Defect Profiles Research Articles

Numerical simulation of slab deformation process with different reduction values in vertical rolls of mill 2000 roughing stands

Perfection of rolled stock production processes at continuous wide-strip hot rolling mill (CWHRM) aimed at minimization of metal consumption, is an effective mean to decrease its cost. In the process of slabs rolling at CWHRM, the metal consumption is stipulated first of all by complicated workpiece forming in roughing stands during consecutive reduction by vertical and horizontal rolls. Results of the numerical study of slab deformation with different values of reduction in vertical rolls of roughing stands of mill 2000 are presented. The implementation of rolling process model based on application of DEFORM-3D program of finiteelement analysis described for evaluation of metal shifting from the edges of slab in the direction of the middle of the width. The convergence of the simulation results with the measurements data of workpiece forming during roughing rolling at Severstal mill 2000 was experimentally confirmed. It was found that an increase of reduction in vertical rolls has no significant effect on the metal shifting from a narrow edge to a wide one. Increase the total reduction in vertical rolls leads to an unfavorable stress-strain state of the edge region and the Cockcroft–Latham criterion rises by 20–30%. It was proposed to reduce the total reduction in the vertical rolls of the roughing stands of mill 2000 down to 40–50 mm. It was shown that increase of time of slab moving from the heating furnace to the scale breaker causes growth the Cockcroft-Latham criterion and does not affect the amount of metal shifting from a narrow face to a wide one. The proposed method of simulation the process of slab deformation in the roughing group of the mill 2000 proved by results of industrial rolling can to be used for further study of the effect of rolls profiling and forming of surface defects with the provision of minimal metal shifting onto a wide face.

Extreme ultraviolet phase defect characterization based on complex amplitudes of the aerial images.

The profile deformation of a phase defect in an extreme ultraviolet (EUV) mask blank is the key factor to simulate its optical effects accurately and to compensate for it precisely. This paper provides a new, to the best of our knowledge, profile characterization method based on complex amplitudes of the aerial images for phase defects in EUV mask blanks. Fourier ptychography is adopted to retrieve the complex amplitudes of the aerial images and improve the lateral resolution. Both amplitude and phase impacted by the defect are taken into consideration to reconstruct the defect profile parameters (the height and the full width at half maxima of the defect's top and bottom profiles). A conformal convolutional neural network model is constructed to map the amplitudes and phases of aerial images to the defect profile parameters. The Gaussian-shaped defect models with the mapped profile parameters can be used to simulate the amplitude and phase properties of the defects when compensating for them. The proposed method is verified to reconstruct the defect profile parameters of both bump defects and pit defects accurately. The involvement of both the amplitude and phase information makes the reconstructed defect profile parameters more appropriate to simulate the optical effects of the defects.

Defect reconstruction of magnetic flux leakage measurements based on single dimension PSO algorithm

Magnetic flux leakage (MFL) detection is widely used in the technology of oil and gas pipeline intelligent detection at present. For the defect reconstruction problem in MFL detection, a new improved particle swarm optimization (PSO) algorithm, called SDPSO, is introduced to enhance the accuracy of defect profile reconstruction in this paper. In order to reduce the interaction between multidimensional information, dimensional coupling will deteriorate the search speed and convergence accuracy of the algorithm, a single dimension evolution strategy is complemented to optimize the tradition PSO algorithm. Each generation of evolution only updates a single dimension of the objective function. The dimension with the maximum error between the candidate signal and reference signal is selected as the one which need to be updated in next generation. In order to testify the performance of the proposed method, the simulated signals are utilized to compare with PSO algorithm. The experiment results verify that the proposed method has a higher adequacy of the performance in terms the quality of the solution and robustness for noise.

Evaluation of displacement damage in solids induced by fast positrons: Modeling and effect on vacancy measurement

• The latest theoretical models of radiation damage in solid and numerical results of Mott differential cross section were used; • Displacement cross section by positrons for elements in most commonly used solids was calculated and the difference between positron and electron radiation was emphasized; • Displacement thresholds of kinetic energy for positrons in 30 elemental solids were presented; • Defects spatial distribution was obtained using Monte Carlo modeling. Positron Annihilation Technique is very sensitive to vacancy defects and small vacancy clusters and has been used as supplementary for TEM in radiation damage research. In this paper, we evaluated the displacement damage in solids induced by positrons and its effect on defects measurement, which has not been considered carefully in most PAT application. Displacement damage could only be produced when kinetic energy of positron exceeds a threshold determined by average displacement energy and the mass of atoms. Based on the latest models of displacement damage and numerical Mott elastic differential cross section of positrons interacting with atoms, displacement cross section for fast positron in solids was calculated and compared with that for electrons. In the energy range from 1 MeV to 100 MeV, electrons will produce more displacement defects than positrons do, especially in high-Z materials. Number of total defects depends on the primary displacement cross section and the size of damage cascades. To get distributions of defects and terminating position of positrons in materials, a Monte Carlo tool with full damage model was developed and validated. From the results of Monte Carlo modeling, the defects -generated by mono-energy positron beam have shallower distribution than the stopping position of positrons, indicating separation of defects and positrons and this fact benefits defects measurement because displacement damage produced by fast probing positron beam have little affection on the measurement. But for the positron beams from radioactive sources (such as 22 Na and 64 Cu) with continuous energy spectrum (from 0 to E max ), the depth profile of defects and terminated position of positrons overlap with each other and this fact indicated that defects measurement in materials will be affected by extra defects produced by positrons. The density of defects produced by positron beam is quite low with a typical value of about 0.01–0.1 cm −3 per positron in low-Z materials, which could be comparable with the defect density limitation if enough accumulated positrons are implanted into materials during measurement. For commonly used structural metals (such as Fe, Mn, Cu and metals with Z number higher than 40), using positron from 22 N and 64 Cu directly to measure defects density is quite safe because the energy is smaller than the displacement threshold.

Behaviour of an angular contact ball bearing with three-dimensional cubic-like defect: A comprehensive non-linear dynamic model for predicting vibration response

The dynamic model of an asymmetric defects on an angular contact ball bearing raceway has not been fully described before. An advanced 10-degree-of-freedom dynamic model that includes detailed contact forms between a three-dimensional cubic-like defect and balls is proposed in this article. Examples are load distributions, ball passing defect profiles, varying effective stiffness between balls and raceways, and the impulse response caused by the collision of balls and defect edges. The results suggest that the circumferential size of the 3-D defect has a significant effect on the contact force distribution, which consequently generates impulse vibration in the bearing system. The analysis on the axial and circumferential sizes of defect show that the extension of the defect in the circumferential direction should be avoided. Additionally, the reduction of the radial-axial load ratio could mitigate the vibration impulses.

Defect Detection in CK45 Steel Structures through C-scan Images Using Deep Learning Method

In the present paper, a method for reliable estimation of defect profile in CK45 steel structures is presented using an eddy current testing based measurement system and post-processing system based on deep learning technique. So a deep learning method is used to determine the defect characteristics in metallic structures by magnetic field C-scan images obtained by an anisotropic magneto-resistive sensor. Having designed and adjusting the deep convolution neural network and applied it to C-scan images obtained from the measurement system, the performance of deep learning method proposed is compared with conventional artificial neural network methods such as multilayer perceptron and radial basis function on a number of metallic specimens with different defects. The results confirm the superiority of the proposed method for characterizing defects compared to other classical training-oriented methods.

A Pinning Actor-Critic Structure-Based Algorithm for Sizing Complex-Shaped Depth Profiles in MFL Inspection with High Degree of Freedom

One of the most efficient nondestructive methods for pipeline in-line inspection is magnetic flux leakage (MFL) inspection. Estimating the size of the defect from MFL signal is one of the key problems of MFL inspection. As the inspection signal is usually contaminated by noise, sizing the defect is an ill-posed inverse problem, especially when sizing the depth as a complex shape. An actor-critic structure-based algorithm is proposed in this paper for sizing complex depth profiles. By learning with more information from the depth profile without knowing the corresponding MFL signal, the algorithm proposed saves computational costs and is robust. A pinning strategy is embedded in the reconstruction process, which highly reduces the dimension of action space. The pinning actor-critic structure (PACS) helps to make the reward for critic network more efficient when reconstructing the depth profiles with high degrees of freedom. A nonlinear FEM model is used to test the effectiveness of algorithm proposed under 20 dB noise. The results show that the algorithm reconstructs the depth profile of defects with good accuracy and is robust against noise.

Blister formation in He-H co-implanted InP: A comprehensive atomistic study

The blistering efficiency in He-H-ions co-implanted and annealed InP has been found to peak and vanish in a narrow range of ion fluence ratio (ΦH/ΦHe = 1.5–3.5) with a fixed He fluence of 2 × 1016 He+/cm2. The blisters are formed at low fluence (ΦH/ΦHe = 1.5), peaked in the middle (ΦH/ΦHe = 2.5), and disappeared at the high fluence ratio (ΦH/ΦHe = 3.5). To get a fundamental understanding of blister formation in nanoscale, the defect profiles were studied by various experimental techniques combined with FEM and ab-initio simulations. Cross-section TEM images showed that at a low fluence ratio, He and H are stored in microcracks and bubbles whereas, at a high fluence ratio, the ions are trapped only inside bubbles. These atomic processes that occur during and after co-implantation and annealing are presented together with detailed scenarios in an attempt to explain our results. Based on DFT simulations, the de-trapping of He atoms from the small clusters is energetically cheaper compared to the migration of He from the large clusters formed at high fluence. Moreover, at a high fluence ratio, the presence of large clusters inhibits the He diffusion to the small clusters (precursor of blisters) by capturing migrating He atoms.

Stochastic assessment of burst pressure for corroded pipelines

Pipeline wall loss is a major concern of the oil and gas industry. The computational simulation through the finite element method is one of the most efficient and reliable tools to quantify the remaining strength of corroded pipes. This work presents a new procedure and tool for structural integrity assessment of corroded pipelines subject to internal pressure, in which the complex corrosion profile is obtained from field inspections. A system and a methodology which generates automatically finite element models will be presented. These models undergo a nonlinear analysis, and failure pressures are obtained. In the second part of this work, the statistical properties of a set of defect profiles are computed and used to generate thousands of synthetic corrosion defects with realistic properties, and these are used to create finite element models that are submitted to a computational cluster, where the open-source package Calculix is used to do nonlinear analyses of these models in parallel. The results of the analyses are automatically collected, and Monte Carlo simulation is used to calculate some statistics of burst pressure (mean and standard deviation). The main purpose of this work is to present the new methodology, to describe the tool developed to automate the whole process of modelling and analysis of the pipelines with real corrosion profiles and to relate the burst pressure with the average and minimum remaining thickness. To demonstrate the efficiency and flexibility of the methodology we present a case study based on real data.

New evaluation method of failure pressure of steel pipeline with irregular-shaped defect

• Failure pressure analysis of pipeline with irregular-shaped defect is conducted. • The effect of deep defects size on the failure pressure is considered. • The evaluation length of irregular-shaped defect is obtained. • A new failure pressure evaluation method for corroded pipeline is proposed. • The accuracy of the new evaluation method is verified by experimental tests. The relation between the failure pressure of pipeline with irregular-shaped defect and the characteristic geometric parameters is more complex than regular-shaped defect. Therefore, it is necessary to study the evaluation method of failure pressure of pipeline with irregular-shaped defect. This paper presents a case study on the failure pressure of irregular-shaped defect based on finite element model and experimental tests. The case is composed of shallow patch and deep defect included in the shallow patch. The effect of the length, depth and the longitudinal spacing of deep defects on the failure pressure of irregular-shaped defect are analyzed. Based on the limit longitudinal spacing between deep defects, the evaluation length of irregular-shaped defect is obtained. According to the irregularity of the depth profile of irregular-shaped defect, the axial projection shape of defect is equivalent to different regular shape. Combined with the effective depth of equivalent shape and the evaluation length, a new evaluation method for predicting failure pressure of steel pipeline with irregular-shaped defect is proposed, and the accuracy of the new method is verified by comparing with the experimental results for different steel grades.

Pipeline corrosion defect parameterisation with magnetic flux leakage inspection: a contextual representation approach

Corrosion is one of the significant reasons for oil and gas pipeline failures. In pipeline integrity management programmes, the magnetic flux leakage (MFL) technique is widely used to detect and quantify corrosion defects. The inspection results of MFL list the profiles of individual corrosion defects; however, the structural safety of a pipeline not only depends on the size of individual corrosion defects but also the pattern of closely spaced defects. To achieve a contextual defect representation, the concept of parameterisation, which considers the adjacent defects as additional information of the central defect, is proposed in this study. The process through which to realise this contextual representation is described in this paper. Three parameterisation models are proposed and a two-dimensional Gaussian function is employed to model the interaction strength between adjacent defects. The experimental results demonstrate that the shape context (SC) model associated with the interaction strength function (ISF) shares the highest similarity with human inspectors in comparison with the other two models. Thus, the proposed parameterisation approach can be used to retrieve similar corrosion defects and analyse defect population distribution along a pipeline.

Revisiting rough-wall turbulent boundary layers over sand-grain roughness

Abstract

Studies on the near-surface trapping of deuterium in implantation experiments

Surface-shifted deuterium profiles are re-examined in deuterium-ion irradiation experiments by using a combined experimental and modelling approach. Recrystallized tungsten foil samples were irradiated with energetic deuterium ions and the defect and deuterium depth profiles were studied using positron annihilation spectroscopy and secondary ion mass spectroscopy. We report direct experimental evidence of trapping of deuterium at the vacancies created by the deuterium ions themselves during the implantation by using positron annihilation studies. The deuterium profile is simulated using a Monte-Carlo diffusion model by taking into account the defect-aided diffusion of deuterium due to the local strain field created by the vacancies. The simulations also elucidate the role of the anisotropy in the diffusion and trapping of deuterium in ion-implantation experiments in metals.

NF-κB signalling as a pharmacological target in COVID-19: potential roles for IKKβ inhibitors.

Coronavirus disease 2019 (COVID-19) has been characterized by lymphopenia as well as a proinflammatory cytokine storm, which are responsible for the poor prognosis and multiorgan defects. The transcription factor nuclear factor-κB (NF-κB) modulates the functions of the immune cells and alters the gene expression profile of different cytokines in response to various pathogenic stimuli, while many proinflammatory factors have been known to induce NF-κB signalling cascade. Besides, NF-κB has been known to potentiate the production of reactive oxygen species (ROS) leading to apoptosis in various tissues in many diseases and viral infections. Though the reports on the involvement of the NF-κB signalling pathway in COVID-19 are limited, the therapeutic benefits of NF-κB inhibitors including dexamethasone, a synthetic form of glucocorticoid, have increasingly been realized. Considering the fact, the abnormal activation of the NF-κB resulting from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection might be associated with the pathogenic profile of immune cells, cytokine storm and multiorgan defects. Thus, the pharmacological inactivation of the NF-κB signalling pathway can strongly represent a potential therapeutic target to treat the symptomatology of COVID-19. This article signifies pharmacological blockade of the phosphorylation of inhibitor of nuclear factor kappa B kinase subunit beta (IKKβ), a key downstream effector of NF-κB signalling, for a therapeutic consideration to attenuate COVID-19.

A Rapid and Accurate Technique With Updating Strategy for Surface Defect Inspection of Pipelines

Defect inspection in pipes at the early stage is of crucial importance to maintain the ongoing safety and suitability of the equipment before it presents an unacceptable risk. Due to the nature of detection methods being costly or complex, the efficiency and accuracy of results obtained hardly meet the requirements from industries. To explore a rapid and accurate technique for surface defects detection, a novel approach QDFT (Quantitative Detection of Fourier Transform) has been recently proposed by authors to efficiently reconstruct defects. However, the accuracy of this approach needs to be further improved. In this paper, a modified QDFT method with integration of an integral coefficient updating strategy, called QDFTU (quantitative detection of Fourier transform of updating), is developed to reconstruct the defect profile with a high level of accuracy throughout iterative calculations of integral coefficients from the reference model updated by a termination criteria (RMSE, root mean square error). Moreover, dispersion equations of circumferential guided waves in pipes are derived in the helical coordinate to accommodate the stress and displacement calculations in the scattered field using hybrid FEM. To demonstrate the superiority of the developed QDFTU in terms of accuracy and efficiency, four types of defect profiles, i.e., a rectangular flaw, a multi-step flaw, a double-rectangular flaw, and a triple-rectangular flaw, are examined. Results show the fast convergence of QDFTU can be identified by no more than three updates for each case and its high accuracy is observed by a smallest difference between the predicted defect profile and the real one in terms of mean absolute percentage error (MSPE) value, which is 6.69% in the rectangular-flaw detection example.

Defect reconstruction from magnetic flux leakage measurements employing modified cuckoo search algorithm.

Accurate and efficient estimation for defect profile of magnetic flux leakage (MFL) signals is important for nondestructive evaluation in industry. To improve the accuracy of defect profile reconstruction, an improved reconstruction method based on modified cuckoo search (CS), called MCS, is proposed in this paper. Firstly, a novel single-dimension updating evolution strategy is proposed to avoid the interference between multiple dimensions, which can make full use of the appropriate nest position in the historical search. Secondly, an adaptive multi-strategy difference evolution is introduced into the evolution process to improve the diversity and efficiency of CS algorithm. The proportion factor of each strategy in multi-strategy difference evolution is adjusted dynamically according to the value of the objective fitness. Finally, various MFL signals are selected to verify the effectiveness of the proposed MCS algorithm. The experiment results illustrate that the proposed method has high performance on the quality of the solution and robustness for noise.

A New Concept for Primary Reconstruction of Skull Defects with 3D-Molded PEEK Patch Assisted by Navigation Based on Animal Study.

To perform an accurate primary repair of temporal bone defects. The temporal bone defect models were performed in beagles. Extended estimated patches of the defects were predesigned by 3D reconstruction software and molded from polyether ether ketone (PEEK) using a lathe. The precise trimming of the extended PEEK patches was established via coordinate transformation of the patches between the navigation system and the reconstruction software, and in real-time tracing via intraoperative navigation. Trimmed PEEK patches were embedded onto the defects. Blood tests and image examinations were conducted postoperatively. The extended PEEK patches were prepared precisely according to the predesign. Real-time tracing of the actual skull defect profile was performed quickly and accurately. Trimmed skull patches perfectly matched the shape of the defects. No signs of infection, absorption, or translocation of the patches occurred postoperatively, and little epidural effusion was found. With the assistance of navigation and 3D reconstruction technology, customized molded PEEK patches can be used for accurate primary repair of temporal bone defects.

A Reinforcement Learning-Based Reconstruction Method for Complex Defect Profiles in MFL Inspection

Magnetic flux leakage (MFL) inspection is one of the most commonly used nondestructive evaluation (NDT) methods for detecting anomalies of ferromagnetic materials. Sizing of the defect with MFL signal is the key problem of inspection, which is important for evaluating the health condition of the material. However, it is an ill-posed inverse problem that is hard to solve and harder to be accurate. Forward models that give a highly accurate simulated signal with a corresponding depth profile are widely used in solving the inverse problem iteratively. Unfortunately, the policy which determines the iteration process is hard to design. In this article, a reinforcement learning (RL)-based algorithm is proposed to reconstruct the depth of defects with a complex depth profile. Instead of designing the policy, the iterative process of the classic iteration-based method is embedded into the learning process of the RL-based algorithm proposed in this article. The policy is learned from the data generated during the reconstructing iteration. By designing the states, actions, and rewards in the RL structure, the most computationally costly part of calling the forward model during iteration is avoided. An adaptive limited exploration process is given to balance the exploration and exploitation in the inverse problem of MFL inspection in this article. The effectiveness of the proposed algorithm is demonstrated with simulation results under different noise levels. The results demonstrate that the proposed algorithm is robust with good reconstruction accuracy.

Thermodynamically consistent variational principles for charged interfaces

A generalized framework that naturally incorporates the free energy contributions of thermochemical, structural, mechanical, and electrical fields is presented to describe the Space Charge Layer (SCL) and their effect on transport properties of ionic ceramics. The theory recovers existing analytical, ideal solution models, such as Debye-Hückel (DH), Mott-Schottky(MS), Symmetric Gouy-Chapman (SGC), and Asymmetric Gouy-Chapman (AGC). Strong solution models, such as Mebane-De Souza (MDS) and Vikrant-Chueh-García (VCG) are discussed. DH,SGC, and AGC models naturally describe the SCL for intrinsic systems, while MS has the capability to capture SCL for substitutional systems with an immobile charged dopant. In general, the ideal solution models fall short in capturing the physical effects associated to SCL in a highly doped system, even though millivolt adjustments to the interfacial voltage decreases the cumulative error associated to experimental electrical conductivity values. In contrast, MDS and VCG models capture very well the concentration-dependent electrical conductivity and contribute a smaller cumulative error, as compared to ideal solution models. Even though MDS provides conductivity fits with uncertainties lower than 0.549%, the defect profiles show sharp, unphysically large concentration gradients, on the order of a few Angstroms. VCG captures the description of a thick SCL, up to 20 nm, due to locally induced chemomechanical stresses, by using physical quantities, delivering uncertainties of 1.79% in total conductivity. The comprehensive theory presented herein sets the stage to model the microstructural evolution of ionic materials and their properties, and enables to design the underlying microstructure under different external fields such as temperature, stress, electrical, magnetic, and chemical stimuli.

Transition from trap-mediated to band-like transport in polycrystalline monolayer molybdenum disulfide memtransistors

Multi-terminal memtransistors using polycrystalline monolayer molybdenum disulfide (MoS2) have recently emerged as novel synaptic devices. Due to the coexistence of disorder and strong Coulomb carrier-carrier interactions in MoS2, localization and delocalization of carriers can come into play successively upon the relative strength of disorder and interactions, which can be tuned by the Fermi level (EF). In this work, we show that the transition from trap-mediated to band-like transport leads to the resistive switching behavior in MoS2 memtransistors, which is driven by the EF shift arising from defect profile redistribution that is facilitated by grain boundaries. In the high resistance state, field-driven hopping conduction can be clearly observed in the high-field region (E>0.05 MV/cm), whereas the linear dependence of ln(I/E) on the square root of the electric field, E1/2, suggests Poole–Frenkel emission in the low-field region (E≤0.05 MV/cm). In the low resistance state, strong interactions prevailed and a substantial amount of thermally activated electrons are excited into the conduction band, leading to band-like transport.