Defect Parameters Research Articles

Possible structures of skyrmion states in chiral ferromagnetic films with spatially modulated uniaxial anisotropy.

In this paper, the stabilization conditions, structure, and properties of possible vortex-like inhomogeneities, including kπ-skyrmions k = 0, 1, 2, 3, 4, in a uniaxial multilayer disk with a columnar defect in the center are investigated based on micromagnetic modeling. Their stability diagrams depending on the Dzyaloshinskii-Moriya interaction, the magnitude of magnetic anisotropy and the defect parameters are determined. New types of vortex-like inhomogeneities that can arise in such samples are found. The obtained data can be used to create artificial regions of nucleation, capture and pinning of magnetic skyrmions, which can provide greater reliability of data storage in spintronic logical devices.&#xD.

Determination of the geometric parameters of the defects based on the tomographically obtained data and their influence on the fatigue behavior of the S960 with laser cladded protective layers

This article deals with identifying defects of layered high strength steel materials with the help of tomography measurement. Test samples were made of S960 High Strength Steel to which layers of either aluminium bronze, hardchrome, cobalt alloy or stainless steel were applied by a laser cladding technology. The experimental campaign included a study of morphometric parameters of internal defects in and near the bi-material interface region using X-ray micro-tomography and their potential influence on the fatigue behavior during a three-point bending test.

Experimental and Numerical Analysis of the Impact of Corrosion on the Failure Pressure of API 5L X65 Pipeline

This paper employs the Finite Element Method (FEM) to simulate and analyze the effects of corrosion defect parameters on the stress and failure pressure of pipelines. It investigates how the boundary conditions of the pipeline model influence stress and examines the sensitivity of failure pressure to corrosion defect parameters. A nonlinear regression equation has been developed from a dataset obtained through simulation experiments to predict the failure pressure of corroded pipelines. To validate the effects of corrosion defect parameters on failure pressure, a hydrostatic test platform for an API 5L X65 pipeline with corrosion defects was established to measure stress levels and failure pressures across varying corrosion defects. This study reveals that failure pressure is negatively correlated with corrosion length and depth, while positively correlated with corrosion width. Among these parameters, corrosion depth exerts a more significant influence on the pipeline’s failure pressure than corrosion length and width. Within the range of corrosion defect parameters examined, the maximum deviation of the prediction equation’s results from the simulation results is 8.71%, with an average deviation of 5.81%. The standard deviation of the fitted residuals is 0.01837. Additionally, the maximum deviation between the predicted results and experimental measurements is 8.39%, with an average deviation of 7.77%. The strong agreement between the predicted results from the equation and the actual measured data underscores the effectiveness of the nonlinear regression equation.

Ultrasonic characterization of defects in polycrystalline materials based on TFM image reconstruction using denoising diffusion probabilistic models

This paper presents a refined ultrasonic total focusing method (TFM) for accurately characterizing key defect parameters including size, orientation, and location in complex materials. The proposed approach aims to accurately reconstruct the defect shape in images compromised by grain interference. First, a TFM image database was generated with varying defect parameters and grain noise levels by adopting a custom forward modeling process based on superposition of defect and grain scattering data. Second, a new architecture called TFM-DDPM was then proposed which incorporates TFM and the conditional denoising diffusion probabilistic model (DDPM). Third, pixel-level uncertainty can be quantified through repeated sampling of noise which follows a standard normal distribution. An acceptance criterion for the reconstruction was further established by analyzing the quantified uncertainty. In simulation, the median Dice coefficient between the de-noised TFMs of 30° cracks and their corresponding ground truth images increased from 0.5585 to 0.9137 using the proposed approach, and the median IoU metric rose from 0.3875 to 0.8408. By applying the 6-dB drop approach to the reconstructed images, the root mean squared errors (RMSEs) of size, angle and location were decreased by 93.59%, 86.90% and 86.25%, respectively. It is also demonstrated that our method can reject 69.19% of incorrect characterization results caused by high levels of noise and/or images with steeply inclined (e.g., 45°) cracks, while accepting 97.29% accurate results. Experimental results obtained on nickel-based alloy K403 specimens also exhibited significant improvements. For 2–3 mm cracks, the average sizing error reduced from 0.46 mm to 0.13 mm, and the error in crack angle decreased from 28.63° to 1.50°. Comparable performance enhancements were observed for 4–5 mm cracks using the proposed approach.

Defect characterization from magnetic field leakage signals in petroleum and natural gas pipelines

Pipelines transport invaluable energy resources such as crude oil and natural gas over long distances. The integrity of the piping system in terms of safety of the process is then of high importance. However, pipes are prone by time to defects that may degrade their properties and lead to failures. In this paper, we study the effect of defect parameters on the magnetic field leakage captured by Hall sensors operating along the pipe. In fact, the obtained results show that the defect parameters influence directly the MFL amplitude and shape. For this reason, the inversion problem allowing us to reconstruct the defect from the MFL signals became fast and easier in comparison to the deterministic and probabilistic algorithm inversion procedure. However, the simplified system cannot describe the real defects and the three-dimensional numerical study became necessary. In tank floor inspection domain, as our recent published work, we have studied the performance of defect shape reconstruction from MFL array sensor imaging and depth estimation while using an iterative inversion method. Indeed, the first stage consists of determining the defect width and length from magnetic flux leakage mapping reconstructed from the recorded signals of the micro-integrated magnetic sensors. Then, after coupling Comsol and Matlab software, the defect depth is obtained by coupling the 3D finite elements method and a fast iterative algorithm recently developed. Consequently, the defect shape and size are obtained after a few iterations with high precision. Furthermore, this method of defect reconstruction and seizing can be extended for irregular defect shapes encountered in pipeline such as cracks and corrosion.

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.

Laser fiber cleave: Modeling and fundamentals

In the laser-assisted fiber cleaving process, an ultrashort, high-energy laser is used to introduce a flaw on the optical fiber surface, and then the fiber is cleaved under a tension or bending load. The quality of the cleaved end depends on the crack propagation from the artificial flaw. To understand the cleaving process and the effects of flaw parameters on cleaving quality, crack propagation is modeled by considering a pre-existing surface flaw using a graph-based finite element method (GraFEA). GraFEA is based on the nonlocal multiple cracking simulation framework for brittle and quasi-brittle materials. First, a three-point bending test is conducted to calibrate material parameters in GraFEA for commercial fused silica glass. Subsequently, the model is validated by four-point bending and ring-on-ring tests. After validation, the fiber cleaving process is investigated by parametric simulations in which different loading types (bending or tension) are considered. Finally, a beneficial process window is obtained and recommended for improved cleaving quality.

Analysis of ionic defect distribution on perovskite photodetector by temperature-dependent deep level transient spectroscopy

The High-efficiency Organohalide perovskites solar cells are produced via a solution-based method. Thus, a lot of defects are inevitable generated during fabrication processes, which are the main factors that affect the efficiency and long-term stability. The defect has been linked to the observation of reduce device stability against degradation and it can also create mid-gap states in a band structure as well act as recombination centers. Although the efficiency of the perovskite solar cells (PSCs) has been improved by curing defects using various passivation methods, deeply trapped defects in the perovskite layer have not been systematically studied, and their function is still unclear. In this study, we perform temperature-dependent deep-level transient spectroscopy (T-DLTS) measurements on PSCs, ionic defect parameters (activation energy, trap density, diffusion constants) for each observed ionic species were compared in different PSCs.

Dependence of the Silicon Carbide Radiation Resistance on the Irradiation Temperature

The effect of high-temperature electron and proton irradiation on SiC-based device characteristics is being investigated. Industrial integrated 4H-SiC Schottky diodes, each with an n-type base and a blocking voltage of either 600 V, 1200 V, or 1700 V, manufactured by Wolfspeed, are being studied. 0.9 MeV electron and 15 MeV proton irradiation were applied. It has been found that the irradiation resistance of silicon carbide Schottky diodes at high temperatures significantly exceeds their resistance at room temperature. This effect is attributed to the annealing of compensating defects induced by high-temperature irradiation. The parameters of radiation-induced defects are determined using the method of deep level transient spectroscopy (DLTS). Under high-temperature ("hot") irradiation, the spectrum of radiation-induced defects introduced into SiC appears to differ significantly from the spectrum of defects introduced at room temperature. It is suggested that approximately half of the compensation is due to radiation-induced defects formed in the bottom part of the bandgap.

MAPOD analysis in eddy current testing of flaws considering multiple response signals and multiple flaw parameters

The reliability of the eddy current testing (ECT) in flaw detection is quantitatively evaluated by the probability of detection (POD). Precise and efficient modelling of POD gives direction for the implement of ECT on sites to avoid false or missing flaw detection. Traditional POD analysis focuses on single uncertain factor or single response signal with limited credibility in engineering. This paper considers multiple response signals and multiple flaw parameters to perform POD. The flaw length, the flaw depth, the coil impedance and the magnetic flux density are comprehensively studied under various lift-off distances. A finite element model (FEM) of ECT is established and verified with experiments to obtain sufficient simulation data for discrete POD modelling. The continuous POD function is then fitted based on the discrete values to show the superiority of integrating multiple factors. A comparison with conventional POD analysis further demonstrates the higher reliability of ECT flaw detection considering multiple flaw parameters and multiple response signals, especially for small flaws. Conflict of Interest Statement The authors declare no conflicts of interest.

Model for the Failure Prediction Mechanism of In-Service Pipelines Based on IoT Technology

With the rapid increase in pipeline mileage in China, the accurate prediction of corrosion issues in in-service pipelines has become crucial for ensuring safe pipeline operation. Traditional pipeline leakage monitoring methods are significantly limited by human factors and equipment precision, making it challenging to predict and identify leakage points accurately. Therefore, aligned with the trend of intelligent pipeline development, this study aims to construct a failure pressure prediction mechanism model for corroded pipelines based on IoT technology. This model leverages intelligent sensing and prediction to assess the safety status of corroded pipeline sections. Ultrasonic phased array technology detects specific corrosion points and detailed defect parameters within pipeline sections. The parameters are then utilized in the Simdroid domestic finite element analysis model to simulate the ultimate burst pressure of the pipeline. A single-variable approach is employed to analyze the sensitivity of different parameters to the pipeline’s ultimate burst pressure, with the minimum burst pressure point of multi-point corroded sections selected as the overall segment failure pressure. Finite element simulation data are integrated into a neural network database to predict the pipeline failure pressure. The real-time operational data of the pipeline are monitored using negative-pressure wave sensing. The operational pressure of the corroded points is compared with the algorithm-predicted failure pressure; if the values approach a critical threshold, an alarm is triggered. Moreover, the remote control terminals evaluate the pipeline’s self-rescue time, providing a buffer for pipeline leakage self-rescue. The failure prediction mechanism model for in-service pipelines was applied to the Fujian–Guangdong branch of the West–East Gas Pipeline III to verify its accuracy and feasibility. The research results offer technical support for the maintenance and emergency repair of pipeline leakage scenarios, leveraging intelligent pipeline technology to reduce costs and increase the efficiency of pipeline operations, thereby supporting the sustainable development of China’s oil and gas pipelines with theoretical and technical backing.

Prediction of the Upwarp Buckling Critical Temperature Rise for Longitudinally Connected Slab Track Under Joint Damage State

The joint of longitudinally connected slab track is vulnerable to damage from environmental impacts and repeated train loads. Under high temperature environments, the joint becomes a high risk area for track slab upwarp, which significantly affects the upwarp stability of the track slab and the safe operation of trains. This study employs the arc length approach and a finite element model to investigate the upwarp equilibrium development path of the track slab, the upwarp evolution process of the track slab under the joint damage is further analyzed. Then, the influence of different initial defects on the vertical stability of the track slab is studied. Utilizing dimensional analysis, a general formula for calculating the critical temperature rise of the track slab is proposed. The results are as follows: (1) The entire upwarp process of track slab under joint damage can be divided into three stages: stability, upwarping development, and instability. (2) A nonlinear correlation exists between the upwarp critical temperature rise of the track slab and three types of initial defects. Height defects in narrow joints exert the most significant impact on the critical temperature rise, followed by initial Out-of-straight (initial OOS), with the initial bending shape having the least effect. The complete defect of the narrow joint reduces the upwarp critical temperature rise of the track slab by 53.26°C, a 48.4% reduction. (3) A unified expression, derived from the characteristic parameters of initial defects and dimensional analysis, can more accurately predict the upwarp critical temperature rise of the track slab.

Large-Scale Statistical Analysis of Defect Emission in hBN: Revealing Spectral Families and Influence of Flake Morphology.

Quantum emitters in two-dimensional layered hexagonal boron nitride are quickly emerging as a highly promising platform for next-generation quantum technologies. However, the precise identification and control of defects are key parameters to achieve the next step in their development. We conducted a comprehensive study by analyzing over 10,000 photoluminescence emission lines from liquid exfoliated hBN nanoflake samples, revealing 11 narrow sets of defect families within the 1.6 to 2.2 eV energy range. This challenges hypotheses of a random energy distribution. We also reported averaged defect parameters, including emission line widths, spatial density, phonon side bands, and Franck-Condon-related factors. These findings provide valuable insights into deciphering the microscopic origin of emitters in hBN hosts. We also explored the influence of the hBN host morphology on defect family formation, demonstrating its crucial impact. By tuning the flake size and arrangement, we achieve selective control of defect types while maintaining high spatial density. This offers a scalable approach to defect emission control, diverging from costly engineering methods. It emphasizes the significance of the morphological aspects of hBN hosts for gaining insights into defect origins and expanding their spectral control.

Approximate solutions for diatomic molecules under combined potentials in a global monopole and Aharonov–Bohm flux field

AbstractBound state energy eigensolutions of nine different diatomic molecules, specifically, , TiH, , CO, NO, ScH, CrH, HCl and LiH, placed in a point‐like global monopole, have been calculated by solving the time‐independent Schrödinger equation (SE). The molecules are confined by the Aharonov–Bohm (AB) flux field and the interaction potential among the charged particles is governed by the combined screened modified Kratzer potential (SMKP) plus Hulthén potential model. Three other special cases of the interaction potential have also been discussed here. Asymptotic iteration method has been used for the mathematical calculations. It is difficult to solve the SE exactly for any non‐zero values of the azimuthal quantum number due to the presence of the centrifugal barrier term. The well‐known Pekeris approximation technique for the terms and has taken into consideration for the purpose of performing numerical computations connected to an arbitrary state. The outcomes of this study are in reasonable agreement with the results of previous research on SMKP, Kratzer‐Fues potential, and modified Kratzer potential in the Minkowski space. It is observed that the energy spectra of the diatomic molecules suffer considerable change due to the effects of the background AB‐flux field and topological defect parameter.

Numerical simulation and experimental studies of rotational eddy current detection of cracks around rivet holes

Multi-layered aeronautical structures, such as fuselage panels and wings, are composed of several layers of materials such as metal and composites. These structures are prone to damage such as corrosion, cracks and delamination between layers, which can compromise their structural integrity. Eddy current sensors are an essential tool for the inspection and preventive maintenance of multi-layered aeronautical structures, contributing to the safety and reliability of these crucial components. Differential-mode eddy current sensors are particularly well-suited for the inspection of multi-layer aerospace structures around dished-head rivets. The differential measurement improves the detection and characterization of defects in these complex geometries, which are prone to fatigue, corrosion, and other types of damage. The advantages of differential mode are improved sensitivity to small defects, elimination of lift-off variations (distance between the sensor and the surface), reduced electromagnetic interference and detection of defects around rivets, which are critical and difficult to access areas. This work deals with a study of the rotational differential sensor signal according to geometrical parameters of fastener holes defect. It is carried out by an eddy current nondestructive testing system implemented under COMSOL Multiphysics. Indeed, despite its rapidity, the results have shown that the sensor is sensitive to the hole defects when the distances Sensor/Rivet and Lift-off are reduced. As predicted, the experimental results have shown the presence of unsuitable signals caused by the additional Lift-off and the distance Sensor/Rivet. As a solution, these tow parameters should be reduced and kept constant in order to get a better defect signal.

Modeling of defects in ultrasonic flaw detection. Status and prospects

In the introduction to the article four factors, which are most important for ensuring the accuracy of defect parameters measurements at ultrasonic inspection, are mentioned: parameters of artificial reflectors in samples, compliance of acoustic properties of material of tuning samples and controlled products, transient characteristics of electroacoustic paths, methodological features of measurements. The present article is devoted to the analysis of the first and partly fourth of listed factors. The review of reflectors, the use of which is regulated in various standards, is carried out. Advantages and disadvantages of flat-bottomed holes, segmental and angular reflectors (“notches”), lateral (BCO) and vertical cylindrical drills, grooves are noted. Taking into account the peculiarities of ultrasonic wave scattering, it is noted that artificial “reflectors” such as “grooves” and BCOs are used to adjust the parameters of modern diffraction control methods. It is recommended to expand the use of grooves, BCO and vertical drilling in the revision of standards governing the use of classical echo-methods. The estimation of accuracy of measurement of defects parameters, first of all — coordinates of crack tip, with application of modern digital methods of information processing at ultrasonic control is given. It is indicated that to increase the accuracy of measurements, to determine the position and orientation of cracks in welds, it is necessary to create a database of digital doubles of samples with artificial reflectors and products with real defects. The general scheme of quality control work execution is given, taking into account the use of standards (measures), digital models of artificial reflectors and digital twins of the control process to ensure the necessary detectability of defects and reliability of manual, automated and, potentially, automatic control.

Stochastic Defect Localization for Cooperative Additive Manufacturing Using Gaussian Mixture Maps

Abstract Robotic additive manufacturing (RAM) offers significant improvements in maximum build volume compared to conventional bounded designs (e.g., gantry) by leveraging high degrees-of-freedom machines and multi-robot cooperation. However, cooperative RAM suffers from the same defect generation challenges as conventional systems, necessitating improvements in the detection and prevention of flaws within fabricated components. Quality assurance can be further bolstered through the integration of AM models, which utilize sensor feedback to localize defects, vastly reducing false positives. This research explores defect localization through a novel dynamic defect model created from simulated sensing data. In particular, two cooperative robots are simulated to estimate defect parameters, while observing the workspace and accurately classifying different regions of the part, generating a Gaussian mixture map that identifies and assigns appropriate actions based on defect types and characteristics. The experimental result shows that the implementation of the dynamic defect model and selective reevaluation achieved an effective defect detection accuracy of 99.9%, an improvement of 9.9% without localization. The proposed framework holds potential for application in domains that utilize high degrees-of-freedom machines and collaborative agents, offering scalability, improved fabrication speeds, and enhanced mechanical properties.

Insight into local defect resonance and its in-situ measurement based on flexible nano-composite sensors

The local defect resonance has been proven to be effective for damage detection, and the methods based on LDR for damage evaluation have demonstrated appealing capabilities of selective assessment and applicability to complex structures. To explain the generation of LDR, models based on vibration theories have been developed in which the defect boundaries are assumed to be fixed. Nevertheless, existing models can only give an accurate prediction of frequency for fundamental LDR mode owing to the deviation of their assumptions from the reality. In addition, the measurement of LDR is currently limited to noncontact technologies, hampering its application to in-situ and online monitoring of inspected structures. To overcome these deficiencies, an analytical model is proposed in this investigation to gain an insight into the generation of LDR from the perspective of wave reflection at defect boundaries and wave superposition. In this model, the interaction of guided waves with defect is scrutinized using a normal mode expansion method to obtain the phase shift of the reflected waves at the defect boundaries. On this basis, the formation of standing waves is analyzed to interpret the occurrence of the resonance of guided waves, whereby the relation of the LDR frequencies and the defect parameters can be obtained. On top of this analytical investigation, the sensing of the LDR using a novel nano-composite sensor is attempted. Flexible and lightweight, these sensors can form a dense sensing network, with which the LDR response in the inspected region can be perceived. Using the LDR-based method and nano-composite sensors, this approach can give a damage characterization in an in-situ and online manner for complex structures. Experimental validations of the proposed approach is performed in which delaminations in composite structures are identified and assessed using the LDR response perceived with the nano-composite sensors.

Surface Defect-Extended BIM Generation Leveraging UAV Images and Deep Learning.

Defect inspection of existing buildings is receiving increasing attention for digitalization transfer in the construction industry. The development of drone technology and artificial intelligence has provided powerful tools for defect inspection of buildings. However, integrating defect inspection information detected from UAV images into semantically rich building information modeling (BIM) is still challenging work due to the low defect detection accuracy and the coordinate difference between UAV images and BIM models. In this paper, a deep learning-based method coupled with transfer learning is used to detect defects accurately; and a texture mapping-based defect parameter extraction method is proposed to achieve the mapping from the image U-V coordinate system to the BIM project coordinate system. The defects are projected onto the surface of the BIM model to enrich a surface defect-extended BIM (SDE-BIM). The proposed method was validated in a defect information modeling experiment involving the No. 36 teaching building of Nantong University. The results demonstrate that the methods are widely applicable to various building inspection tasks.

Comparative assessment and experimental analysis of atomic coordination and mechanical properties of sputter deposited Ti-rich TiN, TiC, and TiCN thin films

In the present work, Titanium nitride (TiN)150 nm, Titanium on Titanium nitride (TiN75 nm/Ti75 nm), Titanium on Titanium carbonitride (TiCN75 nm/Ti75 nm), and Titanium on Titanium carbide (TiC75 nm/Ti75 nm) films were deposited on Si (100), quartz, and glass substrates through dc-magnetron sputtering. Vacuum annelation was carried at 600ºC for 1 hr to form TiN (m-TiN), Ti-rich TiN (b-TiN), Ti-rich TiC (b-TiC) and Ti-rich TiCN (b-TiCN) films. b-TiCN showed less optical absorbance and band gap compared to b-TiN and b-TiC films and more detrimental types of defects, which might lead to the degradation of mechanical properties in b-TiCN film. The shifting of the Ti-N core orbital towards higher binding energy showed the higher bond strength of the b-TiN film. The ITA/ITO ratio increased from 0.8 to 2.37 for b-TiC to b-TiN films, signifying the deterioration in medium-range order. The defect parameter, ID/IG, increased from 0.63 to 0.71, indicating that b-TiCN has higher defects than b-TiC films. The valence band spectra revealed that b-TiN and b-TiC valence bands are present above the Fermi level but below in the case of b-TiCN films. X-ray absorption spectroscopy confirmed that the Ti L, N K, and C K-edge were observed at 462.38, 404.53, and 287.33 eV, respectively. The highest Young’s modulus and hardness were 97.43 and 18.47 GPa, respectively, measured by a Berkovich nanoindenter for b-TiN thin films.