Internal Defects Research Articles

Fracturing Processes in Specimens with Internal vs. Throughgoing Flaws: An Experimental Study Using 3D Printed Materials

AbstractThe fracturing behavior and associated mechanical characterization of rocks are important for many applications in the fields of civil, mining, geothermal, and petroleum engineering. Laboratory testing of rocks plays a major role in understanding the underlying processes that occur on the larger scale and for predicting rock behavior. Fracturing research requires well-defined and consistent boundary conditions. Consequently, the testing design and setup can greatly influence the results. In this study, a comprehensive experimental program using an artificial material was carried out to systematically evaluate the effects of different parameters in rock testing under uniaxial compression. The parameters include compression platen type, specimen centering, loading control method, boundary constraints, and flaw parameters. The results show that these testing conditions have a significant effect on the mechanical behavior of rocks. Using a fixed compression platen helped reduce bulging of the material. Centering of the specimen played a critical role to avoid buckling and unequal distribution of stress. Slower displacement rates can control the energy being released once failure occurs to prevent the specimen from exploding. Also, the frictional end effects were investigated by comparing friction-reduced and non-friction-reduced end conditions. Very importantly, the study also identified variations in crack initiation and propagation between specimens with internal flaws and specimens with throughgoing flaws. This investigation showed that wing cracks appeared in specimens with throughgoing flaws, while wing cracks with petal cracks were associated with the internal flaws. It also showed that the mechanical properties are influenced by the inclination of the flaws and established that specimens with internal flaws generally exhibit higher strength compared to specimens with throughgoing flaws. The systematic analysis presented in this work sheds light on important considerations that need to be taken into account when conducting fracture research and adds knowledge to the fundamental understanding of how fractures occur in nature.

Coupled cellular automata-crystal plasticity modeling of microstructure-sensitive damage and fracture behaviors in deformation of α-titanium sheets affected by grain size

Concerning the micro-scale deformation of titanium metal sheets, the number of grains in the sheet thickness direction decreases, and their formability exhibits a strong grain size sensitivity. Meanwhile, the twinning-induced dynamic recrystallization (TDRX) associated with grain size significantly affects the fracture behavior in the microforming of titanium sheets. Therefore, an accurate prediction of formability to improve manufacturing reliability remains challenging in the microforming of miniaturized titanium components. To address this issue, an in-depth understanding of the grain size-dependent TDRX behavior and its role in damage and fracture development in the microforming of α-titanium sheets is critical, and a coupled cellular automata-crystal plasticity (CA-CP) modeling framework was thus developed as an approach providing efficient solutions and insightful comprehensions of the issue. For the proposed modeling framework, a kinematic model for TDRX was established and integrated into the CP model by the CA algorithm. As a result, the microstructure evolution caused by TDRX was regarded as an intrinsic part of the constitutive behavior to connect heterogeneous plastic deformation and damage evolution through data transmission between the CP model and the CA algorithm. Additionally, the coupled CA-CP modeling framework was validated with the internal defect morphologies and deformation microstructures characterized by X-ray computed tomography (X-CT) and electron backscattered diffraction (EBSD). Experiment and simulation results demonstrated that the fine recrystallized (DRXed) grains were generated after the twin fragmentation when the dislocation density at twin boundaries reached a threshold of 9.2 × 1013 /m2. After TDRX, the dislocation density and the stress concentration intensity in recrystallization regions were revealed to decrease, accounting for the ductility improvement. Nevertheless, the dislocation density at twin boundaries was determined to decrease with the increase of grain size, leading to less twin fragmentation and the absence of TDRX. The uncoordinated deformation between fine DRXed grains motivated defects to grow spherically into microvoids, thereby preventing premature intergranular cracks along twins/grain boundaries. Ultimately, the deformation microstructures resulting from TDRX with the decrease of grain size were confirmed to control the brittle to ductile fracture transition of α-titanium sheets. The presented modeling framework and simulation procedure were validated to be able to predict the material integrity affected by crystalline microstructure in the deformation of titanium metal sheets.

Fatigue Characteristics Analysis of Carbon Fiber Laminates with Multiple Initial Cracks

In the entire wind turbine system, the blade acts as the central load-bearing element, with its stability and reliability being essential for the safe and effective operation of the wind power unit. Carbon fiber, known for its high strength-to-weight ratio, high modulus, and lightweight characteristics, is extensively utilized in blade manufacturing due to its superior attributes. Despite these advantages, carbon fiber composites are frequently subjected to cyclic loading, which often results in fatigue issues. The presence of internal manufacturing defects further intensifies these fatigue challenges. Considering this, the current study focuses on carbon fiber composites with multiple pre-existing cracks, conducting both static and fatigue experiments by varying the crack length, the angle between cracks, and the distance among them to understand their influence on the fatigue life under various conditions. Furthermore, this study leverages the advantages of Paris theory combined with the Extended Finite Element Method (XFEM) to simulate cracks of arbitrary shapes, introducing a fatigue simulation method for carbon fiber composite laminates with multiple cracks to analyze their fatigue characteristics. Concurrently, the Particle Swarm Optimization (PSO) algorithm is employed to determine the optimal weight configuration, and the Backpropagation neural network (BP) is used to train and adjust the weights and thresholds to minimize network errors. Building on this foundation, a surrogate model for predicting the fatigue life of carbon fiber composite laminates with multiple cracks under conditions of physical parameter uncertainty has been constructed, achieving modeling and assessment of fatigue reliability. This research offers theoretical insights and methodological guidance for the utilization of carbon fiber-reinforced composites in wind turbine blade applications.

Deciphering the Effect of Defect Dipoles on the Polarization and Electrostrain Behavior in Perovskite Ferroelectrics.

Defect dipoles are crucial for regulating electromechanical properties in piezoelectric ceramics, but their effects on polarization and electrostrain behaviors are still unclear. Here, a reasonable theoretical model is proposed and evidenced by experiments to address a long-standing puzzle of the relationship between the internal bias field and defect dipoles. By incorporating the additional polarization induced by defect dipoles, we refine the classical theory to account for the recently reported asymmetric giant-strain behaviors. Phase-field simulation reveals the electrostrain evolution in response to defect dipole elastic distortion and additional polarization. This work not only elucidates the effect of defect dipoles on polarization and electrostrain but also advances the theoretical understanding of defects in piezoelectrics.

Bioinspired Asymmetric-Adhesion Janus Hydrogel Patch Regulating by Zwitterionic Polymers for Wet Tissues Adhesion and Postoperative Adhesion Prevention.

Asymmetrically adhesive hydrogel patch with robust wet tissue adhesion simultaneously anti-postoperative adhesion is essential for clinical applications in internal soft-tissue repair and postoperative anti-adhesion. Herein, inspired by the lubricative role of serosa and the underwater adhesion mechanism of mussels, an asymmetrically adhesive hydrogel Janus patch is developed with adhesion layer (AL) and anti-adhesion layer (anti-AL) through an in situ step-by-step polymerization process in the mold. The AL exhibits excellent adhesion to internal soft-tissues. In contrast, the anti-AL demonstrated ultralow fouling property against protein and fibroblasts, which hinders the early and advanced stages of development of the adhesion. Moreover, the Janus patch simultaneously promotes tissue regeneration via ROS clearance capability of catechol moieties in the AL. Results from in vivo experiments with rabbits and rats demonstrate that the AL strongly adheres to traumatized tissue, while the anti-AL surface demonstrate efficacy in preventing of post-abdominal surgery adhesions in contrast to clinical patches. Considering the advantages in terms of therapeutic efficacy and off the shelf, the Janus patch developed in this work presents a promise for preventing postoperative adhesions and promoting regeneration of internal tissue defects.

Thermal-mechanical-chemical coupled model and three-dimensional damage evaluation based on computed tomography for high-energy laser-ablated CFRP

High-energy laser is widely used for machining carbon fiber reinforced polymer (CFRP) composites because of their high precision and fine quality. However, the mechanism by which CFRPs are damaged by high-energy laser in processing is unclear. In this article, the coupled mechanism of laser-ablated CFRPs is investigated experimentally and theoretically. The three-dimensional morphology of laser-damaged CFRPs is captured by computed tomography (CT), which quantitatively characterizes the degree of pyrolytic charring and internal delamination. Accordingly, a thermal-mechanical-chemical coupled model is established considering the matrix pyrolysis, pyrolysis gases flow, sublimation of the charring layer and mechanical failure. The progressive loss of solid media and the inhomogeneous deformation of CFRPs are incorporated into the traditional ablation kinetic model, making it possible to describe the damage to CFRPs caused by both chemical reactions and thermal stress. The predicted damage morphology is consistent with the experimental results, revealing the generation of internal defects due to the synergistic effects of interlaminar tensile stress and matrix pyrolysis. Additionally, the effects of charring layer sublimation, laser power and process time on damage responses are analyzed, and the real-time evolution of damage degree is investigated.

Non-destructive testing based on Unet-CBAM network for pulsed thermography

Infrared thermography (IRT) is a non-destructive testing technique that can detect the internal defects of materials. In the detection of austenitic stainless-steel pipes with large curvature, image noise caused by uneven heating is difficult to avoid. Traditional image processing methods are less effective. According to previous works, a supervised neural network was proposed in this paper using Unet network and convolutional block attention module. Existing image processing method and networks were used to compare with the proposed method. The results show that the proposed method can remove the noise caused by uneven heating, and detect all subsurface defects in stainless-steel pipe.

Study on forming process and performance of nano-La2O3 reinforced tungsten-based composites by selective laser melting

In this study, La2O3 nanoparticles were incorporated into a tungsten (W) matrix to enhance the microstructure and properties of pure W. The selective laser melting (SLM) process for W-2wt% La2O3 was optimized, and the influence of SLM processing parameters on the relative density and internal defects of the samples was examined. Challenges such as uneven powder layering and layer-by-layer thickening during the SLM process were addressed by incorporating a homogeneous material support formed with low laser energy density beneath the sample. This approach widened the process window for sample formation, resulting in a 2.38 % increase in the average relative density of supported samples compared to unsupported ones.With optimized parameters of 240W laser power, 200 mm/s scanning speed, and 80 μm hatch spacing, the sample achieved a relative density of 98.32 % with minimal internal pores, though some microcracks remained. Further investigation revealed that surface roughness decreased with increasing laser power and scanning speed. High laser power combined with low scanning speed yielded good surface quality. Under conditions of high relative density (over 96 %), samples processed with low laser power and high scanning speed (200W, 200 mm/s) exhibited fine and uniform grain morphology, few internal defects, and excellent mechanical properties, with a microhardness of 474HV and a compressive strength of 2237 MPa.

Ultrasonic-assisted stripping of single-crystal SiC after laser modification

Laser stripping technology is an advanced processing method with high efficiency and low material loss, which can greatly reduce material loss in the production process of single-crystal SiC wafer, but the single-crystal SiC ingot still have a certain bonding force after laser modification. Ultrasonic vibration can reduce the bonding force and thus strip single-crystal SiC wafer. In order to investigate the effect of ultrasonic vibration on the reduction of the bonding force of single-crystal SiC internal modification layer, through the ultrasonic-assisted stripping of single-crystal SiC orthogonal experiment, the ultrasonic vibration parameters of ultrasonic frequency, vibration time and ultrasonic power of the three indexes of the reduction of the bonding force was analyzed. The results show that the bonding force of the modified layer decreased by 25 %–60 % after ultrasonic vibration. Variance analysis of the experiment results showed that the main factors influencing the bond strength reduction were vibration time and ultrasonic power in turn. When the vibration time is longer and the ultrasonic power is higher, the stripping force decreases more, and the stripping force of single-crystal SiC wafers decreases up to 60 % under the condition of vibration time of 5min and ultrasonic power of 700 W. Through analysis of the single-crystal SiC cross-section, distinct cleavage steps and cleavage channels are evident. The laser-modified region exhibits defect such as nano-pores, micro-cracks, and nano-particles.After the single-crystal SiC laser modification process was upgraded, the distance between the ultrasonic tool head and the single-crystal SiC was 1.5 mm can directly strip off the single-crystal SiC wafer. And eventually stripped 6-inch single-crystal sic wafers. Therefore, ultrasonic vibration can increase the internal defects in the single-crystal SiC modified layer, causing crack expansion to occur and ultimately stripping the single-crystal SiC wafer.

PDSE-YOLOv8: a lightweight detection method for internal defects in asphalt roads

PDSE-YOLOv8: a lightweight detection method for internal defects in asphalt roads

Critical physics-informed fatigue life prediction of laser 3D printed AlSi10Mg alloys with mass internal defects

The significant scatter in high cycle fatigue life of additively manufactured metallic components presents an increasing challenge to structural integrity. This fatigue life variation is radically attributed to the differences in physical features of critical defects that lead to crack initiation. To address this issue, this paper proposes an integrated framework for identifying critical defects and predicting fatigue life using physics-informed machine learning, with a focus on the impact of 3D defect features. By employing X-ray tomography, high cycle fatigue tests, and fractography analyses on post-mortem specimens, a dataset associated with mass internal defects is first built up to correlate the spatial geometric features of critical defects with fatigue life. A kernel support vector machine is then used to formulate a critical defect identification model, aimed at identifying critical defects among numerous defects by evaluating their geometric attributes. Finally, a fatigue life prediction model is developed using a physics-informed neural network, which incorporates the influence of defect geometry on fatigue life as physical constraints in the loss function. The integrated framework demonstrates that fatigue life predictions from identified critical defects in each specimen exhibit small deviations, with the average prediction falling within twice the error bands. This study is expected to provide a valuable reference for fatigue assessment of additively manufactured components through sequential critical defect identification and fatigue life prediction.

Achieving 1.7 GPa Considerable Ductility High-Strength Low-Alloy Steel Using Hot-Rolling and Tempering Processes.

To achieve a balanced combination of high strength and high plasticity in high-strength low-alloy (HSLA) steel through a hot-rolling process, post-heat treatment is essential. The effects of post-roll air cooling and oil quenching and subsequent tempering treatment on the microstructure and mechanical properties of HSLA steels were investigated, and the relevant strengthening and toughening mechanisms were analyzed. The microstructure after hot rolling consists of fine martensite and/or bainite with a high density of internal dislocations and lattice defects. Grain boundary strengthening and dislocation strengthening are the main strengthening mechanisms. After tempering, the specimens' microstructures are dominated by tempered martensite, with fine carbides precipitated inside. The oil-quenched and tempered specimens exhibit tempering performance, with a yield strength (YS) of 1410.5 MPa, an ultimate tensile strength (UTS) of 1758.6 MPa, and an elongation of 15.02%, which realizes the optimization of the comprehensive performance of HSLA steel.

Full field crack solutions in anti-plane flexoelectricity

In flexoelectric materials, strain gradients can induce electrical polarization. However, internal defects such as cracks profoundly affect the electromechanical coupling properties of flexoelectric solids. In particular, anti-plane cracks involve less physical fields, which are easier to study. In this study, we present a comprehensive and innovative investigation of the anti-plane crack problems in flexoelectric materials, including semi-infinite and finite-length anti-plane cracks. For the first time, we formulate a full-field solution for semi-infinite anti-plane cracks in flexoelectric media by applying the Wiener–Hopf technique. Furthermore, the collocation method and the Chebyshev polynomial expansion are used for the first time to derive the full-field hypersingular integral equation solution for finite-length anti-plane cracks in flexoelectric solids. In addition, a comparative analysis between the full-field and asymptotic solutions for semi-infinite cracks is performed, shedding light on the discrepancies in the representation of the electromechanical coupling behavior near the crack tip. The mixed finite element method is used to compare with the full-field solutions of finite-length cracks. The agreement between the numerical results and the full-field solutions demonstrates the rigor of our study. This research advances the knowledge of defects in flexoelectricity and provides significant insight into relevant failure mechanisms.

Quantitative detection of axial defects in pipelines based on modified multi-mode total focusing method (MTFM)

The axial defects in pipelines are hard to detect effectively with the conventional multi-mode total focusing method (MTFM). The inner and outer curved surfaces of pipelines induce beam divergence, reducing focusing performance and introducing imaging distortion and errors. In this paper, the MTFM employed for inspecting flat plates is modified in consideration of the influences of pipe curvature on the ray paths of direct, half-skip and full-skip mode waves. The corresponding travel times are recalculated and used for performing delay-and-sum (DAS) beamforming, achieving the profile reconstruction and quantitative detection of axial defects. The simulation and experiments were implemented on the carbon steel pipeline with 100 mm outer radius and 20 mm wall thickness. The phased array (PA) probe with 32 elements and 5 MHz central frequency and the 55° curved wedge were adopted to detect the inner-wall axial defects in pipeline. The profiles of the planar defects with a length of 5 mm and orientation angles of −45°∼45° were well reconstructed by modified MTFM, and the measurement errors of flaw lengths, orientation angles and tip depths were no more than 16.6 %, 5.1° and 4.0 % after correction, respectively. Further simulated and experimental results indicate that the internal axial defects can also be detected and quantified by modified MTFM. Finally, the influences of pipe curvature on modified MTFM are discussed by simulation.

Decision Tree Clusters: Non-destructive detection of overheating defects in porcelain insulators using quantitative thermal imaging techniques

Porcelain insulators are subject to performance deterioration during operation under the influence of complex environments, thus increasing the occurrence of flashover accidents. Regular inspection of insulator condition is of great significance for the stable operation of power grids. Therefore, we propose a non-destructive detection method of insulator overheating defects using quantitative thermography. It can be used for defect detection of porcelain insulators with internal overheating defects. In this study, the relationship between the insulating properties of porcelain insulators and the heating anomalies was first analyzed. Then, Decision Tree Clusters (DTC) algorithm is used to extract the spatial temperature feature information to achieve the defective insulator location capture. Finally, Submodular-pick Local Interpretable Model-agnostic Explanations (SLIME) is used for model decision visualization to verify the feasibility of the technique. The experimental results show that DTC not only ensures the accuracy of insulator long-distance detection, but also realizes the quantitative detection of insulators.

Assessment of internal defects in flush ground butt welds in marine structures

In this paper, acceptance criteria of internal planar defects for the highest design S-N curve for surface ground butt welds in fatigue design standards has been assessed based on fatigue tests of tethers containing internal defects. The results from crack growth analysis from defects placed close to the surface are compared with test data from constant amplitude testing of tethers with circumferential welds that includes flaws or small planar defects close to the surface. Floating structures and support structures are subjected to variable loads and the calculated response leads to a long-term stress range distribution with many small stress ranges. This means that if the cracks are small, the resulting stress intensity may be less than the threshold stress intensity factor and the crack does not grow for this stress cycle, or it grows at a reduced crack growth rate in the near threshold region. A methodology to account for this is presented based on a two-parameter Weibull long-term stress range distribution that is representative for load response of floating structures and for support structures for wind turbines. It is shown that the threshold value and the reduced crack growth rate in the near threshold region for small internal defect heights can be used to lift the fatigue test data from constant amplitude testing to be in better correspondence with a higher S-N curve when considering an actual long-term loading.

Microstructure phase analysis and process optimization of ZL205A metal mold casting

In this paper, we take an elastomeric transmission structure part made of ZL205A alloy as the research object, and use the metal type gravity casting technology for casting trial production, analyze the quality and mechanical properties of the molded parts of ZL205A alloy parts under different process parameters, optimize the casting process parameters, get the optimal combination of process parameters, and obtain large ZL205A castings with less internal quality defects and high mechanical properties.

Comparative evaluation of vat photopolymerization and steel tool molds on the performance of injection molded and overmolded tensile specimens

AbstractThis study explores the use of vat polymerization stereolithography (SLA) for fabricating mold tooling, subsequently utilized in injection molding (IM) and overmolding of tensile specimens and directly compared to those produced using metal molds. The results first find the manufacturing time for an SLA‐fabricated mold is remarkably short, approximately 6 h, presenting a substantial improvement over traditional methods. Mechanical testing revealed that the tensile specimens from the SLA‐fabricated molds exhibited the highest tensile strength among all overmolding batches. This performance was consistent with the tensile bars produced using metal molds, demonstrating the viability of SLA‐fabricated molds for overmolding applications and highlighting the potential of FDM to customize the properties of final products. However, variations in mold types impacted the dimensional tolerance and tensile strength of the final specimens. Metal mold‐fabricated tensile bars exhibited superior dimensional accuracy and maximum tensile strength (50.6–61.7 MPa) compared to those produced with SLA‐fabricated molds (46.9–55.9 MPa). These differences are attributed to the rougher surface finish inherent to the layer‐by‐layer construction of SLA and the internal stresses and defects resulting from lower thermal conductivity and uneven cooling. In conclusion, this study underscores the promising future applications of SLA‐fabricated molds in overmolding, offering reduced manufacturing costs and enhanced design freedom. The findings support the potential of SLA to revolutionize mold fabrication, thereby extending its utility and optimizing the production of polymer components with customized properties.Highlights SLA molds compared to metal molds for direct injection molding and overmolding. FFF preforms with varied geometries were overmolded to finalize the specimens. Joint configurations in overmolding improved tensile performance. Overmolding showed better dimensional accuracy than FFF specimens. SLA mold preparation significantly reduced manufacturing costs.

The Impact of Bromine Surface Doping on the Structural, Optical, and Morphological Properties of Bismuth‐Based Perovskite Film as a Light‐Absorber in Perovskite Solar Cells

Bismuth‐based perovskite materials have concerned significant attention due to their low‐toxic and stable properties. However, achieving smooth and dense thin films for the preferential growth of bismuth‐based perovskite along the c‐axis, which is conducive to the preparation of solar cells, is challenging. Therefore, using halogen atoms to partially replace iodine atoms and constrain anisotropic growth has been shown to be an effective method for obtaining high‐quality perovskite films. Herein, Br doping with varying concentrations is used to treat bismuth‐based perovskite films with larger and denser grains compared to those without doping. When a small amount of Br ions is doped, the surface of the perovskite layer becomes more uniform, significantly improving the compactness of the perovskite film. Additionally, proper Br doping can reduce internal defects in the films, effectively inhibiting nonradiative recombination, enhancing light absorption, and increasing carrier lifetime. The optimal power conversion efficiency of Br‐doped bismuth halide perovskite solar cells is found to be 0.136%, compared to 0.087% for pristine devices.

Revisiting the sequential evolution of sizing agents in CFRP manufacturing to guide cross-scale synergistic optimization of interphase gradient and infiltration

Using sizing agents instead of various nanoparticles to modify carbon fibers is widely recognized as the most practical approach to address processing issues and improve interfacial properties in carbon fiber reinforced polymer composites. However, a limited understanding of sizing agent evolution during composite manufacturing hinders comprehensive theoretical guidance for sizing treatment, thereby limiting further enhancement of composite performance. Here we disentangled the sizing agents into chemical anchoring and physical adsorption components, and elucidated the sequential wetting, diffusion, and crosslinking evolution processes of sizing agents across scales. By manipulating the proportion of chemical anchoring and physical adsorption in the sizing agents, the interfacial modulus gradient and infiltration efficiency were synergistically optimized. Consequently, significant improvements of 26.2 % in interfacial shear strength (IFSS) and 52.9 % in transverse fiber bundle tensile (TFBT) strength were achieved, indicating enhanced interfacial stress transfer and reduced internal defects in the composites. In summary, this work revisited the cross-scale evolution and mechanism of sizing agents during composite manufacturing, and thus provided a new paradigm for optimizing composite performance.