Propagation Path Research Articles

High-precision Lamb wave evaluation for corrosion damage with model-based Bayesian Optimization and Gaussian meta-modeling strategy

The presence of corrosion damage in metallic structures is a critical problem affecting system safety, which poses challenges for structural maintenance. Ultrasonic Lamb wave testing has shown many benefits, including high sensitivity and a large coverage area. However, multiple external factors are causing a mismatch between the imaging result and the actual damage. This study proposes a Bayesian Optimization-based model calibration framework, incorporating a Gaussian process (GP) measurement model, for accurate corrosion damage quantification. In this method, one critical problem is obtaining the high-fidelity Finite Element Method (FEM) model. The initial FEM model usually has inevitable modeling errors due to necessary simplifications and idealized constraints. Here we introduced Bayesian Optimization by which the numerical model could be calibrated. The calibrated FEM model, which had fewer discrepancies with actual experiments, could generate high-fidelity signals corresponding to various damage severity. Then, the GP measurement model outputted the mean and variance of the corrosion width and depth corresponding to the differences between experiment signals and model outputs. The inversion of damage information from the established GP model was accomplished by the genetic algorithm. Hence, both the damage size and depth could be evaluated with high accuracy. Once the corrosion information along different propagation paths was obtained, it can be combined with the location of the corrosion damage center for locating the edge points of the corrosion damage. In the end, the edge points were fitted using the least square algorithm. Validations were experimentally performed, and the detection result showed good consistency with the actual damage.

Fretting fatigue crack initiation and propagation behaviours of Ti6Al4V alloy coated by functionally graded material

Fretting fatigue pertains to the behaviour of engineering components undergoing cyclic loading while in contact with each other. This intricate contact-related phenomenon often results in premature failure compared to conventional fatigue issues. Moreover, when these components operate in high-temperature atmospheres and experience high wear conditions, such as the heat transfer tubes in the nuclear reactor, the application of Functionally Graded Material (FGM) coatings becomes essential. Consequently, it is imperative to investigate how FGM coatings influence the initiation and propagation behaviour of fretting fatigue cracks. This paper employs the Critical Plane (CP) method to calculate the damage parameter. Additionally, Linear Elastic Fracture Mechanics (LEFM), specifically the Extended Maximum Tangential Stress (E-MTS) criterion, is utilized to examine how FGM coatings affect the paths of fatigue crack propagation in the presence of fretting conditions. Meanwhile, due to the unavailability of material properties of FGM coatings, the damage parameter and stress intensity factors are utilized to indirectly assess the effect of FGM coatings on crack initiation and propagation lifetimes. The FGM coating significantly influences tangential stress, thereby affecting the length of the stick zone, while having minimal impact on the distribution of normal stress along the contact surface. Furthermore, it is observed that adjusting the variation in composition of FGM coatings and the elastic modulus of the first FGM coating layer provides a potential technique for enhancing both crack initiation and propagation lifetimes.

Optimization of quasi-β forging parameters to control trimodal microstructure parameters and performance of TC21 forgings

This study aims to explore the influence of distinct forging parameters on microstructure and mechanical properties of TC21 forgings. The trimodal microstructure, which includes equiaxial α (αeq), lath α (αlath), and fine α (αfine) phases, was achieved via quasi-β forging and dual heat treatment. Subsequently, mechanical properties were evaluated through tensile, impact toughness (ak), and fracture toughness (KIC) tests. Results indicate that the content of αeq is higher at lower forging heating temperature, whereas the content of αlath is diminished and the size of αfine remains relatively small. This tendency reverses at higher forging heating temperature due to the increased driving force of the phase transition. The rise in αlath content implies more pronounced interface strengthening and plastic deformation, which significantly contributes to strength compared to αfine and αeq but exerts a weaker influence on plasticity. Moreover, the combined deformation and fracture of αlath and αfine exert a significant influence on the initiation and propagation of cracks in ak and KIC specimens. The limited coordination of deformations exhibited by αlath leads to preferential stacking dislocations and shear fractures at interfaces, which are further influenced by its higher aspect ratio affecting crack propagation paths. This not only increases the required energy for initiating cracks but also raises energy consumption during their propagation. Crucially, the presence of αfine significantly enhances the dislocation accumulation and the plastic deformation zone at the crack tip, thereby playing a pivotal role in determining local deformation capacity and crack deflection frequency.

A propagation path-based interpretable neural network model for fault detection and diagnosis in chemical process systems

Process monitoring through automated fault detection and diagnosis (FDD) plays a crucial role in maintaining a productive and reliable chemical process system. Developments in AI and machine learning have boosted FDD model performances especially with deep learning methods. However, these neural network models are considered black-boxes where the reasoning behind a diagnosis is unclear, preventing industrial adoption. Therefore, in this study, an interpretable neural network model is proposed for FDD in chemical processes. This framework detects and diagnoses faults based on the propagation paths of different faults which are embedded into the architecture through graph convolutional networks. A mechanism for interpreting the node activations which represent process variables is developed for decision verification. The proposed method is evaluated on the benchmark Tennessee Eastman Process where it achieves a 93.56% accuracy on selected faults.

CYCLONE STABILITY PARAMETER: ITS NUMERICAL VALUE AND SIGNIFICANCE IN THE PERSPECTIVE OF TRACK DETERMINATION

The study of the dynamics of tropical cyclones constitutes a major portion of the curriculum for atmospheric science throughout the world. This is due to its enormous significance on the coastal human civilization all over the world. The increase in sea surface temperature globally has led to an increase in the frequency of tropical cyclones. As many as ten deadly tropical cyclones have hit the Coromandel Coast of the Bay of Bengal Coastline after generating depressions from the Bay of Bengal in the last decade. The most challenging part lies in the early detection of tropical depressions in the ocean bed, the consequent intensity prediction of the generated tropical cyclone, and the forecasting of the resulting path of propagation of the cyclone in landmass. For these a detailed analytic study of the related cyclone dynamics governing equations, their corresponding solution, propounding of the cyclone analytic solution model, and estimation of some critical parameters based on real cyclone data for the validation of the analytic model is of utmost importance. Radio Sonde Radio Wind (RSRW) data analysis for 5 cyclones and subsequent Cyclone Stability Parameter (CSP)determination, simplification of the complicated expression of and its subsequent significance is the main work of this paper. The is the representative of the entire analysis of the governing equations of tropical cyclones in the applicable coordinate system of a previously performed important work. So this work is also a validation of the previously performed analytic work. We have also analytically simplified the expression of through some approximations and chalked out a more lucid expression which is a function of only. This work effectively unites analytic and numerical performances for more effective prediction of tropical cyclone path of propagation in landmass after their formation in tropical oceans.

Semi-blind sparse channel estimation using regularized expectation maximization

In Massive multiple-input multiple-output (MIMO) systems, channel estimation is crucial. The large size of the antennas causes a significant pilot and feedback overhead, making it challenging to estimate channels in massive MIMO systems. Besides, the studies have shown that mmWave channels are sparse due to the limited number of dominant propagation paths. Therefore, the motivation of this paper is to exploit the inherent sparsity of the massive mmWave MIMO channels to develop a semi-blind channel estimation with reduced number of pilots. To this goal, an expectation maximization (EM) based technique has been developed which leverages the sparsity of the underlying channel for its better estimation. An iterative approach is proposed to solve the modeled problem which simultaneously updates the channel coefficients and data symbols using available data and system structure at each iteration. The proposed method imposes sparsity with the aid of Smoothed L0 norm (SL0) in the M-step. The simulation results demonstrate the proposed method have quick convergence and lower channel estimation error compared to the existing methods. As a quantitative evaluation, the proposed method attains the normalized mean square error of 9×10−2 and 7×10−3 at SNR=5dB and SNR=15dB, respectively.

Using reactive links to propagate changes across engineering models

AbstractCollaborative model-driven development is a de facto practice to create software-intensive systems in several domains (e.g., aerospace, automotive, and robotics). However, when multiple engineers work concurrently, keeping all model artifacts synchronized and consistent is difficult. This is even harder when the engineering process relies on a myriad of tools and domains (e.g., mechanic, electronic, and software). Existing work tries to solve this issue from different perspectives, such as using trace links between different artifacts or computing change propagation paths. However, these solutions mainly provide additional information to engineers, still requiring manual work for propagating changes. Yet, most modeling tools are limited regarding the traceability between different domains, while also lacking the efficiency and granularity required during the development of software-intensive systems. Motivated by these limitations, in this work, we present a solution based on what we call “reactive links”, which are highly granular trace links that propagate change between property values across models in different domains, managed in different tools. Differently from traditional “passive links”, reactive links automatically propagate changes when engineers modify models, assuring the synchronization and consistency of the artifacts. The feasibility, performance, and flexibility of our solution were evaluated in three practical scenarios, from two partner organizations. Our solution is able to resolve all cases in which change propagation among models were required. We observed a great improvement of efficiency when compared to the same propagation if done manually. The contribution of this work is to enhance the engineering of software-intensive systems by reducing the burden of manually keeping models synchronized and avoiding inconsistencies that potentially can originate from collaborative engineering in a variety of tool from different domains.

Examining the Capability of the VLF Technique for Nowcasting Solar Flares Based on Ground Measurements in Antarctica

Measurements of Very-Low-Frequency (VLF) transmitter signals have been widely used to investigate the effects of various space weather events on the D-region ionosphere, including nowcasting solar flares. Previous studies have established a method to nowcast solar flares using VLF measurements, but only using measurements from dayside propagation paths, and there remains limited focus on day–night mixed paths, which are important for method applicability. Between March and May of 2022, the Sun erupted a total of 56 M-class and 6 X-class solar flares, all of which were well captured by our VLF receiver in Antarctica. Using these VLF measurements, we reexamine the capability of the VLF technique to nowcast solar flares by including day–night mixed propagation paths and expanding the path coverage in longitude compared to that in previous studies. The amplitude and phase maximum changes are generally positively correlated with X-ray fluxes, whereas the time delay is negatively correlated. The curve-fitting parameters that we obtain for the X-ray fluxes and VLF signal maximum changes are consistent with those in previous studies for dayside paths, even though different instruments are used, supporting the flare-nowcasting method. Moreover, the present results show that, for day–night mixed paths, the amplitude and phase maximum changes also scale linearly with the logarithm of the flare X-ray fluxes, but the level of change is notably different from that for dayside paths. The coefficients used in the flare-nowcasting method need to be updated for mixed propagation paths.

Effect of size and anisotropy on fracture process zone of coal: An experiment and numerical simulation

The size and properties of the fracture process zone (FPZ) have a significant impact on the fracture toughness of materials. Researching and understanding the characteristics of FPZ contribute to optimizing material performance and enhancing the reliability of engineering structures. In this study, the newly proposed modified semi circular bending (SCB) test method was used to carry out the pure mode I fracture test of coal samples with four sizes and four bedding angles, the development process of FPZ was obtained by using digital image correlation method, and the cohesive zone model considering the bedding plane was established. The influence of size and anisotropy on the development and size of FPZ was studied, and the influence mechanism of FPZ on the size effect and anisotropy of fracture toughness was revealed. The results show that the FPZ length of coal has obvious size effect and anisotropy. The FPZ length increases with the increasing specimen size, and increases first and then decreases with the increasing bedding angle. The FPZ relative length decreases with increasing specimen size, indicating that as the specimen size increases, the influence of specimen boundaries on PFZ gradually decreases, and the size effect of fracture toughness also gradually weakens. The competition between microcrack development driven by principal stress and microcrack development driven by bedding plane results in anisotropy in the development process of FPZ. The anisotropy of FPZ development process results in the anisotropy of FPZ length, fracture toughness and crack propagation path. The research findings can provide valuable guidance for the design of hydraulic fracturing in coal seams.

Thermal fatigue behavior of the ZGH451 Ni-based superalloy fabricated by direct energy deposition in the temperature range of 900–1100 °C

In this study, a novel Ni-based superalloy, ZGH451, has been fabricated using direct energy deposition (DED). The thermal fatigue resistance of ZGH451 is systematically evaluated at 900, 1000, and 1100 °C, primarily focusing on the crack initiation and propagation behaviors. The results indicate that higher peak temperatures lead to earlier initiation and more rapid propagation of cracks. Cracks are initiated at the defects and grain boundaries in the vicinity of the notch, and different crack propagation mechanisms (γ' phase slip shearing, γ' phase distortion shearing, and γ' phase rafting shearing at 900, 1000, and 1100 °C, respectively) are the main reason for the different cracks propagation behaviors under the three temperatures. The main crack propagation paths are oriented at approximately 45° with respect to the build direction, suggesting activation of the {111}<110> slip system. Additionally, oxidation reduces the matrix strength and passivates the crack tips, leading to varying rates of crack propagation. At elevated temperatures, the synergistic effects of thermal stress and oxidative erosion are found to be the primary damage mechanisms of thermal fatigue. Overall, the proposed ZGH451 superalloy demonstrates exceptional thermal fatigue resistance, providing a crucial experimental reference for thermal fatigue in additively manufactured superalloys.

Depolarization effects when receiving radio waves on a moving object for various types and characteristics of the path

Depolarization is a change in the plane of oscillation of the vector of an electromagnetic wave during its propagation. It is important to take into account the depolarization of electromagnetic waves when designing a radio path, since each component (vertical and horizontal), depending on the propagation conditions, will have its own attenuation coefficient. In this regard, the choice of one or another type of polarization (linear, circular and elliptical) for a specific radio path will have a significant impact on the level of the received signal. In the course of this work, the most significant factors leading to the depolarization of electromagnetic waves along the propagation paths were identified. These factors included: scattering on bodies of suburban terrain (ground, forests, etc.), reflections (in combination with multipath propagation) from bodies of urban terrain, random (inclined) position of the antenna mobile terminal, Faraday rotation and dispersion in precipitation. As a result of the analysis of depolarization factors, mathematical models were formed that, due to their applied nature, made it possible to predict the effect of depolarization on the quality of reception by a subscriber station installed on a moving object, and also showed the relevance of using antenna systems with automated polarization adaptation.

UHF antenna complex with polarization adaptation

Formulation of the problem. With the development of the telecommunications industry and the growth in the number of subscribers, there is a need to more efficiently use the microphone frequency resource and increase the capacity in the mid-frequency UHF network. Thus, a promising approach to the UHF antenna complex is polarization adaptation, which makes it possible to compensate for the negative influence of various objects on the propagation of paths, such as effects of influence, multipath, depolarization, etc. A model of an antenna complex with polarization adaptation has been developed. In this case, polarization adaptation by the image stabilization method selects the signal with the highest signal level corresponding to the polarization. A distinctive characteristic of this AFS is the controlled control of measurements of the received signal. The antenna complex is used for current and future VHF-UHF pair communications. The proposed antenna system makes it possible to effectively compensate for the effects of depolarization on radio wave propagation paths and increase the signal/(noise + interference) ratio, including in conditions of complex interference activity.

SAW Humidity Sensing with rr-P3HT Polymer Films.

In the present paper the humidity sensing properties of regioregular rr-P3HT (poly-3-hexylthiophene) polymer films is investigated by means of surface acoustic wave (SAW) based sensors implemented on LiNbO3 (1280 Y-X) and ST-quartz piezoelectric substrates. The polymeric layers were deposited along the SAW propagation path by spray coating method and the layers thickness was measured by atomic force microscopy (AFM) technique. The response of the SAW devices to relative humidity (rh) changes in the range ~5-60% has been investigated by measuring the SAW phase and frequency changes induced by the (rh) absorption in the rr-P3HT layer. The SAW sensor implemented onto LiNbO3 showed improved performance as the thickness of the membrane increases (from 40 to 240 nm): for 240 nm thick polymeric membrane a phase shift of about -1.2 deg and -8.2 deg was measured for the fundamental (~78 MHz operating frequency) and 3rd (~234 MHz) harmonic wave at (rh) = 60%. A thick rr-P3HT film (~600 nm) was deposited onto the quartz-based SAW sensor: the sensor showed a linear frequency shift of ~-20.5 Hz per unit (rh) changes in the ~5-~50% rh range, and a quite fast response (~5 s) even at low humidity level (~5% rh). The LiNbO3 and quartz-based sensors response was assessed by using a dual delay line system to reduce unwanted common mode signals. The simple and cheap spray coating technology for the rr-P3HT polymer films deposition, complemented with fast low level humidity detection of the tested SAW sensors (much faster than the commercially available Michell SF-52 device), highlight their potential in a low-medium range humidity sensing application.

Splitting Tensile Mechanical Performance and Mesoscopic Failure Mechanisms of High-Performance Concrete under 10-Year Corrosion from Salt Lake Brine

In regions characterized by the challenging combination of brine corrosion in the salt lakes and river sand with alkali silica reaction (ASR) activity in areas of the Northwest, high-performance concrete (HPC) formulated with high-volume composite mineral admixtures as ASR suppression measures has been preferred for civil engineering structures in the region. This study investigates the splitting tensile strength, corrosion products, microscopic structure characteristics, and mesoscopic mechanical mechanisms of splitting failure of such HPC under 10-year corrosion from salt lake brine. The relationship between mechanical properties and corrosion damage, as well as the characteristics of internal crack propagation paths and failure mechanisms of HPC under splitting load, are explored. The findings reveal that as the alkali content within HPC rises, corrosion damage intensifies, resulting in a reduction in splitting tensile strength. Moreover, a linear association between mechanical properties and corrosion damage is observed. Microscopic structural analysis and numerical simulation of the splitting failure process of HPC elucidate that while the substantial presence of mineral admixtures effectively suppresses the ASR risk associated with alkali-reactive aggregates in concrete, uneven ASR gel products persist. These discontinuous micro-fine interface cracks induced by the gel products and the cracks induced by the gel products around the selective alkali-active aggregate particles distributed in the local area are the initiation sources of mortar cracks in HPC splitting failure. In terms of the overall failure state observed during the concrete splitting process, mortar cracks manifest two distinct extension paths: along the coarse aggregate interface and directly through the aggregates themselves. Notably, a greater proportion of coarse aggregates are directly penetrated by mortar cracks, as opposed to the number of interface failures bypassing coarse aggregates. More importantly, the above work establishes a theoretical reference in three dimensions: macroscopic, mesoscopic, and microscopic, for studying concrete corrosion damage in complex environments such as salt lake brine corrosion and ASR inhibition.

Design of the primary mirror assembly for a space gravitational wave based on the optical path variation model

As an important component of the gravitational wave detection interferometric measurement system, the telescope’s main function is to receive and emit laser signals. Under the influence of in-orbit environmental disturbances, the telescope will experience structural deformation. This can result in changes in the propagation path of the laser within the telescope, which in turn affects the ranging accuracy. Therefore, it is necessary to suppress the optical path variation caused by the deformation of the telescope during the design phase of the telescope structure. In this paper, a calculation and analysis model of the non-geometric optical path length variation within the telescope was established using the first 36 orders of the fringe Zernike polynomials. The derivation of the geometric optical path variation within the telescope was completed, and the optical system error analysis was performed based on the internal optical path variation of the telescope as an evaluation index. The primary mirror components that meet the detection requirements were designed. The results showed that for the off-axis four-mirror optical system, under the same disturbance, the geometric optical path variation caused by the rigid displacement of the primary mirror dominates. When the environmental temperature stability is 2.8×10−6K⋅Hz−1/2 @0.1 Hz, the system’s optical path stability is reduced from the original 8.5pm⋅Hz−1/2 @0.1 Hz to 0.45pm⋅Hz−1/2 @0.1 Hz.

Path Loss Models for 5G Communications System in Corridors Environment

This paper presents the propagation path loss channel models, developed from real-field measurement in Universiti Teknologi Malaysia (UTM) Kuala Lumpur, Malaysia. The purpose of the study is to characterize the channel at 28 GHz for 5G communications system in line-of-sight corridors environment. Measurement campaigns were conducted to measure the wireless signal of received signal strength at three different construction of straight corridors, narrow, wide, and open corridors. The large-scale path loss models are developed using the closed-in reference distance and floating–intercept modeling approaches. Besides contributing path loss models at 28 GHz for different corridors dimension, the result found in this work discovered the breakpoint distance of radio propagation is seen varies differently at those corridors.

MSO-GP: 3-D segmentation of large and complex conjoined tree structures

Robust segmentation of large and complex conjoined tree structures in 3-D is a major challenge in computer vision. This is particularly true in computational biology, where we often encounter large data structures in size, but few in number, which poses a hard problem for learning algorithms. We show that merging multiscale opening with geodesic path propagation, can shed new light on this classic machine vision challenge, while circumventing the learning issue by developing an unsupervised visual geometry approach (digital topology/morphometry). The novelty of the proposed MSO-GP method comes from the geodesic path propagation being guided by a skeletonization of the conjoined structure that helps to achieve robust segmentation results in a particularly challenging task in this area, that of artery-vein separation from non-contrast pulmonary computed tomography angiograms. This is an important first step in measuring vascular geometry to then diagnose pulmonary diseases and to develop image-based phenotypes. We first present proof-of-concept results on synthetic data, and then verify the performance on pig lung and human lung data with less segmentation time and user intervention needs than those of the competing methods.

Revisiting Seismic Energy of Shallow Tremors: Amplifications Due To Site and Propagation Path Effects Near the Nankai Trough

AbstractWe investigated the effects of the propagation path and site amplification of shallow tremors along the Nankai Trough. Using far‐field S‐wave propagation from intraslab earthquake data, the amplification factors at the DONET stations were 5–40 times against an inland outcrop rock site. Thick (∼5 km) sedimentary layers with VS of 0.6–2 km/s beneath DONET stations have been confirmed by seismological studies. To investigate the effects of thick sedimentary layers, we synthesized seismograms of shallow tremors and intraslab earthquakes at seafloor stations. The ratios of the maximum amplitudes from the synthetic intraslab seismograms between models with and without thick sedimentary layers were 1–2. This means that thin lower‐velocity (&lt;0.6 km/s) sediments just below the stations primarily control the estimated large amplifications. Conversely, at near‐source (≤20 km) distances, 1‐order amplifications of seismic energies for a shallow tremor source can occur due to thick sedimentary layers. Multiple S‐wave reflections between the seafloor and plate interface are contaminated in tremor envelopes; consequently, seismic energy and duration are overestimated. If a shallow tremor occurs within underthrust sediments, the overestimation becomes stronger because of the invalid rigidity assumptions around the source region. After 1‐order corrections of seismic energies of shallow tremors along the Nankai Trough, the scaled energies of seismic slow earthquakes were 10−10–10−9 irrespective of the region and source depth. Hence, the physical mechanisms governing seismic slow earthquakes can be the same, irrespective of the region and source depth.

Deep artificial neural network-powered phase field model for predicting damage characteristic in brittle composite under varying configurations

This work introduces a novel artificial neural network (ANN)-powered phase field model, offering rapid and precise predictions of fracture propagation in brittle materials. To improve the capabilities of the ANN model, we incorporate a loop of conditions into its core to regulate the absolute percentage error for each observation point, that filters and consistently selects the most accurate outcome. This algorithm enables our model to better adapt to the highly sensitive validation data arising from varying configurations. The effectiveness of the approach is illustrated through three examples involving changes in the microgeometry and material properties of steel fiber-reinforced high-strength concrete structures. Indeed, the predicted outcomes from the improved ANN phase field model in terms of stress–strain relationship, and crack propagation path demonstrates an outperformance compared with that based on the extreme gradient boosting method, a leading regression machine learning technique for tabular data. Additionally, the introduced model exhibits a remarkable speed advantage, being 180 times faster than traditional phase field simulations, and provides results at nearly any fiber location, demonstrating superiority over the phase field model. This study marks a significant advancement in the application of artificial intelligence for accurately predicting crack propagation paths in composite materials, particularly in cases involving the relative positioning of the fiber and initial crack location.

Analysis of crack propagation and life estimation of spiral bevel gears with root cracks

Abstract In order to study the effect of tooth root cracks on the fatigue life of spiral bevel gears, a certain spiral bevel gear was taken as the research object, and the mechanism of tooth root fatigue cracks was analyzed based on crack propagation theory; By combining the extended finite element method and the level set method, an initial crack propagation finite element model is established. The crack location of the gear teeth is determined through static analysis of the gear pair, and the influence of alternating loads on the initiation and propagation life of tooth surface cracks is studied. The analysis results indicate that the number of load cycles required for each crack propagation after its first occurrence gradually decreases; The crack propagation path of gear cracks under fatigue load is consistent with the actual tooth surface fracture surface; Realize life estimation from crack propagation to fracture failure.