Defect Parameters Research Articles

FEM-Based Analysis of the Loading Capacity of Defective Cable Tunnel Structures

With the popularized application of underground cable tunnels in China, various structural defects such as cracking, deforming and material deteriorating also emerge. In cable tunnels that have been poorly maintained for a long time, there is always a coexistence of several kinds of defects, and with the current methods of monitoring, it is difficult to identify the major defect affecting the load-carrying capacity and resolve it. However, the finite element method (FEM) can better solve this problem by analyzing the effect of a single defect parameter separately. In this paper, four different types of cable tunnels, namely the circular, rectangular, arched and trenched sectional tunnels, are modelled and analyzed with FEM. Defect parameters, including crack dimensions and concrete deterioration, are considered as variables, which are controlled and studied respectively. The results of the simulation indicate that the impact of crack propagation on the residual-bearing capacity of cable tunnels is much larger than that of concrete deterioration, especially the deepening of cracks. Works in this paper have the potential to be further referenced for cable-tunnel structure estimation and defect prevention.

Research on electromagnetic characteristics of metal spheres with variable parameter defects based on COMSOL finite element method

In order to study the influence of defect geometric parameters (width, thickness) on the electromagnetic characteristics of the space around the defect in the process of eddy current testing of metal spheres, based on the principle of eddy current testing, a metal sphere detection model with different defect parameters was established by COMSOL software for simulation. The distribution of the magnetic field around the defect under different parameters is analyzed with the help of the butterfly diagram composed of the radial magnetic induction intensity and the axial magnetic induction intensity. The results show that: When the width of the corrosion defect is different, the butterfly diagram will change differently. When the width is small, the butterfly diagram basically does not change. When the width reaches a certain value, the butterfly diagram begins to change significantly. The intersection of the graph and the initial butterfly graph is defined as the influence node, and the width of the defect can be quantitatively analyzed according to the sequence of the influence nodes. The influence of the thickness of the corrosion defect on the magnetic field on the surface of the sphere is different under different defect widths. The larger the thickness of the corrosion defect, the greater the influence on the magnetic field near the center of the defect, and the deeper the depression of the butterfly diagram.

Electronic structure modulation of multi-walled carbon nanotubes using azo dye for inducing non-radical reaction: Effect of graphitic nitrogen and structural defect

Multiwalled carbon nanotube (MWCNT) have a great potential for advanced oxidation process as a metal free catalyst. However, there catalytic activity is very low and needs to be appropriately tuned. Herein, we demonstrate a novel synthesis method for tuning the defect and surface functionality of MWCNT using azo dyes and the catalytic performance was tested for the degradation of different organic contaminates using PMS as an oxidant. The content, type of heteroatom functional groups, and the defect parameters were optimized by varying the pH and concentration of the organic dye. The quenching effect showed that singlet oxygen (1O2) is the primary reactive species generated by graphitic nitrogen, which can be boosted by the degree of graphitic structure disruption in MWCNT. The Linear sweep voltammetry (LSV) also confirmed that extrinsic doping enhanced the non-radical degradation by increasing the direct charge transfer rate from MB to PMS. Moreover, the designed catalyst showed a fast degradation performance with 35.1 kJ/mol activation energy and achieved the highest dye degradation rate and even surpassed some state-of-the-art metal-based and metal-free catalysts. The effect of inorganic anions study has also confirmed its industrial applicability.

POSSIBILITY OF IDENTIFYING DEFECTS IN MASSIVE CAST STRUCTURES BY NON-DESTRUCTIVE TESTING METHODS

In the context of improving methods and means of non-destructive testing (NDT), along with increasing in formativeness, complex technical problems arise. For example, when examining structural elements with a service life of more than 20 – 30 years, modern NC tools detect defects that have not been rejected by the manufacturer. Assessment of the impact of such defects on the operability of the structure requires a comprehensive study using NC and strain gauge. The purpose of the work is to evaluate the parameters of defects in a cast part of a hydraulic stamping press with a service life of more than 60 years in order to make a decision on the possibility of its further operation. The defect was investigated using magnetic powder, eddy current and ultrasonic control methods. By means of strain gauges, mechanical stresses are measured directly during operation. The indicator pattern of the magnetic particle inspection defect has signs uncharacteristic for fatigue defects: branching, intermittent and broken (not smooth) character. To quantify the degree of smoothness of the indicator pattern, it is proposed to use a fractal dimension, which for the defect under study was 1.07. The estimated depth of the defect detected by the eddy current method was from 4 to 6 mm, by ultrasound – from 8 to 18 mm. The presence of an echo signal by a direct converter indicates the volumetric nature of the defect. After mechanical removal of the surface layer with a thickness of 2 mm in some areas, the width of the defect increased to 2 mm, and the depth to – 20 mm. On the inner side surface of the defect, a dense, dark scale characteristic of high temperatures is visually determined.The defect is classified as a casting shell with a depth of 20 mm. No traces of fatigue failure were found. Compressive mechanical stresses with an amplitude of no more than 41 MPa amounted to less than 20 % of the fatigue endurance limit of 35L steel. During the year, the average number of working cycles is 20 thousand, repeated examination of the press defect is recommended in 5 – 10 years (100 – 200 thousand cycles).

Single- Versus Multi-Step Trap Assisted Tunneling Currents—Part I: Theory

Leakage currents through dielectrics in modern logic, memory, and power devices, and back-end interlevel layers can severely increase the time-zero power dissipation and shorten the lifetime of the material structure. Depending on thickness, material properties, and fabrication quality, different conduction mechanisms through the insulating layer, such as band-to-band and trap-assisted tunneling (TAT) are observed. These leakage currents can be distinguished by their dependence on electric field strength, temperature, and their transient characteristics. The identification of the underlying mechanisms is of utmost importance for the selection of suitable dielectrics and optimization of device processing. In this work, we present a nonradiative multiphonon model which extends our compact physics (Comphy) reliability framework to also account for TAT. The model is based on a single physical defect parameter set from which charge transfer kinetics between charge carrier reservoirs and oxide defects (single-TAT) as well as between the defects (multi-TAT) can be derived. We thereby demonstrate that the thermal barrier for inelastic defect–defect carrier tunneling is approximately twice as large in comparison to reservoir-defect interaction and further show in which parameter regime multi-TAT plays a role. Our results show that multi-TAT currents are a less important contribution to the overall tunnel current than previously assumed.

Approach for defective floating pile embedded in layered saturated soils and application in pile integrity test

AbstractIn this study, a novel analytical method combining a 3D continuum model, Biot propagation theory, a fictitious saturated soil pile (FSSP) model, and a heterogeneous pile model is proposed to analyze the dynamic response of a defective floating pile embedded in saturated soils. The vertical velocity of the defective pile in the frequency domain is obtained by introducing the complete coupling conditions of the pile and soil. With the most widely used half‐sine pulse as the excitation force in the low‐strain integrity testing of the pile, the solution is extended to the time domain using the inverse Fourier transform (IFT). The rationality and accuracy of the proposed approach are verified via comparison with previous methods and measured data from an engineering example. Parametric analyses are also conducted to investigate the quantitative relationship between the pile defect parameters and the dynamic response characteristics of a defective pile. It is indicated that the depth and length of a pile defect can be roughly evaluated using the proposed methodology when clear signals are reflected from pile defect interfaces in practical engineering.

Non-Dominant Genetic Algorithm for Multi-Objective Optimization Design of Unmanned Aerial Vehicle Shell Process.

This paper uses Pareto-optimized frames and injection molding process parameters to optimize the quality of UAV housing parts with multi-objective optimization. Process parameters, such as melt temperature, filling time, pressure, and pressure time, were studied as model variables. The quality of a plastic part is determined by two defect parameters, warpage value and mold index, which require minimal defect parameters. This paper proposes a three-stage optimization system. In the first stage, the main node position of the electronic chip in the module is collected by the unified sampling method, and the chip calculation index of these node positions is analyzed by the mold flow analysis software. In the second stage, the kriging function predicts the mathematical relationship between the mold index and warpage value and the process parameters, such as melt temperature, filling time, packing pressure, and packing time. In the third stage, using LHD sampling and non-dominant rank genetic algorithm II, a convergence curve of warp value is found near the Pareto optimal frontier. In the fourth stage, the fitting degree of Pareto optimal leading edge curve points was verified by analytical experiments. According to experimental verification, it can be seen that the injection molding factors are pressure and pressure time, because the injection molding time and pressure time are completely positively correlated with the mold indicators, the correlation is the strongest, the mold temperature and glue temperature are not the main influencing factors, and the mold temperature shows a certain degree of negative correlation. In this experiment, the die index is mainly improved by injection time and pressure, optimal injection parameter factor combination and minimum injection index, the optimization rate of the die index is up to 96.2% through genetic algorithm optimization nodes and experimental verification, the average optimization rate of the four main optimization nodes is 91.2%, and the error rate with the actual situation is only 8.48%, which is in line with the needs of actual production, and the improvement of the UAV IME membrane is realized.

Simulation Dataset Preparation and Hybrid Training for Deep Learning in Defect Detection Using Digital Shearography

Since real experimental shearography images are usually few, the application of deep learning for defect detection in digital shearography is limited. A simulation dataset preparation method of shearography images is proposed in this paper. Firstly, deformation distributions are estimated by finite element analysis (FEA); secondly, phase maps are calculated according to the optical shearography system; finally, simulated shearography images are obtained after 2π modulus and gray transform. Various settings in the parameters of object, defect, load and shearing in those three steps could prepare a diverse simulation dataset for deep learning. Together with the real experimental images taken from a shearography setup, hybrid trainings of deep learning for defect detection are performed and discussed. The results show that a simulation dataset, generated without any real defective specimen, shearography system or manual experiment, can greatly improve the generalization of a deep learning network when the number of experimental training images is small.

Failure assessment of corroded ultra-high strength pipelines under combined axial tensile loads and internal pressure

The failure of corroded ultra-high-strength steel (X100 and X120) pipelines under combined axial loads and internal pressure is investigated numerically by finite element analyses, and an empirical model is proposed for burst strength prediction. The finite element structural models are constructed with uniformly oriented axial defects and consider material non-linearity. After validating the finite element models against test data of intact and corroded ultra-high-strength pipes, they are used to study the effect of axial tensile force on burst strength. Extensive parametric analyses are then conducted to investigate the influence of corrosion defect parameters on the burst strength under combined loading. The results revealed that both axial tension and corrosion defect can significantly reduce the burst strength of UHS pipe. Later, the results of the parametric analysis are used to develop an empirical model for burst strength prediction of ultra-high-strength steel corroded pipelines subjected to combined loading. Finally, the model's prediction capability is validated by comparisons with other available models.

REMOVAL OF DIESEL OIL WATER BY HYDRODYNAMIC DISPERSION

REMOVAL OF DIESEL OIL WATER BY HYDRODYNAMIC DISPERSION

Варианты репаративного ответа при закрытии макулярного разрыва различными способами

Baсkground. Recently, additional microtraumatization of neuroretinal tissue has been proven during removal of the internal limiting membrane (ILM) due to its close connection with the inner layers of the retina and with Muller cells. These factors may influence functional results after surgery for closure of macular hole. Purpose. To propose a new technique of surgery for macular hole, which is based on the preservation of ILM and to assess the dynamics of the functional parameters of the retina. Methods. The results of OCT of 60 patients (60 eyes) with the diagnosis of macular hole were analyzed. Group 1 (30 eyes) – patients who underwent surgical treatment with inverted flap. Group 2 (30 eyes) – patients who were operated using the original method with preservation of ILM in the central zone. All patients underwent standard ophthalmological examination before and after surgery, including visometry, biomicroscopy, ophthalmoscopy, and OCT. Results. Preoperative functional parameters of the retina were comparable in both groups of patients. The study identified 3 types of macular hole closure. When studying morphological changes in macular hole repair by the “pseudocyst” type in patients of both groups, it showed a more pronounced resistance of neuroretinal tissue in patients of group 1. In the 2nd group, more pronounced dynamics of reducing the morphological parameters of the hyporeflective defect was revealed throughout the entire observation period. When the macular hole is completely closed, there is a higher rate of regression of neuroepithelial tissue edema in group 2 patients. Non-closure of the macular hole was observed only in group 1 patients, and in this type of repair, there was a deterioration in morphological parameters. Conclusion. Based on this study, we can conclude that using this technique the ILM is preserved, which reduces the risk of intraoperative damage to the retinal layers. Key words: macular hole; peeling; microperimetry.

Practical limits of pulsed thermal NDT: The concept of additive/multiplicative noise

The approach to determining thermal nondestructive testing (TNDT) limits by defect parameters is presented on the base of the suggested concept of noise. The concept presumes that active TNDT limits are conditioned by the inherent noise, which can be conventionally classified for additive and multiplicative. It is shown that practical TNDT limits are associated with multiplicative noise, which can be conveniently expressed in terms of noise running contrast. Considering a certain interval of running contrast values adhered to a particular construction material can be useful when determining potentials of thermal NDT by minimal size and maximal depth of detected defects, for example, by using a simple analytical 1D model.

Ultimate Bearing Capacity Analysis of Manned Submersible Based on the Genetic Algorithm Discontinuous and Galerkin Finite Element Method

The pressure hull of deep manned submersible is the most basic component to ensure its intended function. It is necessary to study the influence of initial geometric defects on the bearing capacity of pressure hull of manned submersible with different depths. According to the idea of discontinuous Galerkin finite element method, the theoretical model is constructed and the corresponding algorithm is designed, and the genetic algorithm is combined with discontinuous Galerin finite element method to establish the inverse method to obtain the ultimate bearing capacity of manned submersible. First, the discontinuous Galerkin finite element model is constructed, the inversion model is also established through combing the discontinuous Galerkin finite element method and genetic algorithm, and then the corresponding solution algorithm is designed. Moreover, then, the ultimate bearing analysis of manned submersible for different deep is carried out based on the inversion model combing discontinuous Galerkin finite element method and genetic algorithm. The effect of defect parameters on ultimate bearing capacity of manned submersible is obtained.

Correlation between relative afferent pupillary defect and visual field defects on Humphrey automated perimetry: A cross-sectional clinical trial.

To evaluate the correlations between relative afferent pupillary defect (RAPD) magnitude, assessed using the clinical plus scale and neutral density filters, and visual field parameters in patients with unilateral or asymmetrical bilateral optic neuropathy or retinopathy. Fifty-two patients with RAPD, graded by the swinging flashlight test and neutral density filters, were analyzed in this cross-sectional trial. The RAPD clinical plus scale was divided into grade 1+, initial weak constriction; grade 2+, initial stall then dilatation; grade 3+, immediate dilatation; and grade 4+, fixed amaurotic pupil. Patients with positive RAPD underwent a visual field examination with Humphrey automated perimetry that included visual field index (VFI), mean deviation (MD), and pattern standard deviation (PSD). Spearman's rank correlation coefficients and linear regression were used to analyze the association between RAPD grades and visual field parameters. RAPD clinical plus grades were correlated with interocular VFI (r = 0.55, P < 0.001) and MD (r = 0.48, P = 0.004) differences. Average interocular VFI differences were estimated as follows: 16.75 × RAPD plus grade- 7.53. RAPD, graded by neutral density filters, was correlated with VFI (r = 0.59, P < 0.001), MD (r = 0.54, P < 0.001), and PSD (r = 0.34, P = 0.01). The RAPD plus scale and neutral density filter grading systems were associated with quantitative visual field defect parameters, with VFI showing the strongest association. RAPD clinical grading could substitute more sophisticated central visual field evaluation methods as a low-cost, low-tech, and widely available approach.

Leakage performance of CFRP laminate under cryogenic temperature: Experimental and simulation study

Leakage rate prediction of carbon fiber reinforced polymer (CFRP) composites for cryogenic propellant tanks has been a challenge for the research community. In this paper, the leakage properties of CFRP laminates with various lay-up configurations are experimentally assessed by measuring their leakage rates under different loads and temperatures. The effects of temperature, cooling conditions and loading on the leakage rates of the above laminate composites are discussed. Meanwhile, in-situ micro X-ray computed tomography (μCT) testing is performed to characterize the internal microstructure evolution of the composites under tension. The geometric morphology and parameters of defects are investigated as well. The propagation of internal cracks in the composites under loading is carefully monitored. A novel 3D image-based model is developed using μCT scans to predict the leakage properties of the composites under various loads. The initiation and propagation leakage rates of laminates, whose values are found to be within the same order of magnitude as experimental ones. The proposed simulation method allows one to quickly calculate the image-based leakage model suitable for the prediction of leakage performance and the lay-up design of composite cryogenic propellant tanks under cryogenic temperatures.

The Sliding-Aperture Transform and Its Applicability to Deep-Level Transient Spectroscopy

A mathematical method is presented for the extraction of defect parameters from the multiexponential decays generated during deep-level transient spectroscopy experiments. Such transient phenomenon results from the ionization of charge trapped in defects located in the depletion width of a semiconductor diode. From digitized transients acquired at fixed temperatures, this method produces a rate–domain spectral signature associated with all defects in the semiconductor. For signal-to-noise ratio of 1000, defect levels with carrier emission rates differing by as little as 1.5 times may be distinguished.

Analyzing probability of detection as a function of defect size and depth in pulsed IR thermography

This study introduces a novel approach to the presentation of the probability of detection (POD) function in infrared (IR) thermographic nondestructive testing. The modified POD is suggested as a function of two defect parameters, namely, defect depth and lateral size. The proposed approach is based on calculating theoretical values of maximum temperature contrast for many defect size/depth combinations by using an appropriate analytical model. Furthermore, these values are used for the quantification of defects to produce predicted POD curves by applying a signal/response method. The results appear as the POD maps illustrating detectability of defects with various size/depth combinations. By setting a particular POD threshold, for example, 90%, the detectability limit contours can be obtained. These contours illustrate the limiting combinations of the depth and diameter of the defects, which can be detected with a required probability of correct detection under a particular temperature signal threshold. The proposed methodology is illustrated with an example of using the POD approach in pulsed IR thermographic inspection of a 3D printed specimen with artificial sphere-like defects. Such an approach allows predicting the detectability of defects in a vast range of depth/size ratios by using an analytical model and a limited number of experiments.

Quantitative sizing of compound location defects based on PECT-EMAT hybrid testing methods

Metal structures are widely used in modern industrial fields, in which various compound location defects are inevitably produced from manufacture to service. Facing such complex conditions, a single electromagnetic nondestructive testing method usually cannot meet all needs. For metal structure with surface crack and bottom thinning defect, a novel PECT-EMAT hybrid testing method is proposed in this study. The relevant simulation and experimental method are developed to realize the compound location defects detection. The proposed method employs only one set of equipment to realize the compound location defects detection, which greatly reduces the complexity of the experimental system and improves the detection efficiency. In addition, the correlation between the extracted signal features and the defect parameters is established through simulation, and further verified by experiment. Furthermore, in order to estimate the damage level of the defects, the inversion calculation procedure of the hybrid NDT method are developed based on genetic algorithm and neural network algorithm, respectively. The reconstruction of the compound location defects using the above two inverse algorithm are carried out using simulation data and experimental data. Finally, the effects of the two inverse methods are compared and the reasons for their advantages and disadvantages are analyzed.

Thermodynamics of Point Defects in Solids and Relation with the Bulk Properties: Recent Results

For several decades, the crucial question has arisen as to whether there exists any direct interconnection between the thermodynamic parameters of point defects in solids with the bulk properties of the solid under investigation. To answer this important question, an interrelation of the defect Gibbs energy gi in solids with bulk properties has been proposed almost half a century ago. Considering that gi corresponds to an isobaric and isothermal process, this interrelation states that, for different processes (defect formation, self-diffusion activation, and heterodiffusion), gi is proportional to the isothermal bulk modulus B and the mean volume per atom Ω, termed cBΩ model. Here, we review several challenging applications of this interrelation that appeared during the last decade (2011–2021), including high pressure diamond anvil measurements, high Tc superconductors, nuclear fuels, and materials for micro-electronics devices, applications of usefulness in Geophysics and Seismology, a problem of major technological interest, search for compositions of better target properties in Cu-Co-Si alloys via machine learning as well as two independent studies on the physical origin of this interrelation that has been further strengthened during the last few years.

Dynamic disorder in a coupled two-lane exclusion process with Langmuir kinetics

In intracellular transport, the motor proteins may jump between the filaments due to structural deformity where the motion is hindered by presence of bound proteins. This motivates us to study a system of two parallel disordered exclusion processes with Langmuir kinetics under symmetric and asymmetric coupling conditions. Theoretically, continuum mean-field approximation is employed to obtain steady-state equations which are further solved numerically. The steady-state system dynamics are examined for different values of coupling constant [Formula: see text], which indicates ratio of lane-changing rates. The effect of binding constant [Formula: see text] and defect parameters is also explored. Under the symmetric coupling case, the topological structure of phase diagram turns out to be similar to that in single-lane model, which differs significantly under fully asymmetric coupling. The asymmetric coupling increases magnitude of difference between densities in two lanes. At a very large attachment/detachment rate, the LK dynamics dominate the effect of asymmetric coupling in the lanes. The defect parameters are found to reduce particle flux in the steady state. The numerical results are validated through extensive Monte Carlo simulation.