Shallow Cracks Research Articles

Application and environmental sustainability assessment of microbial induced calcite precipitation in asphalt concrete crack repair

ABSTRACT Cracks are a major factor affecting the durability of asphalt concrete. Microbial-induced calcite precipitation (MICP) represents an eco-friendly method for repairing these cracks compared to conventional methods. This study investigates the repair of artificial prefabricated asphalt concrete cracks using MICP, assessing uniaxial compressive strength, permanent deformation, moisture buffering, and water sensitivity for different crack depth conditions. Microscopic analysis using SEM/EDS and X-ray micro-computed tomography was conducted. The results show that MICP reduces void fraction by 75% and increases uniaxial compressive strength and ultrasonic velocity by approximately 20%, while improving creep stiffness modulus, moisture buffering value, and resilient modulus ratio by 5%-10%. The effectiveness decreases with increasing crack depth. Calcite particles cluster within 20 mm from the crack top, enhancing mechanical properties. MICP is feasible for repairing shallow cracks. An analysis of the energy consumption and carbon emissions of the MICP technology using a life cycle assessment demonstrates that the industrial preparation processes of calcium sources and urea produce substantial carbon emissions and energy consumption, accounting for 68.31% and 94.64% of the total process, respectively, revealing that it is crucial to explore alternative materials in the future to reduce the environmental impact.

Cracking of silty mudstone subjected to wetting-drying cycles

Cracking affected by wetting-drying cycles is a major cause of shallow failure of soft rock slopes. Knowledge of rock tensile properties and cracking behaviors helps better assess the stability of soft rock slopes. This study aims to examine the cracking behaviors and tensile strength of silty mudstone under wetting-drying cycles. The wetting-drying cycles and Brazilian splitting tests were performed on silty mudstone considering various cycle number and amplitude. The cracking behaviors of wetting-drying cycles were analyzed by digital image correlation, three-dimensional (3D) scanning technology, and scanning electron microscopy. The results reveal a spiral-like pattern of crack ratio escalation in silty mudstone, with a higher crack ratio observed during drying than wetting. Tensile strength and fracture energy correlate negatively with cycle number or amplitude, with cycle number exerting a more pronounced effect. The variance of the maximum principal strain reflects stages of initial deformation, linear deformation, strain localization, and stable deformation. The formation of strain localization zones reveals the physical process of crack propagation. Crack tip opening displacement progresses through stages of slow growth, exponential growth, and linear growth, delineating the process from crack initiation to stable extension. Failure modes of silty mudstone primarily involve tensile and tensile-shear failure, influenced by the geometric parameters of cracks induced by wetting-drying cycles. Fracture surface roughness and fractal dimension increase with cycle number due to mineral dissolution, physical erosion, and nondirectional crack propagation. Hydration-swelling and dehydration-shrinkage of clay minerals, along with absorption-drying cracking, initiate and merge cracks, leading to degradation of the rock mechanical properties. The findings could provide insights for mitigating shallow cracking of soft rock slopes under wetting-drying cycles.

Advanced concrete pavement internal crack monitoring using wave response variation and deep learning

This paper presents an in-depth investigation into internal crack monitoring in concrete pavement through the application of wave response variation (WRV) and deep learning techniques. The study examines wave scattering in both homogeneous (HM) and inhomogeneous (IHM) media, validating WRV by analyzing forward scattering due to interval vertical cracks through laboratory tests and analytical solutions. It compares various laboratory tests with experimental and finite element (FE) results. The analysis reveals that shallower cracks result in peaks at lower impulse frequencies on the WRV curve, while deeper cracks correspond to peaks at higher frequencies, as observed from both forward and incident waves. The study also finds that the complexity of IHM, influenced by random aggregate size and distribution, significantly affects WRV patterns, with larger aggregates causing greater energy attenuation in forward waves compared to smaller aggregates. Machine learning (ML) techniques are employed to predict cracks and clarify the impact of aggregate information on WRV. This research establishes a framework for understanding internal damage in IHM using ML technology. This study enables effective monitoring of internal vertical cracks, such as reflective cracks in bridge decks, pavements, and airport runways.

A probabilistic model to predict specimen geometry effects on fracture toughness in ferritic–pearlitic steels

This work describes a probabilistic framework for cleavage fracture of ferritic–pearlitic steels incorporating experimental measurements of microcrack distribution associated with the cracking of the pearlitic microstructure. A central objective of this study is to explore and further extend application of a probabilistic framework incorporating the statistics of microcracks to predict specimen geometry effects on the fracture toughness distribution for a typical ferritic–pearlitic structural steel. Fracture toughness values for an ASTM A572 Grade 50 structural steel derived from fracture tests using conventional SE(B) specimens with varying thickness and a/W-ratios provide the cleavage fracture resistance data needed to assess specimen geometry effects on the probability distribution of Jc-values. The present exploratory study successfully predicts the measured statistical distribution of cleavage fracture toughness in shallow crack specimens and provides further support of the proposed probabilistic model as a more advanced and effective engineering-level procedure in fracture assessment methodologies.

Finite Element Analysis based Stress Intensity Factor Solutions for Surface Cracks

The stress intensity concept is important in termsof crack extension as critical values of the stress intensityfactors govern crack initiation. Therefore, the present workdetermines stress intensity factors for semielliptical shallowand deep surface cracks as a function of parametric angle,crack depth, and aspect ratio for tension and bending loads.The stress intensity factors are obtained from a threedimensional finite-element analysis of semielliptical surfacecracks in finite plates subjected independently to tensionand bending loads under elastic conditions. The obtainedstress intensity factor is used to predict the crack growthunder linear elastic conditions. Results show that the stressintensity factor varies along the crack front for shallow anddeep cracks. At the deepest point in bending and tension thestress intensity factor increases as the ratio of the crackdepth to the crack length at surface decreases. However, atthe free surface the stress intensity factor becomesmaximum when the crack depth equals crack length. Asurface crack in tension loading is predicted to break thewall thickness with a relatively small amount of crackgrowth at surface. While in bending the crack breaksthrough with large amount of crack growth in the widthdirection.

Analysis of failure mechanism of concrete pole based on finite element extended method

Concrete poles play an important role in distribution networks and are prone to degradation due to environmental influences. Fracture failures primarily result from structural deterioration, including both damage to the concrete structure under stress overload conditions and the deterioration of the concrete material itself. Due to the lower tensile strength compared to compressive strength, concrete structures often exhibit cracking and fractures. This study initially analyzes the structural deterioration process of concrete electric poles and subsequently develops a damaged model using the finite element method. The results reveal that the maximum tensile strength of concrete electric poles occurs at 2.4 m, while the compression is maximum within the 2–6 m range. Furthermore, an analysis of the main factors contributing to fracture failures and structural deteriorations of these poles is conducted using the finite element extension method. It is determined that shallower crack depths and higher concrete strength enhance fracture resistance and the bearing capacity of concrete poles. Notably, annular cracks at the 2.4 m height are more prone to spreading.

Concrete crack segmentation based on multi-dimensional structure information fusion-based network

The state-of-the-art (SOTA) crack segmentation methods still face the challenges in low-contrast shallow crack recognition and multi-scene compatibility. Therefore, this paper proposes a solution based on a multi-dimensional structure information fusion-based network (MDSIFNet). This network consists of two branches, one for extracting two-dimensional (2D) spatial feature information and another for acquiring three-dimensional (3D) geometric one. In the former, the designed 2D curve structure constraint module based on prior knowledge combined with a pretrained 2D feature extraction module can reduce learning samples and realize crack segmentation in unseen scenes. In the latter, a one-hot transformation and a 3D geometric structure information extraction module are designed to make the network pay attention to the geometric features of shallow cracks and improve their segmentation accuracy. Finally, a fusion module couples the multi-dimensional structure feature information of these two branches and outputs pixel-wise segmentation results that can be used for crack measurement and quantitative analysis. The experimental results show that the designed model network MDSIFNet performs better than the SOTA methods in terms of performance and visualized results.

Quantification of micro-damage evolution process in ceramics through extensive analysis of multi-source heterogeneous data

Due to the randomness of hard and brittle material damage evolution, assessing damage and interpreting mechanisms is challenging. This study focuses on analyzing material damage mechanisms by employing extensive multi-source heterogeneous data to extract quantitative information. A machine vision-based method for detecting and assessing defects in ceramics was proposed, achieving 98 % accuracy. Leveraging this method in scratching experiments, the progression of damage and micro-failure mechanisms in Si3N4 was investigated through the analysis of defect area distribution, force and acoustical signals. Results revealed that the distribution of defect areas conforms to a three-parameter Weibull distribution. At scratch depths of 0.01, 0.02 mm, approximately 90 % of damage accumulated within 1e2–1e4 μm2; conversely, 0.03–0.06 mm led to a decrease to 30 – 40 %. Extensive crack propagation occurs within 0.02–0.03 mm, resulting in the intersecting formation of spalling blocks. Damage evolution occurs in three stages: shallow and small cracks with scattered spalling blocks in the first stage, deep and long cracks with continuous and irregularly shaped spalling blocks in the second stage, and nearly no cracks with continuous and regularly shaped blocks in the third stage. This study not only proposes an efficient method to detect and evaluate ceramic defects, but also deeply understands the evolution process of material damage mechanism. Considering defect distribution and statistical trends, this research not only provide guidance for the optimization of machining parameters, especially in the scene of specific precision and high removal rate. At the same time, the damage evolution and failure mechanism of Si3N4 provide useful experimental basis and data support for deepening the understanding of material behavior during ultra-precision grinding.

Dual-path network combining CNN and transformer for pavement crack segmentation

Cracks are one of the most common pavement surface diseases. Timely repair of these cracks is imperative to prevent a substantial reduction in the pavement’s service life. However, the persistent challenges in crack segmentation arise from factors such as thin and shallow crack characteristics, a cluttered background, and foreground distractors. In response to these challenges, a dual-path network for pavement crack segmentation is introduced, leveraging a synergistic combination of Convolutional Neural Network (CNN) and transformer. First, the proposed approach involves a lightweight CNN encoder for local feature extraction and a novel transformer encoder integrating a fully convolutional high-low frequency attention (FCHiLo) mechanism and an efficient feedforward network for global feature extraction. Second, a complementary fusion module (CFM) is introduced to aggregate intermediate features extracted from both encoders. The multi-scale fusion outputs are systematically conveyed to the decoder, facilitating gradual image recovery and segmentation result acquisition. Evaluation on three publicly available datasets—DeepCrack, CrackForest, and CrackTree 260—affirms the superior performance of the proposed network compared to ten established models.

Automated surface defect detection in forged parts by inductively excited thermography and magnetic particle inspection

ABSTRACT Inductively excited thermography has been shown to detect cracks in metallic components with good sensitivity. It is discussed as an alternative to magnetic particle testing. An open question to achieve acceptance in the industry is its testing reliability. A study with in total 200 forged steel parts was performed in order to compare the testing reliability of automated inductively thermographic testing and magnetic particle inspection. A robot supported thermographic inspection station was used. An inductor with orientation-independent crack detection was built up and tested. The thermographic phase images obtained were analysed by an automatic defect detection procedure based on machine learning techniques. Results of magnetic particle inspection served as a reference. Depending on the type of test object, an agreement of 68% to 82% was achieved, if only large indications of thermography were considered. The weak thermographic indications turned out to be due to shallow cracks (<150 µm depth). Improvement of the testing speed can be achieved by inspection inside large coils.

Novel semi-ring type alternating current field measurement probe for inspection of coiled tubing

Coiled tubing is a critical equipment in the oil and gas exploration and development field. Due to the high pressure, corrosive medium and repeated buckling, cracks are easily introduced in the surface of the coiled tubing. It is necessary to detect cracks in-service for the maintenance of the coiled tubing. In this paper, a new semi-ring type alternating current field measurement (ACFM) probe is presented for imaging and evaluating the surface cracks in the coiled tubing. The finite element method (FEM) model is developed to analyze the characteristic signals of the crack. According to the simulate results, the tunnel magneto resistance (TMR) sensor arrays in semi-ring ACFM probe is placed between the coiled tubing wall and the coil. The experimental results show that the novel ACFM probe can achieve imaging and detection of surface axial and circumferential cracks in the coiled tubing. The through-wall crack can be judged effectively compared to the shallow crack. The length of axial cracks can be accurately evaluated by the peak-valley spacing of the Bz signal. The length of circumferential crack can be evaluated approximately by the location of sensor arrays in the circumferential direction.

Анализ зависимости проницаемости от открытой пористости карбонатных пород коллектора в районах Астраханского газоконденсатного месторождения

At the present moment the fields reserves containing viscous and high-viscosity oil account for more than half of all the explored reserves of oil and gas fields. Carbonate deposits, in which oil and gas fluids are concentrated, are characterized by a complex structure of void space containing hydrocarbons. Due to the higher content of part of the oil in unrelated shallow cracks, the development of such reserves is difficult. For this reason, the main task of this study was to establish the dependence of the core-core permeability index on the porosity of carbonate reservoir rocks composing the Astrakhan Gas Condensate field (AGCM). Based on the characteristics of the Astrakhan arch and deposits in the AGCM areas, the paper presents the results of research work to determine the porosity of the rock by hydrostatic weighing based on the available information about the carbonate deposits of the formation, the physical properties of the rocks composing the formation, the characteristics of the geophysical values of porosity and permeability. The obtained values of the mass samples are given by weighing in various saturation states and calculating the permeability of the core samples. The linear dependence of the open porosity of carbonate rocks on permeability is revealed. The analysis of the results of studies on core samples obtained at the wells of the AGCM was carried out. The values of porosity and permeability coefficients are given. Based on the conclusion about the filtration-capacitance properties of the deposit the dependence of the permeability of the rock on the open porosity on the reservoir properties of the deposit was cocluded. The graph obtained on the basis of the calculated data is given, the equation of the “core-core” dependence or a linear regression equation is compiled.

Automated crack segmentation on 3D asphalt surfaces with richer attention and hybrid pyramid structures

ABSTRACT Automated pavement crack detection is crucial to supporting fine pavement maintenance and ensuring safety for road facilities. Due to the complex pavement condition and crack features, it is still a critical challenge in intelligent pavement surveys. This paper proposed a novel pixel-level pavement crack segmentation network, PCSNet, to provide a solution to this challenge. The network has richer attention and hybrid pyramid structures, which implement full-process crack feature fusion and enhancement. The richer attention module consists of cascaded self-attention and attention gate modules. It captures the crack spatial dependence information and prunes the feature response. The hybrid pyramid structures consist of a multistage convolutional pyramid module and a pyramid pooling module. It integrates contextual information at multiple receptive field scales to enhance the potential crack feature representation. The proposed structure enriches the crack details and optimises the scene parsing on the global geometry of the cracks. A sizeable 3D pavement crack dataset is built for training and testing. The proposed network exhibited the best performance, achieving F1-score, mean intersection of union, and mean pixel accuracy of 81.21%, 77.13%, and 87.17%, respectively. The network can reconstruct the complete crack geometry, preserve the crack edges well, and optimises the detection of shallow and complex cracks. The method exhibits superior and robust performance, facilitating accurate pavement technical condition assessment and maintenance decisions.

Process research on the hydrocarbon conversion of straight-run gas oil (SRGO) to chemical materials

To deepen the understanding of the reaction process for SRGO-hydrocarbon conversion, this article systematically explained the process conditions and conversion performance of SRGO-hydrocarbon conversion to produce chemical materials, based on the reaction mechanism. Ni & W and USY molecular sieve were selected as the hydrogenation active component and the cracking component of the hydrocracking catalyst, respectively. γ-Al2O3 and USY molecular sieve were mixed and extruded to prepare the carrier for the hydrocracking catalyst. The results indicate that cycloalkanes and aromatics are preferentially converted into heavy naphtha (HN) in the primary cracking process. The aromatic-potential-content of HN is high during shallow cracking due to the high content of cycloalkane and aromatic in SRGO. As the cracking depth increases, the cracking of paraffin is gradually strengthened, and the absolute paraffin-amount in diesel accelerates to decrease. Simultaneously, due to the enrichment of paraffin in HN, the aromatic-potential-content of HN decreases. In addition, the experimental results also indicate that although reaction temperature and LHSV are both means of controlling the conversion rate of SRGO, even if the conversion rate of SRGO is similar, high temperature is still conducive to the formation of light components, such as light naphtha (LN). High H2 pressure will inhibit the conversion of HN to lighter components and the conversion of paraffin in diesel to HN.

Investigation on the fracture behavior of octet-truss lattice based on the experiments and numerical simulations

Octet-truss lattice is an excellent carrier for structure–function integration because of its natural porous characteristics and remarkable bearing capacity. Currently, a significant discussion in its engineering applications revolves around assessing the fracture toughness of the lattice structure. In this paper, the single edge notched bend (SENB) specimens composed of PolyMaxTMPLA with shallow crack are prepared using the Fused Deposition Modelling (FDM) method, and three-point bending tests are conducted to investigate the fracture behavior of the octet-truss lattices. Based on the elastic–plastic fracture behavior of the specimens, the J-integral method is used to calculated the effective fracture toughness and the effect of shallow crack on the fracture toughness was considered. The experimental results show that the effective fracture toughness of the polymer specimens increases linearly with the relative density and the square root of truss length. To study the fracture behavior of lattice structure deeply, the numerical simulations are performed to further analyze the fracture behavior of the structures and verified by the experimental results. The results suggest that the fracture at the nodes and the truss near the nodes is the main failure mode of the specimens. Specially, the truss in the X-Z plane always breaks before the X-Y plane, while the deformation of truss in the Y-Z plane is always elastic. A prediction formula of the effective fracture toughness of 3D printed PLA polymer octet-truss lattice is determined based on a non-dimensional parameter sensitive to the loading mode.

Application of Non-Destructive Testing Technology in Quality Testing and Control of Water Conservancy Projects

In view of social development, the demand for water conservancy engineering applications continues to increase. The number and scale of water conservancy projects in China have been in a state of continuous expansion in recent years. As a result, how to achieve efficient testing and effective control of the quality of water conservancy projects has always been a topic of discussion in the field of water conservancy engineering in our country. This paper summarizes the application of non-destructive testing technology in the quality testing and control of water conservancy projects. On the basis of explaining the connotation and application advantages of non-destructive testing technology, the non-destructive testing application strategies for concrete strength, steel corrosion and shallow cracks in water conservancy projects were studied.

Influence of reinforcement method on the crack characteristic parameters of expansive soil experimental study

The expansive soil slope is mainly characterized by the decline of slope integrity caused by shallow expansive soil cracking and the destruction of internal soil structure, which seriously affects the overall stability of expansive soil slope. To study the effect of the combination of geogrid reinforcement and slope vegetation on inhibiting the development of expansive soil cracks, six groups of test models were made. The natural dry–wet cycle was simulated, and the crack image was binarized by using image processing technology. The crack characteristic parameters such as crack ratio, crack width, and crack length were extracted, and the effect of various reinforcement methods on inhibiting the development of cracks was comprehensively evaluated. The basic situation of the development of crack indexes in each group with the development of multiple dry–wet cycles was obtained, and the fluctuation changes of crack indexes in different stages were different under different reinforcement methods and dry–wet cycles. At the same time, the influence of different reinforcement methods on the crack development of expansive soil is obtained. It is considered that planting vetiver grass + geogrid backpacking has a good effect on inhibiting the crack development of expansive soil.

Mechanism of Time-Dependent Instability of Deep Soft-Rock Roadway and Crack-Filling Reinforcement Technology

Soft broken surrounding rock exhibits obvious rheological properties and time-dependent weakening effects under the action of deep high-ground stress, leading to the increasingly prominent problem of sustained large deformation in deep roadways. In this study, with the II5 Rail Rise in Zhuxianzhuang Coal Mine as an example, the mechanism and control technology of time-dependent damage and instability in a deep soft-rock roadway were explored through a field observation and numerical simulation. The research results show that the range of the loose circle in the deep fractured surrounding rock can reach 3.0 m. The expansion of shallow and deep cracks causes the primary plastic deformation and secondary rheological deformation of the surrounding rock, with the rheological deformation rate increasing by 21.4% every 55 days on average, which ultimately induces the instability and failure of the surrounding rock. Based on the mechanism of roadway instability, a control technology of high-preload bolt + deep- and shallow-borehole crack filling was proposed. The technology reduces deformation and ensures the stability of the roadway surrounding rock by inhibiting the propagation of deep and shallow cracks and reinforcing the surrounding rock.

A Comment on: An Eocene army ant (2022) by Sosiak CE et al.

A Comment on: An Eocene army ant (2022) by Sosiak CE et al.

Cryogenic fracture toughness of 3D random fibrous materials

This study aimed to evaluate the fracture toughness of three-dimensional random fibrous (3D RF) materials with 87% porosity and shallow surface cracks at room temperature (20 ℃) and cryogenic temperature (− 100 ℃). The ratios of crack length to specimen width of three-point-bending (3-p-b) specimens were 0.2 and 0.5, respectively. The experimental results revealed that the average fracture toughness KIC at − 100 ℃ was higher than that at 20 ℃. In addition, the experimental data were analysed using the boundary effect model (BEM), with almost all experimental data included in the upper and lower boundaries with 96% reliability, as specified by a normal distribution. Furthermore, based on the fracture toughness KQ computed using the formula of American Society for Testing Materials (ASTM), the expression of the fibre gap size G is derived. When the confidence level was 95%, no significant difference was observed in the fracture toughness model when the fibre gap size G was replaced with the average fibre spacing size D2 in the fracture toughness model. Thus, this study is expected to provide a reference for the safety assessment of the insulation layer of space shuttles at cryogenic temperatures.