Void Regions Research Articles

Intelligent identification of defective regions of voids in tunnels based on GPR data

Quantitatively detecting voids behind tunnel linings presents significant challenges in identifying the range of width and depth. This paper develops an innovative method for identifying defective regions of voids based on Ground Penetrating Radar (GPR) data. This method involves three steps: Firstly, the void-identifying-feature-set (VIFS) is constructed by extracting the Amplitude peak (AT), Signal energy (ET), and Amplitude peak of the first intrinsic mode function (IMF1) component (AH) of every A-scan signal. Secondly, the Support Vector Machine (SVM) is utilized to identify defect signals and normal signals, contributing to the width identification of void in the horizontal direction. Thirdly, an innovative Three-Stage-Boundary-Extraction (TSBE) algorithm is proposed to identify the depth range of voids in the vertical direction. Experimental results conducted on both field data and simulated data demonstrated that the Intersection over Union (IOU) value and consumption time of three groups of GPR data (Data I, Data II, and Data V) are 0.739 and 0.888 s, respectively. The average IOU and consumption time of the TSBE algorithm are 0.739 and 0.058 s, respectively.

Image segmentation on void regional formation in the flip-chip underfilling process by comparing YOLO and mask RCNN

Purpose This paper aims to identify a suitable convolutional neural network (CNN) model to analyse where void(s) are formed in asymmetrical flip-chips with large amounts of the ball-grid array (BGA) during underfilling. Design/methodology/approach A set of void(s)-filled through-scan acoustic microscope (TSAM) images of BGA underfill is collected, labelled and used to train two CNN models (You Look Only Once version 5 (YOLOv5) and Mask RCNN). Otsu's thresholding method is used to calculate the void percentage, and the model's performance in generating the results with its accuracy relative to real-scale images is evaluated. Findings All discoveries were authenticated concerning previous studies on CNN model development to encapsulate the shape of the void detected combined with calculating the percentage. The Mask RCNN is the most suitable model to perform the image segmentation analysis, and it closely matches the void presence in the TSAM image samples up to an accuracy of 94.25% of the entire void region. The model's overall accuracy of RCNN is 96.40%, and it can display the void percentage by 2.65 s on average, faster than the manual checking process by 96.50%. Practical implications The study enabled manufacturers to produce a feasible, automated means to improve their flip-chip underfilling production quality control. Leveraging an optimised CNN model enables an expedited manufacturing process that will reduce lead costs. Originality/value BGA void formation in a flip-chip underfilling process can be captured quantitatively with advanced image segmentation.

Mimicking Human Hearing with Topologically Optimized Structure

The remarkable auditory capabilities of human ears have inspired the development of bio-inspired acoustic sensing technologies. In this study, a topology optimization problem is formulated to replicate the hearing profile of the human ear and is solved using a gradient-based optimization method. To ensure manufacturability and mesh independence, a density filter is employed to eliminate gray scale transitions between solid and void regions. The objective function is defined to minimize the error between the human's Head-Related Transfer Function (HRTF) of a reference structure and the designed domain in specific frequencies and directions. Numerical simulations demonstrate that the optimized structure exhibits similar acoustic characteristics and spatial directivity to that of the ideal human ear at the designated frequencies. The proposed structure and optimization method show great potential for applications such as 3D audio rendering, hearing- aid design, and sound source localization.

Performance analysis of underwater wireless sensor networks using Reinforcement Learning

This article presents a novel routing protocol named DROR, specifically tailored for underwater wireless sensor networks (UWSNs) to tackle the challenge of void regions. DROR integrates Reinforcement Learning (RL) and Opportunistic Routing (OR) in a recipient-oriented approach, considering the energy limitations and the unique underwater setting. It incorporates a mechanism for void rehabilitation, allowing packets to circumvent void nodes and maintain continuous moving for dependable transmission. Furthermore, a dynamic scheduling strategy based on relative Q-values ensures proficient packet forwarding along the most efficient routing path. Simulation outcomes illustrate the efficacy of the suggested protocol concerning delay, PDR, and energy tax in UWSNs with varying Range, Depths, Packet sizes, and moving radius.

Aspect-ratio-dependent void formation in active rhomboidal and elliptical particle systems.

We execute a numerical simulation of active nematics with particles interacting by an excluded-volume effect. Systems with rhomboidal particles and with elliptical particles are considered in order to investigate the effect of the direct contact of particles. In our simulation, the void regions, where the local number density is almost zero, appear in both systems when the aspect ratio of the particles is high. We focus on the relationship between the void regions and the particle orientation of the bulk. The particle number density, particle orientation, topological defects, and void regions are analyzed for different aspect ratios in both systems. The systems with rhomboidal particles have characteristic void sizes, which increase with an increase in the aspect ratio. In contrast, the distribution of the void-region size in the systems with elliptical particles is broad. The present results suggest that the void size in the systems with rhomboidal particles is determined by the correlation length of the particle orientational field around the void regions, while the void size might be determined by the system size in the systems with elliptical particles.

Inception of vented water trees in high voltage XLPE cable insulation: Effect of inorganic contaminations inside the semiconductive material

AbstractWet‐design AC subsea power cables are currently rated up to a maximum voltage of 72.5 kV. These high voltage (HV) cables are cost‐effective alternatives to subsea cables kept dry by a protective lead sheath and exhibit superior properties for dynamic applications. However, several vented water trees, degradation phenomena reducing the cable lifetime, are observed in a HV XLPE insulated cable subjected to wet aging in the laboratory. The water trees initiate from a smooth and clean XLPE insulation/semiconductive screen interface. In this paper, we show that voids in the range 15–150 μm are observed in the conductor screen, 50–320 μm from the water tree inception sites. Degradation of the semiconductive material is observed, in the form of porous regions that connect the voids to the water tree inception sites. NaCl impurities are detected on the void surfaces and in the porous regions. These features are proposed to be the pre‐requisites for the formation of the vented water trees observed in this type of cable. The mechanism responsible for the formation of the void and porous regions in the semiconductive cable screen is discussed based on the observations.

Effect of secondary flow and wall collisions on particle-laden flows in 90° pipe bends

Fully developed, statistically stationary particle-laden turbulent flows in a 90° pipe bend at a moderate Reynolds number are studied using direct numerical simulation coupled to a Lagrangian particle tracking technique. Three populations of particles are studied which are two-way coupled with the carrier phase. The focus is the investigation of the effect of strong curvature on particle transport dynamics across a range of particle inertias. A validation of the carrier phase predictions is performed, with good agreement found with available experimental data. It is demonstrated that the presence of particles notably affects the turbulence statistics of the carrier phase, decreasing the mean fluid velocity in the outer bend while slightly increasing it in the inner bend. Two intriguing phenomena emerge: the presence of a particle void near the inner bend and reflection layers near the outer bend. Centrifugal forces are responsible for driving particles to the outer wall, with some rebounding back into the main body of the flow, and others, influenced by the secondary flow in the plane of the pipe cross-section, converging towards the inner wall before re-entering the central pipe region. These effects dictate the size and shape of the particle void region and the formation of reflection layers due to particle-wall collisions. These two phenomena have a significant influence on the particle distribution in the pipe bend, as well as on the first- and second-order moments of the velocity and acceleration of the particulate phase. Finally, a heat map of particle-wall collision statistics indicates that the effect of the secondary flow on particle distribution and particle-wall collisions is not negligible.

High-order complex Fourier numerical manifold method for improving the optimization of cracked structures

In this paper, a combination of the high-order numerical manifold method with material interpolation is established with the goal of improving the optimization of cracked structures. Complex Fourier shape functions, known for their inherent advantages, are utilized as weight functions in the numerical manifold method. By implementing high-order analysis, the occurrence of checkerboard patterns is effectively avoided. In addition, a modified sensitivity filtering technique is introduced to address the issue of mesh dependency and minimum length scale in the final topology. This technique is based on the notion of a manifold element. Furthermore, a methodology is introduced to represent void regions within the design domain without the need for passive elements. This methodology involves describing an algorithm to accurately determine the manifold element and the corresponding element area within the final topology. Numerical problems of topology optimization are presented to examine all the aforementioned advantages. The findings indicate that the proposed algorithm for topology optimization does not exhibit any instances of checkerboard patterns. Moreover, the final topology of the curved void regions does not show any zigzag patterns. The above method demonstrates a commendable rate of convergence, and the final topology of the cracked regions can be conveniently simulated.

CAVITY, Calar Alto Void Integral-field Treasury surveY and project extension

We have learnt in the last decades that the majority of galaxies belong to high density regions interconnected in a sponge-like fashion. This large-scale structure is characterised by clusters, filaments, and walls, where most galaxies concentrate, but also under-dense regions called voids. The void regions and the galaxies within represent an ideal place for the study of galaxy formation and evolution, as they are largely unaffected by the complex physical processes that transform galaxies in high-density environments. The void galaxies may hold the key to answer current challenges to the Lambda CDM paradigm as well. The CAVITY survey is a Legacy project approved by the Calar Alto Observatory to obtain spatially resolved spectroscopic information of $ void galaxies in the Local Universe (0.005 < z < 0.050), covering -17.0 to -21.5 in $ r$ band absolute magnitude. It officially started in January 2021 and has been awarded 110 useful dark observing nights at the 3.5 m telescope using the PMAS spectrograph. Complementary follow-up projects, including deep optical imaging, integrated as well as resolved CO data, and integrated HI spectra, have joined the PMAS observations and naturally complete the scientific aim of characterising galaxies in cosmic voids. The extension data has been named CAVITY+. The data will be available to the whole community in different data releases, the first of which is planned for July 2024, and it will provide the community with PMAS datacubes for around 100 void galaxies through a user friendly and well documented database platform. Here, we present the survey, sample selection, data reduction, quality control schemes, science goals, and some examples of the scientific power of the CAVITY and CAVITY+ data.

Impact of electrode arrangement and electrical connections on the power generation of ceramic membrane microbial fuel cell

AbstractSome of the most popular technologies for wastewater sanitation, still face serious limitations related to high energy consumption requirements. In this context, microbial fuel cells (MFCs) constitute a promising approach since they do not require aeration and produce electricity at the same time. Limitations for these devices, however, are related to the cost of the constituents and the functionality of the arrangement. In this work, a semi‐cylindrical ceramic MFC was designed and constructed using a low‐cost commercial ceramic handcraft as a membrane, carbon felt, carbon cloth, and carbon cloth/activated carbon in different arrangements for the anode and cathode components. The best results were obtained using carbon felt as an anode and a cathodic zone built with carbon felt in which void regions were filled with activated carbon. This arrangement produced 85 mWm−2 for each cell. Evaluating the performance of the MFC in a modular system with eight cells using a different number of separations inside the module and different electrical connections, resulting in a 4‐compartment module that produced 90 mWm−2 with one single module and 95 mWm−2 with a serial arrangement of two modules.

Segmentation of void defects in X-ray images of chip solder joints based on PCB-DeepLabV3 algorithm

Defects within chip solder joints are usually inspected visually for defects using X-ray imaging to obtain images. The phenomenon of voids inside solder joints is one of the most likely types of defects in the soldering process, and accurate detection of voids becomes difficult due to their irregular shapes, varying sizes, and defocused edges. To address this problem, an X-ray void image segmentation algorithm based on improved PCB-DeepLabV3 is proposed. Firstly, to meet the demand for lightweight and easy deployment in industrial scenarios, mobilenetv2 is used as the feature extraction backbone network of the PCB-DeepLabV3 model; then, Attentional multi-scale two-space pyramid pooling network (AMTPNet) is designed to optimize the shallow feature edges and to improve the ability to capture detailed information; finally, image cropping and cleaning methods are designed to enhance the training dataset, and the improved PCB-DeepLabV3 is applied to the training dataset. The improved PCB-DeepLabV3 model is used to segment the void regions within the solder joints and compared with the classical semantic segmentation models such as Unet, SegNet, PSPNet, and DeeplabV3. The proposed new method enables the solder joint void inspection to get rid of the traditional way of visual inspection, realize intelligent upgrading, and effectively improve the problem of difficult segmentation of the target virtual edges, to obtain the inspection results with higher accuracy.

Enhancing metasurface fabricability through minimum feature size enforcement.

The metasurfaces have shown great potential for miniaturizing conventional optics while offering extended flexibility. Recently, there has been considerable interest in using algorithms to generate meta-atom shapes for these metasurfaces, as they offer vast design freedom and not biased by the human intuition. However, these complex designs significantly increase the difficulty of fabrication. To address this, we introduce a design process that rigorously enforces the fabricability of both the material-filled (fill) and empty (void) regions in a metasurface design. This process takes into account specific constraints regarding the minimum feature size for each region. Additionally, it corrects any violations of these constraints across the entire device, ensuring only minimal impact on performance. Our method provides a practical way to create metasurface designs that are easy to fabricate, even with complex shapes, hence improving the overall production yield of these advanced meta-optical components.

Detachment of particulate structures from a fiber array due to stretching and simultaneous gas flow

The main cause of high pressure drop and increased energy consumption in a filtration process is the clogging of particulate material in the upstream layers of a depth filter. To alleviate this issue, stress can be introduced into the particulate structure through stretching, which promotes rearrangement and detachment of particle structures, allowing for transfer of some of the clogged particulate material from the upstream layers to downstream void regions. This study aims to extend previous findings from experiments with single fibers to the level of an array. The goal is to analyze the introduction of a multiple stress state by performing stretching experiments with a particle-structure on a fiber array.The stretching tests investigate the influence of different process parameters such as stretching velocity and air flow velocity during stretching on the rearrangement and detachment behavior of a separated particle structures from the fiber array. Rearrangement and detachment of the particle structure are a direct consequences of the stress induced by stretching. The experiments showed a significant increase in relative free projection area of fiber interspaces (RFPI) of up to 160% and thus a large-scale removal of particle material from the fiber interspaces when the flow velocity was increased from 0.05 m/s to 0.8 m/s. Surprisingly, the radial rearrangement of the compact particle structures during stretching resulted in a clogging and blockage of the interfiber spaces (negative RFPI in the range of minimum −54% after the first stretching cycle) and not in a total release of the interfiber spaces. The size of the particle structures in the experiments decreased by about 331 μm with the number of stretching cycles, indirectly confirming the presence of residual structures. Preliminary experiments also confirmed an increased influence on the rearrangement and detachment (removed pariticulater material of about 30%) of particle structures by further increasing the fiber distance of 27 μm and thus introducing a biaxial stretching into the particle structure.

Modeling the coverage of MoS2 and WS2 thin films using in-situ spectroscopic ellipsometry

In-situ spectroscopic ellipsometry (SE) was used to analyze monolayer and few-layer samples of molybdenum disulfide (MoS2) and tungsten disulfide (WS2) grown by metalorganic chemical vapor deposition (MOCVD) on sapphire substrates. MoS2 and WS2 film growth times ranged from 5 – 40 min to achieve a range of film coalescence and surface coverage from less than a monolayer to considerable bilayer and additional layers. Post-growth measurements using atomic force microscopy, photoluminescence and Raman spectroscopy were used to assess the evolution of surface morphology and film properties with growth time to determine the areal coverage of monolayer, bilayer, multilayer and void regions. The room temperature SE spectra were modeled using an effective medium approximation to obtain the monolayer and bilayer dielectric functions of MoS2 and WS2. Using these distinct dielectric functions, changes in ellipsometry parameters associated with partial to full coverage of monolayers and bilayers were simulated. Such simulations will enable improved control of the layer-by-layer deposition of MoS2 and WS2 by monitoring in-situ spectroscopic ellipsometry.

Nonlinear topology optimization of flexoelectric soft dielectrics at large deformation

We propose a novel nonlinear topology optimization framework tailored for flexoelectric soft dielectrics undergoing large deformation. A numerical method based on Isogeometric analysis (IGA) is introduced to nonlinear soft dielectrics at finite strain, ensuring the C1-continuity for flexoelectric problems. We outline the process of consistent linearizations and IGA discretizations. Additionally, we introduce an innovative and efficient Strain Density Function (SDF) interpolation scheme for optimizing electromechanical coupling factors (ECFs). In this scheme, the interpolation of electromechanical and hyper-elastic energy terms is grounded in the SIMP model, while a linear material interpolation model is employed for the dielectric energy. Our numerical analysis highlights the remarkable performance of the proposed SDF interpolation scheme in nonlinear electromechanical optimization scenarios. An energy remedy scheme is applied to void regions to eliminate the instability of nonlinear optimization, effectively preventing distortion deformations in low-stiffness elements. Furthermore, we investigate the influence of size effect and larger deformation on the optimization of flexoelectric soft materials. The proposed topology optimization framework adeptly leverages the interplay between size effect and larger deformation, resulting in a notable improvement in ECFs within the optimized structures. Finally, the electromechanical coupling factors (ECFs) of the optimized structures in all the examined cases exhibit enhancements up to 9 times as compared to the reference guess designs.

Multi-scale design of composite material structures for maximizing fundamental natural frequency

This study deals with the topology optimization (TO) of linear elastic composite structures considering fundamental natural frequency maximization. The concept of functionally graded structures (FGS) is used for anisotropic composite material structure design to improve the structural dynamic performance. The rational approximation of material properties (RAMP) method was employed as an alternative to the solid isotropic material with penalization (SIMP) method to improve the convergence stability for eigen-frequency problem. In the SIMP method, the occurrence of local eigen-modes at low frequencies in the void region causes ill-convergence, whereas the RAMP method prevents local eigen-modes from occurring. The method of moving asymptotes is used as an optimizer. Numerical verification was performed for three structural types: cantilever beam, double-clamped beam, and four-pinned beam structure. In addition, for cantilever beam design, bi-objective optimization for maximizing fundamental natural frequency as well as minimizing structural compliance was performed using the adaptive weighting method that quantitatively reflects the designer's preference by adjusting the weight for each objective function at each iteration.

Revealing void anisotropies in vertically-vibrated granular sphere packings with various structural characterizations

We utilize magnetic resonance imaging (MRI) techniques to study granular sphere packings prepared with vertical vibration, and reveal the extremely slight global anisotropies of the void phase with systematic analyses on Delaunay pores and chords. Unexpectedly, the global orientational orders of the eigenvectors of tensors quantifying (i) pore throats, (ii) chords going through individual pores, (iii) shape of Voronoi cells and (iv) contact fabrics have consistent evolution laws when packing fraction changes, but the orientational order of the eigenvectors of a pore volume tensor exhibits a peculiarly different trend. With an orientation-dependent spatial correlation function, we attribute their different behaviors to the fact that different anisotropy variables probe the void phase at different length scales, so that their dependences on packing fraction are different. The segmentation of the void region into pores sensitively captures a unique and intricate structural anisotropy at an intermediate length scale.

Effect of surface peak-valley features on the fluid flow performance in rough contact interface

In this work, two kinds of microtextured surfaces with different surface peak-valley features, namely positively skewed surface with micropillar array and negatively skewed surface with micropit array, are prepared to explore the effect of peak-valley features on the fluid flow performance in rough contact interface. The distribution and connectivity of microchannels is analyzed, and the physical mechanism of peak-valley features inducing different fluid flow processes is also derived through constructing a kinetic model of fluid spreading. It is found that when the surface skewness Ssk > 0, the positively skewed surface forms the void regions with better connectivity in the interface compared with the negatively skewed surface (Ssk < 0), despite both the surfaces having nearly the same roughness (Sa ∼ 3.6 mm). The formed microchannels are defined as crossed open microchannel and semi-closed microchannel, respectively, and the feature length of the microchannel decreases with the increase in load. The quantitative results of fluid flow demonstrate that the liquid has a better spreading and flow ability in the contact interface of the positively skewed surface. Even under the same microchannel feature length (nearly 48 mm), the fluid spread area ratio of the positively skewed surface has an order of magnitude higher than that of the negatively skewed surface. The mechanism of different flow characteristics induced by surface peak-valley features is believed as the variation of the microchannel shape, leading to the change in the capillary pressure at the meniscus. We believe the present work would lay a theoretical foundation for regulating the microscopic flow behavior in the contact interface.

Nanoparticles synthesis in microwave plasmas: peculiarities and comprehensive insight

Low-pressure plasma processes are routinely used to grow, functionalize or etch materials, and thanks to some of its unique attributes, plasma has become a major player for some applications such as microelectronics. Plasma processes are however still at a research level when it comes to the synthesis and functionalization of nanoparticles. Yet plasma processes can offer a particularly suitable solution to produce nanoparticles having very peculiar features since they enable to: (i) reach particle with a variety of chemical compositions, (ii) tune the size and density of the particle cloud by acting on the transport dynamics of neutral or charged particles through a convenient setting of the thermal gradients or the electric field topology in the reactor chamber and (iii) manipulate nanoparticles and deposit them directly onto a substrate, or codeposit them along with a continuous film to produce nanocomposites or (iv) use them as a template to produce 1D materials. In this article, we present an experimental investigation of nanoparticles synthesis and dynamics in low-pressure microwave plasmas by combining time-resolved and in-situ laser extinction and scattering diagnostics, QCL absorption spectroscopy, mass spectrometry, optical emission spectroscopy and SEM along with a particle transport model. We showed for the first time the thermophoresis-driven dynamic of particle cloud in electrodless microwave plasmas. We showed that this effect is linked to particular fluctuations in the plasma composition and results in the formation of a void region in the bulk of the plasma surrounded by a particle cloud in the peripherical post-discharge. We also reveals and analyze the kinetics of precursor dissociation and molecular growth that result in the observed nanoparticle nucleation.

Understanding the Formation and Evolution of Dark Galaxies in a Simulated Universe

We study the formation and evolution of dark galaxies using the IllustrisTNG cosmological hydrodynamical simulation. We first identify dark galaxies with stellar-to-total mass ratios, M */M tot, smaller than 10−4, which differ from luminous galaxies with M */M tot ≥ 10−4. We then select the galaxies with a dark matter halo mass of ∼109 h −1 M ⊙ for mass completeness and compare their physical properties with those of luminous galaxies. We find that, at the present epoch (z = 0), dark galaxies are predominantly located in void regions without star-forming gas. We also find that dark galaxies tend to have larger sizes and higher spin parameters than luminous galaxies. In the early universe, dark and luminous galaxies show small differences in the distributions of spin and local environment estimates, and the difference between the two samples becomes more significant as they evolve. Our results suggest that, unlike luminous galaxies, dark galaxies tend to be initially formed in less dense regions and could not form stars because of heating from cosmic reionization and few interactions and mergers with other systems containing stars. This study based on numerical simulations can provide important hints for validating dark galaxy candidates in observations and for constraining galaxy formation models.