Crack Analysis Research Articles

Half-sectioned spot weld parameter optimisation for liquid metal embrittlement analysis in advanced high-strength steels

Half-section welding has been proposed as a method to observe nugget growth throughout the resistance spot welding process. Some past studies used this technique as an in-situ monitoring approach to analyse the cracking behaviour during welding. However, there is a lack of understanding regarding the half-sectioned welding parameters, which critically impacts the liquid metal embrittlement cracking index. This study optimised half-sectioned welding parameters for liquid metal embrittlement crack analysis by developing process maps that compare the half-sectioned and full-section processes. It was found that the liquid metal embrittlement crack located at the weld shoulder can correlate to the temperature gradient in the heat-affected zone. This study proposes half-sectioned welding as a viable technique for liquid metal embrittlement analysis.

Mitigation of aeolian erosion of loess soil by Bio-Stimulated microbial induced calcite precipitation

Microbial-induced calcite precipitation (MICP) is a soil amelioration technique that addresses various environmental and engineering concerns. Here, we present a study focusing on aeolian erosion control of loess soil from the Negev Desert (Israel). Changes in the treated soil's chemical, physical, and microbial community (abundance and diversity) were characterized following bio-stimulation of native, urea-hydrolyzing soil bacteria to achieve MICP. Bio-stimulation of the loess soil was induced in liquid media (batch experiments) and by spraying soil trays with stimulation media (urea and yeast extract). These experiments showed that the Negev loess could be readily stimulated to induce bacterial urea hydrolysis. Three to four daily sprayings were sufficient to achieve effective bio-stimulation, evidenced by a high hydrolysis rate and an alkaline pH. Erodibility experiments on a decimeter scale (50 cm x 50 cm trays) were performed on loess sprayed with treatment media with varying concentrations of urea and CaCl2, with a constant 1:1 M ratio. The effectiveness of the treatments was studied in a wind tunnel and by image analysis of desiccation cracks. Upscaling of the experiments to the large trays revealed a more complicated reality with urease activity, community composition, and calcium carbonate precipitation depending on the concentration of the treatment medium. Specifically, we show that a twofold reduction in the area and length of the desiccation cracks can be achieved by spraying the soil with a 0.5 M solution, resulting in effective MICP or a high concentration treatment (>1M solution) without achieving MICP. Our results show that erosion mitigation in loess soil depends on an interplay between biotic and abiotic processes based on the treatment media concentration and provides a necessary step for upscaling the bio-stimulated MICP strategy for future field implementations.

Thermal stress analysis of cracks around the joints of the side wall of cast-in-place reinforced concrete open channels

Thermal stress analysis of cracks around the joints of the side wall of cast-in-place reinforced concrete open channels

A novel extended integrated radial basis functions meshfree method for crack analysis in plate problem

In this paper, a novel extended meshfree method is presented based on the integrated radial basis functions (iRBF) for crack analysis in bending plate problems. The new method is named XiRBF. The First-order Shear Deformation Theory (FSDT) is adopted to describe the deformation and stresses in cracked plate structures. The advantage of the iRBF approach is that it starts the approximation process with the highest-order derivative of the primary function first and then the lower-order derivatives are obtained by integration. This approximation style can give more accurate results for derivative values that appear a lot in governing equations of boundary value problems. In addition, the iRBF shape function also satisfies the Kronecker delta property, so essential boundary conditions can be applied as simply as the finite element method. In fracture analysis, to model the discontinuous behavior of crack surfaces, the Heaviside function is used, and to capture the singularity at the crack tip, the enriched functions are selected suitably based on the asymptotic analysis from the analytical solution. Various numerical tests are performed in which the stress resultant intensity factors (SRIFs) are calculated and the crack paths are visualized for crack propagation in the plate problems. The accuracy and efficiency of the proposed method are confirmed by comparing the present results with those obtained by other existing methods.

Analysis of an interfacial crack between two nonhomogeneous piezoelectric materials using a new domain-independent interaction integral

Considering the difficulties introduced by piezoelectric material non-homogeneity and discontinuities to interfacial crack analysis, a domain-independent interaction integral (DII-integral) is proposed to derive the stress intensity factors (SIFs) and electric displacement intensity factor (EDIF) of an interfacial crack between nonhomogeneous piezoelectrics. For continuously varying material properties, traditional interaction integral (I-integral) needs to compute the derivatives of material parameters with respect to the x1 direction of the local coordinate system, while the proposed DII-integral is demonstrated to be unrelated to any derivatives of material parameters. Furthermore, a significant improvement is achieved that the new formulation of I-integral remains valid even when the integration domains include intricate and multiple interfaces, as long as the material interfaces are perfectly bonded. Firstly, the intensity factors (IFs) calculated by the combination of the DII-integral and the extended finite element method are compared with the analytical solutions, and it is found that the relative errors of the IFs are all less than 1.79 % with various crack lengths, which verifies the accuracy of the proposed method. For the piezoelectric bi-material model with continuously nonhomogeneous properties, the calculated IFs match each other well (relative deviation < 1.3 %) for different sizes of integration domains. In addition, for the perfectly bonded interface with discontinuous electromechanical properties, the IFs are almost identical (relative deviation < 0.85 %) whether or not the integration domain contains the material interface, which further numerically verifies the good domain-independence of the established DII-integral. For an interfacial crack near extra interfaces, the differences in elastic stiffness and piezoelectric coefficient between interface sides have an obvious influence on mode-I SIF, but mode-II SIF and EDIF are affected mainly by piezoelectric coefficient and dielectric permittivity.

AI-Powered Crack Analysis: Leveraging NLP for Structural Health Monitoring

Cracks in structures pose significant risks to safety, integrity, and functionality, necessitating efficient and accurate analysis methods. This paper presents an innovative approach to crack analysis by integrating Artificial Intelligence (AI) techniques with Natural Language Processing (NLP) methodologies. Initially, NLP techniques are employed to extract key concepts, methodologies, and findings related to crack analysis from textual sources. Subsequently, features relevant to crack detection, classification, and severity assessment are extracted from the processed text data. AI models, including supervised learning algorithms such as Convolutional Neural Networks (CNNs) and unsupervised clustering methods, are trained using labelled data to detect cracks, classify their types, and assess their severity. Reinforcement learning techniques may also be explored for optimizing inspection strategies and maintenance schedules based on crack analysis results. Furthermore, the integration of sensor data, such as images from cameras and measurements from ultrasonic devices, enriches the analysis process, providing more accurate and comprehensive insights into crack formation and propagation. Real-time monitoring systems, coupled with AI models, enable continuous assessment of structural health, with alert mechanisms in place to notify relevant stakeholders of potential issues. This approach not only streamlines crack analysis processes but also enhances the efficiency and effectiveness of structural health monitoring systems, ultimately contributing to safer and more resilient infrastructure.

Machine Learning–Based Reliability Analysis of Structural Concrete Cracking Considering Realistic Nonuniform Corrosion Development

Machine Learning–Based Reliability Analysis of Structural Concrete Cracking Considering Realistic Nonuniform Corrosion Development

Research on Crack Limit Dimension of Pressure Vessel Based on FAD Diagram

Pressure vessels are widely used in petrochemical, aerospace, transportation and other industries. In the process of processing, it will form surface opening defects, and these defects will threaten the production safety. In order to effectively avoid the occurrence of safety accidents and understand the service life of pressure vessels, it is necessary to predict and analyze the crack limit size. In response to the problem of complex stress and difficulty in theoretical calculation after cracks appear on the surface of pressure vessels, this article uses the ANSYS Workbench platform to simulate and analyze the pressure vessels and obtain relevant parameters such as stress intensity factor and stress. Through calculation, the toughness ratio and load ratio are obtained. Using the FAD Failure Assessment Diagram, the ultimate crack size of pressure vessels under safety conditions is obtained. This method provides a reference for crack analysis methods and safe use of pressure vessels.

Advancing crack segmentation detection: Introducing AAMC-Net algorithm for image crack analysis

This research paper presents an innovative solution to address the challenges of poor detail detection effectiveness and prolonged training time in image segmentation. The proposed approach leverages the Adaptive Attention Multiscale Convolution Network (AAMC-Net), incorporating a multi-scale dilated convolution VGG L network for feature extraction and a deconvolution method for image segmentation. Extensive experiments demonstrate the superior performance of the proposed algorithm concerning intersection over Union (IOU), accuracy, precision, recall, F1, average training efficiency, and segmentation efficiency when compared to several traditional algorithms. On average, the proposed algorithm achieves remarkable improvements of 3.9%, 3.1%, 1.7%, 4.9%, 17.9%, 14.8% ,and 20.2% in these metrics. Moreover, the enhanced algorithm exhibits notable advantages in detail processing and real-time image segmentation detection.

The mechanism and regulation of hot cracking in a new complex-concentrated alloy by a novel integrated directed energy deposition

Improving thermal efficiency in advanced ultra-supercritical coal-fired power plants relies on increased steam temperature and pressure, accelerating the emergence of newly complex-concentrated alloys (CCAs). However, the new developed CCA have a combined Al and Ti content for 4.87 wt%, which indicates a high susceptibility to hot cracking. In this work, the hot cracking problem for the CCA during the laser deposition process was studied. The eutectic of the matrix and carbides with a low melting point liquefied during reheating process. The hot cracking occurred with local unbearable stress concentration. Based on the above analysis of hot cracking, a novel integrated directed laser deposition method was proposed to flexibly adjust the microstructure evolution and stress distribution by thermal cycles to achieve the control of hot cracks. The microstructure evolution and the control of residual stress are realized by gas quenching and preheating substrates, respectively. The evidence was obtained to show that the coupled process with synchronous gas quenching during preheating can eliminate the hot cracks effectively. More specifically, the preheating process relieved the residual stress, and the local gas quenching simultaneously accelerated the liquid film solidification and reduced carbide segregation. Finally, the sample prepared by the integrated directed energy deposition presented superior overall performance with ultimate tensile strength of 991.84 MPa and elongation of 18.28 %. This work provides a meaningful reference for producing crack-free superalloys in metal additive manufacturing.

(Invited) In Situ Characterization during Electrode Processing: The Role of Hidden Parameters

Micron and nano-sized functional materials play a key role for future technologies that are currently developed in the field of energy conversion (electrolysers, fuel cells) and electrocatalysis (N2 fixation, CO2 reduction reaction). While new materials with outstanding properties are continuously developed, they rarely find their way into – urgently needed – large scale production and industrial applications.1 One reason for this are hidden parameters that occur during ink formulation, coating (and decal transfer), cell assembly, and operation. We propose the development of coherent workflows that help us to identify reliable correlations. These should be developed for each electrocatalyst, bridging synthesis, electrode and gas diffusion electrode (GDE) / membrane electrode assembly (MEA) fabrication, and testing. All information, including “negative” results like crack formation, delamination, structural ageing and dissolution, must be reported until the relevant hidden parameters are deciphered, and the design chain is understood. Then, materials and electrodes derived from complementary processes and exhibiting subtle variations in composition and structure, can be evaluated against each other.However, this implies to fill the “blackbox” between technical catalysts and electrochemical testing in flow cells, GDEs or MEAs, with quantitative data on powders, ink formulations and coating properties. In the past years, we developed a toolbox of methods that starts from key control characteristics for technical catalysts, i.e., Pt/C for polymer electrolyte membrane fuel cells, that thereon enable the in situ analysis of ink formulations and pastes during the dispersion process and at application concentration.2,3 This is followed by the assessment of the resulting coatings from large-area crack analysis down to the level of surface roughness and pore size characteristics.4 Finally, this input is connected with performance and stability testing results to enable the comparison of different materials, the assessment of structure property relations, and ultimately to establish inline process control during electrode manufacturing. In this contribution, the developed methods will be summarized and related to their current limitations and prospects, in particular for unraveling hidden parameters during electrode fabrication and MEA assembly as well as in line process control. Literature [1] Siegmund, Daniel; Metz, Sebastian; Peinecke, Volker; Warner, Terence E.; Cremers, Carsten; Grevé, Anna; Smolinka, Tom; Segets, Doris; Apfel, Ulf-Peter; Crossing the Valley of Death : From Fundamental to Applied Research in Electrolysis, JACS Au 1 (2021), 527 – 535.[2] Bapat, Shalmali; Segets, Doris; Sedimentation Dynamics of Colloidal Formulations through Direct Visualization : Implications for Fuel Cell Catalyst Inks, ACS Applied Nano Materials 3 (2020), 7384 – 739.[3] Bapat, Shalmali; Giehl, Christopher; Kohsakowski, Sebastian; Peinecke, Volker; Schäffler, Michael; Segets, Doris; On the state and stability of fuel cell catalyst inks, Advanced Powder Technology 32 (2021), 3845 – 3859.[4] Jaster, Theresa; Albers, Simon; Leonhard, Armin; Kräenbring, Mena-Alexander; Lohmann, Heiko; Zeidler-Fandrich, Barbara; Özcan, Fatih; Segets, Doris; Apfel, Ulf-Peter; Enhancement of CO₂RR product formation on Cu-ZnO-based electrodes by varying ink formulation and post-treatment methods, JPhys Energy 5 (2023), 024001.

Mechanical Loading Effect on Stress States and Failure Behavior in Thermal Barrier Coatings

Under service conditions, apart from the harsh temperature environment, mechanical loading also seriously affects the life of thermal barrier coatings (TBCs). A comprehensive understanding of the combined effects of thermo-mechanical loads can help to further reveal the failure mechanism of TBCs. In this work, a portion of a thin-walled circular pipe is intercepted for numerical analysis, and the interface is simplified as a sinusoidal curve. The dynamic growth of thermally grown oxide (TGO) is included into the model. A cohesive model is used for interfacial cracking analysis. The results show that the effects of tensile and compressive loads on the normal stress of the coating are not significant, while the effect on the shear stress of the coating is more obvious. In addition, the in-phase load will delay the occurrence of interfacial failure behavior, while an out-of-phase load can promote the failure. These results will help to better understand the effects of the coupling of mechanical and temperature loads and to provide support and guidance for the design of new TBCs structures in the future.

Evaluating the Potential of Multi-Walled Carbon Nanotube-Modified Clay as a Landfill Liner Material.

In this paper, the feasibility of multi-walled carbon nanotube (MWCNT)-modified clay as a landfill liner material is investigated. Experiments were conducted on the modified clay with 0.5%, 1%, and 2% MWCNTs. The effects of the MWCNTs on the compaction characteristics, permeability coefficient, stress-strain curve, peak deviation stress, shear strength parameters (internal friction angle and cohesion), microstructures, and adsorption performance of the clay were analyzed. The results showed that the optimum moisture content (OMC) increased from 16.15% to 18.89%, and the maximum dry density (MDD) decreased from 1.79 g/cm3 to 1.72 g/cm3 with the increase in MWCNTs. The permeability coefficients firstly fell and then gradually rose as the MWCNTs increased; the minimum permeability coefficient was 8.62 × 10-9 cm/s. The MWCNTs can also effectively increase the peak deviation stress of the clay, and at the maximum level, the peak deviation stress was increased by 286%. SEM images were processed using the Pore and Crack Analysis System (PCAS), and the results showed that the appropriate amount of MWCNTs could fill the pores and strengthen the clay structure. The effect of the MWCNT-modified clay on the adsorption performance of common heavy metal ions Cd2+, Mn2+ and Cu2+ in landfill leachate was analyzed by batch adsorption tests. The maximum adsorption capacities (Qmax) of Cu2+, Cd2+ and Mn2+ in the 2% MWCNT-modified clay were, respectively, 41.67 mg/g, 18.69 mg/g, and 4.97 mg/g. Compared with the clay samples without MWCNTs, the adsorption properties of Cu2+, Cd2+, and Mn2+ were increased by 228%, 124%, and 202%, respectively. Overall, the results suggest that MWCNT-modified clays have the potential to be suitable barrier materials for the construction of landfills.

Structural integrity analysis of the pre-stressed concrete dome of the Belgrade fair hall 1

Belgrade fair hall 1 is well known for its dome, which is still the world largest self-supported construction made of pre-stressed concrete, with its diameter of 106 m. In this paper the Finite Element Method (FEM) was performed to analyze different loading and supporting conditions. At the same time, crack growth in a support column was simulated by the extended FEM (XFEM). Results of numerical calculations indicate ingenious design of such a complex structure which was based on “hand” calculation decades ago, without computers. In addition to classical engineering and more advanced numerical calculations, risk based analysis was performed taking into account artificially introduced crack and Failure Analysis Diagram, obtained using stress intensity factor and net stress, as well as fracture toughness and critical stress. This analysis, made for the first time for Belgrade fair hall 1, proved that its structural integrity is jeopardized only when a crack reaches half the thickness of a steel bar.

Surface crack analysis of 8Cr4Mo4V steel based on Crystal/Phase microstructure model by grinding

Metal polycrystalline materials tend to be homogeneous and isotropic at the macroscopic level, which leads it difficult to visually characterize the sprouting and expansion of cracks by traditional grinding simulation. In this study, the Johnson–Cook constitutive model was used for the finite element method (FEM) based on grinding characteristics with a high strain rate and large plastic deformation. The models are focused on the actual microstructure distribution, one of them contains grains and grain boundaries, and another contains phase organization (martensite and acicular martensite) and carbides. The study pinpoints the changes in microstructure under different grinding parameters during the grinding process and the influences on the formation of microscopic cracks. Ultimately, it was found that the shedding of large primary carbide is a critical factor for inducing surface cracks. The uncoordinated deformation between brittle carbides with the other phases is the main cause of carbide shedding. Therefore, this article visualized shows the influence of grinding parameters on surface cracks from the perspective of microstructure modeling, which is of great significance in guiding practical processing.

Failure analysis for outer ring cracking of GCr15 rolling bearing

The purpose of this study analysis is to explore the reasons for the outer ring cracking of GCr15 rolling bearing. The failure mechanism was studied through observation of its microstructure and fracture morphology. The analysis results reveal that the main failure reason for the bearing was that the surface secondary quenching layers and network carbides caused the formation of cracks. In order to prevent failure, reasonable grinding process parameters, forging process parameters and normalizing heat treatment before spherodizing annealing were suggested.

In-Depth Steel Crack Analysis Using Photoacoustic Imaging (PAI) with Machine Learning-Based Image Processing Techniques and Evaluating PAI-Based Internal Steel Crack Feasibility

Steel plays an indispensable role in our daily lives, permeating various products ranging from essential commodities and recreational gears to information technology devices and general household items. The meticulous evaluation of steel defects holds paramount importance to ensure the secure and dependable operation of the end products. Photoacoustic imaging (PAI) emerges as a promising modality for structural inspection in the realm of health monitoring applications. This study incorporates PAI experimentation to generate an image dataset and employs machine learning techniques to estimate the length and width of surface cracks. Furthermore, the research delves into the feasibility assessment of employing PAI to investigate internal cracks within a steel sample through a numerical simulation-based study. The study’s findings underscore the efficacy of the PAI in achieving precise surface crack detection, with an acceptable root mean square error (RMSE) of 0.63 ± 0.03. The simulation results undergo statistical analysis techniques, including the analysis of variance (ANOVA) test, to discern disparities between pristine samples and those featuring internal cracks at different locations. The results discern statistically significant distinctions in the simulated acoustic responses for samples with internal cracks of varying sizes at identical/different locations (p &lt; 0.001). These results validate the capability of the proposed technique to differentiate between internal crack sizes and positions, establishing it as a viable method for internal crack detection in steel.

A generalized finite difference method for 2D dynamic crack analysis

This paper presents a new framework for efficient and accurate analysis of transient elastodynamic cracks by using the generalized finite difference method (GFDM). The method first discretizes the solution domain into a set of overlapping small subdomains, and then in each of the subdomains, the unknown functions and their derivatives are approximated by using the local Taylor series expansions and moving-least square approximation. The degree of the Taylor series used in the local subdomain is increased automatically in the regions near the crack-tips, in order to appropriately describe the local asymptotic behavior of near-tip displacement and stress fields. The path-independent J-integral and sub-domain technique are adopted to compute the dynamic stress intensity factors (SIFs) of the cracked bodies. Preliminary numerical experiments for dynamic SIFs with both uniform and variable loading conditions are given to show the efficient and accuracy of the present method for transient elastodynamic crack analysis.

Road crack detection interpreting background images by convolutional neural networks and a self‐organizing map

AbstractThe presence of road cracks is an important indicator of damage. Deep learning is a prevailing method for detecting cracks in road surface images because of its detection ability. Previous research works focused on supervised convolutional neural networks (CNNs) without non‐crack features or unsupervised crack analysis with limited accuracies. The novelty of this study is the addition of background classification. By increasing the number of non‐crack categories, CNNs are driven to learn non‐crack features and improve crack detection performances. Non‐crack images are preprocessed, and their features are extracted in an unsupervised way by a deep convolutional autoencoder. A self‐organizing map clusters features to obtain non‐crack categories. This study focusses on classification though the method can be adopted in parallel with the latest segmentation algorithms. Using common road crack datasets, modified deep CNN models significantly improved accuracy by 1%–4% and f‐measure by 3%–8%, compared to previous models. The modified visual geometry group (VGG) 16 showed the top‐level performance, 96% accuracy and 84%–85% f‐measure. The models drastically reduced false detection cases while maintaining their crack detection abilities.

A Study of Acoustic Emission Based RA-AF Characteristics of Polypropylene Fiber-Reinforced Recycled Aggregate Concrete Under Uniaxial Compression

In order to research the acoustic emission characteristics of polypropylene fiber-reinforced recycled aggregate concrete under uniaxial load, 20 groups of test specimens with a coarse aggregate substitution rate of 25 % and 50 % are designed and fabricated to conduct the acoustic emission test under uniaxial compression, and the evolution laws of the acoustic emission b-value, the cracking modes and the acoustic emission RA-AF moving averages with time are studied. The laws of influence of the coarse aggregate substitution rate and coarse-fine polypropylene fiber on the acoustic emission b-value of RAC are discussed. The K-means clustering method is adopted for two-dimensional clustering analysis of the shear cracking and tensile cracking, and then the SVM is used to obtain the boundary between the two types of clusters. The time distribution laws of shear cracking and tensile cracking of the polypropylene fiber-reinforced recycled aggregate concrete are analyzed. The changes in the moving averages of RA and AF of RAC test specimens with time are studied, and the research indicates that as the RA value decreases, the shear cracking gradually reduces and the tensile cracking gradually increases and dominates.