms of the curing regime and fiber morphology on the dynamic compressive properties of UHPC. The recalibrated empirical DIFfc model suitable for UHPC under strain rates of 37 s-1 to 212 s-1 was proposed.

Identification of the Surface Cracks of Concrete Based on ResNet-18 Depth Residual Network

To ensure the safety and durability of concrete structures, timely detection and classification of concrete cracks using a low-cost and high-efficiency method is necessary. In this study, a concrete surface crack damage detection method based on the ResNet-18 residual network was developed. This method was implemented by training a model with images to extract the cracks, where the image processing algorithms and deep learning were combined. The results show that the computational accuracy can meet the requirements by utilizing the established image dataset and appropriate model hyperparameters. The trained model had high recognition accuracy when the 256 × 256 resolution images were adopted, and the worst accuracy of crack recognition in the test set was over 90%. The average accuracy in the test set was 91.3% when considering environmental interference generated by processing the images with a brightness adjustment, salt-and-pepper noise, and localized interference. Then, it was demonstrated that the present model possesses good robustness for crack identification in different environments. The average recognition accuracy when dealing with images of a real bridge, which are outside the training dataset, was 99.7%. The residual network model developed in this study has the advantages of low cost, high efficiency, and practicality compared to traditional detection methods. Compared to the existing deep learning methods, the model created in this study requires less computational resources and storage space, and shows a faster training speed and higher accuracy.

Characteristics of 3D Printed Functionally Graded Material for Replacement of Dissimilar Metal Weld in Nuclear Reactor

The dissimilar metal welds in the most of the reactors are connections between low alloy steel parts and stainless steel piping. There is a high possibility of primary water stress corrosion cracking (PWSCC) damage attributed to residual stress caused by the difference in material properties in the dissimilar metal weld joints. A number of accidents such as leakage of radioactive coolant due to PWSCC have been reported around the world, posing a great threat to nuclear safety. The objective of this study is to develop a technology that can fundamentally remove dissimilar metal welds by replacing the existing dissimilar metal parts with the functionally graded material (FGM) manufactured by metal 3D printing consisting of low alloy steel and austenitic stainless steel. A powder production, mixing ratio calculation, and metal 3D printing were performed to fabricate the low alloy steel-stainless steel FGM, and microstructure analysis, mechanical properties, and coefficient of thermal expansion (CTE) measurement of the FGM were performed. As a result, it is observed that CTE tended to increase as the austenite content increased in FGM. The gradual change of coefficient of thermal expansion in a FGM showed that the additive manufacturing using 3D printing was effective for preventing an abrupt change in thermal expansion properties throughout their layers.

The multi-dimensional joint response of the electric potential time–frequency-field in the fracture process of flawed coal under dynamic load

The fracture failure of flawed coal has always been a problem in underground engineering. Therefore, it is necessary to monitor crack propagation and damage evolution during coal fracture. In this study, the split Hopkinson pressure bar (SHPB) and digital image correlation (DIC) were combined to analyze the impact failure electric potential (EP) of flawed coal samples. The multi-dimensional joint response characteristics of coal EP time–frequency-field under dynamic load were studied and the differential expression and multi-fractal characteristics of EP responses at different measuring points were analyzed. Based on the EP signals, the evolution of damage to the coal was calculated. The results show that the time series evolution of EP and stress–strain curves during coal failure is consistent. The generation of fracture zones will excite the high-value area of local EP, and the spectral distribution of EP signals in this area shows the characteristics of low frequency and high amplitude. Each channel’s EP signal and the degree of deformation at the corresponding place are perfectly matched. The multi-fractal spectrum of the EP signal close to the fracture zone has a higher Δα and a lower Δf, which demonstrates the dominance of the large-scale EP signal produced in this region by the destruction of sample. Theoretical study indicates that the main causes of the anomalous distribution of the EP field are crack tip potential, diffusion potential, etc. The results can provide theoretical basis for the evaluation of coal fracturing by EP technology.

Assessment of adjacent foundations consequences and solutions for remediation via physical modeling

In modern construction projects, a significant challenge arises from the consequential impacts of developing adjacent structures. The interplay of stresses within neighboring foundations can lead to a range of issues, such as deformation, leaning, cracking, instability, and various other damages. Among the numerous factors affecting foundation interaction, this research uniquely focuses on the impact of soil type, utilizing precise physical modeling through a 1 g testing apparatus. To enhance measurement accuracy, image processing techniques are employed in conjunction with LVDT and displacement gauges. The study systematically investigated the roles of five distinct deposit types—soft clay, loose sand, silty sand, loess, and low-compacted Tehran clay—in the manifestation of settlement and tilt arising from foundation adjacency. Subsequent to this evaluation, a comprehensive examination of strategic measures aimed at preventing and mitigating damages resulting from foundation interaction is undertaken. For silty sand, a detailed comparison of five remediation techniques is conducted, while in other soil types, only densification method is applied to address settlement and tilt. The comparison is based on the reduction in settlement and tilt, after the implementation of remediation methods under new foundation. Results highlight the crucial role of soil properties in determining damages from foundation adjacency. Notably, Tehran soil with low density exhibits maximum settlement in its loose state, while loess soil shows the highest settlement in the dense state. The exploration of soil improvement methods reveals that diaphragm walls and pile groups are influential in minimizing tilt and settlement of existing foundations, while pile groups proved to be the best remediation method in controlling displacements of new foundation.

Mechanical behaviors and rupture processes of a typical granitic stratum

Granitic veins (GVs) have a significant influence on the mechanical responses of tunnels excavated in granitic strata. Distinguishing the mechanical properties of host granites (HGs), GVs and vein-granite interfaces (VGIs) is critical. For this, this paper analyzed the mechanical behaviors and rupture processes of typical HG, GV, and VGI samples under uniaxial compression condition. For the rocks studied, although the linear axial stress‒strain relation can be identified and the deformation modulus can be determined, the transverse deformation developed nonlinearly with axial stress. As a result, the instantaneous Poisson's ratio increases continuously and may even exceed 0.5, making it extremely difficult to accurately determine the Poisson's ratio. In addition, the studied GV samples were found to be significantly brittle, indicating that large-scale GVs cannot be ignored when assessing rockburst hazards in granitic strata with brittle GVs. In terms of the rupture process, the HG and GV samples were gradually damaged by the formation of small-scale cracks and then ruptured by large cracks formed from small-scale cracks, whereas the VGI samples ruptured along large cracks with significant energy release. By examining the characteristic stress thresholds of these three granites, it is noted that the crack closure stress σcc exceeds both the crack initiation stress σci and the crack damage stress σcd for the HG and VGI samples. The transverse damage to a tested sample appears to be significantly greater than the axial damage, which is essentially related to the rock grain size and grain size distribution.

Effects of Combined Delamination and Crack Damage on Natural Frequency and Strain Energy Release Rate in Adhesively Bonded Joints Under Thermal Condition: FEA and Experimental Validation

Effects of Combined Delamination and Crack Damage on Natural Frequency and Strain Energy Release Rate in Adhesively Bonded Joints Under Thermal Condition: FEA and Experimental Validation

Damage localization on reinforced concrete slab structure using electromechanical impedance technique and probability-weighted imaging algorithm

Damage localization plays a key role in structural damage identification and health monitoring. This paper proposed a new damage localization approach using electromechanical impedance/admittance (EMI/EMA) technique integrated with probability-weighted imaging algorithm based on Gaussian distribution. The proposed approach comprises five steps namely measurement of the EMA signature from an array of piezoelectric ceramic lead zirconate titanate (PZT) transducers, computation of statistic damage indicator, establishment of regression model for the indicator, damage visualization via Gaussian distribution and final damage localization. Experimental validation of the approach was conducted on a reinforced concrete (RC) slab with artificial crack damages detected by using an array of surface-bonded PZT patches. Comparative studies on localization accuracy were performed by utilizing root mean square deviation (RMSD), baseline-changeable RMSD namely RMSDk, mean absolute percentage deviation (MAPD) and correlation coefficient (CC). Experimental results demonstrated that the proposed approach could achieve precise localization of concrete crack with error as small as 0 mm, and that using RMSDk index exhibited the highest localization accuracy in average. The proposed approach promoted the capability of the EMI technique in characterization of concrete structural damages.

Effect of height-diameter ratio on the mechanical characteristics of shale with different bedding orientations

Geological exploration cores obtained from shale gas wells several kilometers deep often show different height-diameter ratios (H/D) because of complex geological conditions (core disking or developed fractures), which makes further standard specimen preparation for mechanical evaluation of reservoirs difficult. In multi-cluster hydraulic fracturing, shale reservoirs between planes of hydraulic fractures with different lengths could be simplified to have different H/D ratios. Discovering the effect of H/D on the mechanical characteristics of shale specimens with different bedding orientations will support mechanical evaluation tests of reservoirs based on disked geological cores and help to optimize multi-cluster fracturing programs. In this study, we performed uniaxial compression tests and acoustic emission (AE) monitoring on cylindrical Longmaxi shale specimens under five bedding orientations and four H/D ratios. The experimental results showed that both the H/D-dependent mechanical properties and AE parameters demonstrated significant anisotropy. Increasing H/D did not change the uniaxial compressive strength (UCS) evolution versus bedding orientation, demonstrating a V-shaped relationship, but enhanced the curve shape. The stress level of crack damage for the specimens significantly increased with increasing H/D, excluding the specimens with a bedding orientation of 0°. With increasing H/D, the cumulative AE counts of the specimens with each bedding orientation tended to exhibit a stepped jump against the loading time. The proportion of low-average-frequency AE signals (below 100 kHz) in specimens with bedding orientations of 45° and 60° increased to over 70% by increasing H/D, but it only increased to 40% in specimens with bedding orientations of 0°, 30°, and 90°. Finally, an empirical model that can reveal the effect of H/D on anisotropic UCS of shale reservoir was proposed, the anisotropic proportion of tensile and shear failure cracks in specimens under four H/D ratios was classified based on the AE data, and the effect of H/D on the anisotropic crack growth of specimens was discussed.