Void Features Research Articles

Void number counts as a cosmological probe for the large-scale structure

ABSTRACT Void number count (VNC) indicates the number of low-density regions in the large-scale structure (LSS) of the Universe, and we propose to use it as an effective cosmological probe. By generating the galaxy mock catalogue based on Jiutian simulations and considering the spectroscopic survey strategy and instrumental design of the China Space Station Telescope (CSST), which can reach a magnitude limit $\sim$23 AB mag and spectral resolution $R\gtrsim 200$ with a sky coverage of 17 500 deg2, we identify voids using the watershed algorithm without any assumption of void shape and obtain the mock void catalogue and data of the VNC in six redshift bins from $z=0.3$ to 1.3. We use the Markov chain Monte Carlo method to constrain the cosmological and VNC parameters. The void linear underdensity threshold $\delta _{\rm v}$ in the theoretical model is set to be a free parameter at a given redshift to fit the VNC data and explore their redshift evolution. We find that the VNC can correctly derive the cosmological information, and the constraint strength on the cosmological parameters is comparable to that from the void size function method, which can reach a few per cent level in the CSST full spectroscopic survey. This is because, since the VNC is not sensitive to void shape, the modified theoretical model can match the data better by integrating over void features, and more voids could be included in the VNC analysis by applying simpler selection criteria, which will improve the statistical significance. It indicates that the VNC can be an effective cosmological probe for exploring the LSS.

Decoding ceramic fracture: Atomic defects studies in multiscale simulations

Microstructural atomic defects, including voids, cleavage, and inclusions, are commonly observed in alumina materials, and their impact on mechanical properties, such as fracture stress and toughness, is significant. In this paper, we introduce novel alumina models that incorporate experimentally observed void features. An atomic model is established to study the effects of micro-structural void features on fracture properties and atomic structure changes using molecular dynamics simulations. The electron backscatter diffraction and scanning electronic microscopy analysis of experimental samples are used to evaluate microstructural features that are used as inputs to the simulations (e.g., void aspect ratio, void angle). We apply an innovative Atomistic-to-Continuum (ATC) method based on Riemann sums to bridge atomic and continuum mechanics theories, evaluating the resistance of materials with atomic defects to crack propagation. The results show the greatest effects of pore angles on weakening mechanical properties such as peak strength and fracture energy density. The accuracy and efficiency of the ATC method in evaluating stress intensity factors are used to calculate the mechanical responses. Additionally, we establish a multiple layer perceptron neural network to evaluate the complex relationship between void features (aspect ratio, pore angle, relative distance) and typical fracture properties (fracture stress, critical stress intensity factor). A meta-analysis of these results from both machine learning methods and molecular dynamics simulations reveals the significant impact of each void feature on the sensitivity of typical fracture properties (peak strength, critical stress intensity factor at peak strength) and highlights the critical role of aspect ratio on fracture properties.

Water Diffusion in Additively Manufactured Polymers: Effect of Voids

This study investigates the effect of void features in additively manufactured polymers on water diffusion, focusing on polyethylene terephthalate glycol (PETG) composites. The additive manufacturing (AM) of polymers, specifically, material extrusion AM (MEAM), results in manufacturing-induced voids, therefore affecting the water resistance of the printed parts. The research analyses the effects of size, shape, orientation and the hydrophilicity of voids on moisture diffusion in PETG composites employing numerical (finite-element) simulations. Two void types were examined: voids of Type I that retard the moisture propagation and voids of Type II that enhance it. Simulations demonstrate that a higher volume fraction of voids and their orientation with regard to the diffusion direction significantly hinder the moisture transport for Type I voids. Conversely, due to their high diffusivity, Type II voids serve as channels for rapid moisture transmission. Consequently, for such materials, the global diffusion rates mainly depend on the volume fraction of voids rather than their shape. These findings indicate the critical role of voids in the design of AM parts for environments exposed to moisture, such as marine and offshore applications. Understanding the void effects is critical for optimising the durability and performance of MEAM components underwater exposure.

Self-assembled photonic cavities with atomic-scale confinement

Despite tremendous progress in research on self-assembled nanotechnological building blocks, such as macromolecules1, nanowires2 and two-dimensional materials3, synthetic self-assembly methods that bridge the nanoscopic to macroscopic dimensions remain unscalable and inferior to biological self-assembly. By contrast, planar semiconductor technology has had an immense technological impact, owing to its inherent scalability, yet it seems unable to reach the atomic dimensions enabled by self-assembly. Here, we use surface forces, including Casimir–van der Waals interactions4, to deterministically self-assemble and self-align suspended silicon nanostructures with void features well below the length scales possible with conventional lithography and etching5, despite using only conventional lithography and etching. The method is remarkably robust and the threshold for self-assembly depends monotonically on all the governing parameters across thousands of measured devices. We illustrate the potential of these concepts by fabricating nanostructures that are impossible to make with any other known method: waveguide-coupled high-Q silicon photonic cavities6,7 that confine telecom photons to 2 nm air gaps with an aspect ratio of 100, corresponding to mode volumes more than 100 times below the diffraction limit. Scanning transmission electron microscopy measurements confirm the ability to build devices with sub-nanometre dimensions. Our work constitutes the first steps towards a new generation of fabrication technology that combines the atomic dimensions enabled by self-assembly with the scalability of planar semiconductors.

Cement pavement void detection algorithm based on GPR signal and continuous wavelet transform method

The dimension of the void area in pavement is crucial to its structural safety. However, there is no effective method to measure its geometric parameters. To address this issue, a void size extraction algorithm based on the continuous wavelet transform (CWT) method was proposed using ground-penetrating radar (GPR) signal. Firstly, the finite-difference time-domain (FDTD) method was used to investigate the GPR response of void areas with different shapes, sizes, and depths. Next, the GPR signal was processed using the CWT method, and a 3D image based on the CWT result was used to visualize the void area. Based on the differences between the void and normal pavement in the time and frequency domains, the signal with maximum energy from the CWT time–frequency result was extracted and combined to reconstruct the new B-scan image, where void areas have energy concentration phenomenon. Based on this, width and depth of void detection algorithm was proposed to recognize the void area. Finally, the detection algorithm was verified both in numerical model and physical lab model. The results indicated that the CWT time–frequency energy spectrum can be used to enhance the void feature, and the 3D CWT image can clearly visualize the void area with a highlighted energy area. After fully testing and validating in numerical and lab models, our proposed method achieved high accuracy in void width and depth detection, providing a precise method for estimating void dimension in pavement. This method can guide DOT departments to carry out pre-maintenance, thereby ensuring pavement safety.

HiTop 2.0: combining topology optimisation with multiple feature size controls and human preferences

ABSTRACT Topology optimisation is a computational design approach that generates high-performing, efficient structures uniquely suited to a design engineer’s goal. However, there exist two major obstacles to the accessibility, or ease of use, of topology optimisation: expensive computational costs and users’ binary decision between personal intuition and the algorithm’s result. Human-informed topology optimisation, or HiTop, presents an alternative approach to topology optimisation when a user lacks access to a high-performance computer or knowledge of code parameters. HiTop 2.0 prompts users to interactively identify a region of interest in the preliminary design and modify the size of the solid and/or void features. The novel contribution of this paper implements multi-phase minimum and maximum solid feature size controls in HiTop 2.0, and demonstrates 2D and 3D benchmark examples, including test cases that show how the user can interactively enhance issues related to eigenvalues, stress, and energy absorption, while solving the minimum compliance problem.

Microscopic void characteristics of OGFC in Sponge City and its effect on noise reduction performance using X-ray CT

This study aims to evaluate how material composition and microscopic void characteristics affect the noise reduction performance of open-graded friction courses (OGFC). X-ray computed tomography (CT) and image processing were employed to analyze the microscopic void characteristics of different OGFC mixtures. Sound absorption tests were conducted, revealing a direct link between OGFC's noise reduction performance and its microscopic void features, particularly connected air voids and void area. This relationship is linear, with every 1 % increase in air voids resulting in a 4.93 % average sound absorption coefficient increase. When air voids are similar, coarser gradations and larger nominal maximum aggregate sizes (NMAS) correspond to higher noise reduction levels, particularly for high-frequency noise. The most significant impact on microscopic void properties comes from the 9.5 mm and 4.75 mm mesh sizes, followed by 1.18 mm, while the 2.36 mm sieve exhibits a weaker correlation. These findings are crucial for enhancing OGFC pavement's noise-reduction capabilities, especially in Sponge Cities, and extending the acoustic lifespan of pavement.

Machine-learning Cosmology from Void Properties

Cosmic voids are the largest and most underdense structures in the Universe. Their properties have been shown to encode precious information about the laws and constituents of the Universe. We show that machine-learning techniques can unlock the information in void features for cosmological parameter inference. We rely on thousands of void catalogs from the GIGANTES data set, where every catalog contains an average of 11,000 voids from a volume of . We focus on three properties of cosmic voids: ellipticity, density contrast, and radius. We train (1) fully connected neural networks on histograms from individual void properties and (2) deep sets from void catalogs to perform likelihood-free inference on the value of cosmological parameters. We find that our best models are able to constrain the value of Ω m , σ 8, and n s with mean relative errors of 10%, 4%, and 3%, respectively, without using any spatial information from the void catalogs. Our results provide an illustration for the use of machine learning to constrain cosmology with voids.

Using microgravity techniques in the archaeology case study, the animal cemetery at Saqqara, Egypt

ABSTRACT The use of microgravity technique for the detection of subsurface features is considered a valuable tool in archaeological prospection. The precise and detailed measurements obtained through this method have been crucial for the identification of buried structures. In the animal cemetery of Saqqara, a microgravity survey was conducted using a high-precision relative gravity metre called CG-5 device. This instrument has a standard resolution of 1 microGal (1 microGal = 10−8 m s−2) and a standard deviation of less than 5 microGals. The survey covered the entire animal cemetery, including the Ebbs tunnels, and was processed to calculate the vertical deviations in the area after applying terrain correction (TC). By detecting and delineating local density variations caused by a near-surface void, the microgravity technique was able to identify the presence of a possible void feature, as indicated by the acquired negative anomaly in the residual Bouguer anomalies. The precise gravitation data obtained after correction revealed that both the entrance of the cemetery and the densities of the burial chamber were relatively smaller than the surrounding areas of the animal cemetery in the Saqqara region. The data also showed the presence of two crypts leading to the burial chamber region in the southeast part of the cemetery. However, these preliminary results require further investigation, and the study area needs to be expanded to include a larger area. Additionally, other geophysical methods may be used to confirm the abnormality detected and verify the existence of a burial chamber or other corridors.

Boundary recognition of tunnel lining void from ground-penetrating radar data

Abstract Relatively low ground-penetrating radar antenna frequencies are usually selected for tunnel inspection due to the thickness of the lining, which causes the geometric features of voids in the image to be blurred and difficult to identify. Therefore, the boundary points of the voids are determined by combining reflection and attenuation coefficients, and the geometric features are constructed to identify the voids. Depending on the electromagnetic differences between the void and other mediums in the lining, when the electromagnetic wave propagates from the lining concrete to the void, the reflection coefficient is positive, and the phase of the reflected wave is the same as the incident wave. Conversely, the phase of the reflected wave is opposite to the incident wave. Therefore, the boundary point can be determined in the one dimension time-waveform diagram (A-Scan) based on the phase change. Moreover, the amplitude of the electromagnetic wave attenuates exponentially in the concrete, but it attenuates slowly in the void. Also, electromagnetic waves exhibit high-frequency characteristics in the lining but low-frequency characteristics in the voids. Boundary points that conform to the variation of amplitude and frequency characteristics in the void are screened. These boundary points are then constructed in two-dimensional scan data (B-Scan) to identify the voids by using the geometry of the voids. This method is applied to the Hu Sa Tunnel. The voids are successfully identified in the mileage section YK81+310–YK81+422 of the Hu Sa Tunnel, and the depth of cover and the area of voids are correctly estimated.

CF/PEEK interleaved laminates with PEEK film interleaving manufactured by laser-assisted forming: Microstructure and interlaminar shear strength

In this work, adding PEEK film interleaving between layers is proposed to reduce the interlaminar voids and improve the interlaminar shear strength. CF/PEEK interleaved laminates are manufactured with PEEK film interleaving and repass treatment. The porosity and microscopic features of voids are measured and characterized through the water displacement method and optical microscope. It turns out that the interleaving in interleaved laminates with repass treatment has a significant effect on reducing porosity. The crystallinity of laminates, analyzed and calculated by differential scanning calorimeter, is observed to decrease slightly with the increase of interleaving thickness. This is possibly caused by less fibers in the interleaving areas, which act as nuclei of PEEK crystallization. Interlaminar shear strength of interleaved laminates with repass treatment is higher than those without interleaving. This could be attributed to the reduction of porosity, uniform distribution of fiber/resin and the long diffusion time of chains across the interface.

Predicting failure progressions of structural materials via deep learning based on void topology

Despite considerable mechanics modeling-based efforts, accurate predictions of failure progressions of structural materials remain challenging in real-world environments primarily due to complex damage factors and defect evolutions. Here, we report a novel deep learning-based method for predicting failure properties based on defect state evolutions, which enables the full reflection of the damage accumulated in a material until the time of its examination. The method uniquely combines nondestructive X-ray computed tomography (X-CT), persistent homology (PH), and deep learning. It exploits the PH-encoded features from 3D X-CT images as its only input, and outputs failure-related properties. Using two fracture datasets based on low-alloy ferritic steel as a representative structural material, the method was demonstrated to reliably classify or predict the local strain (tensile dataset) and fracture progress (fatigue dataset). The excellent deep learning performances are attributed to both PH analysis and multimodal learning, where key topological features of internal voids, such as their size, density, and distributions, are precisely quantified. The proposed method enables accurate prediction of failure-related properties at the time of material examination based on void topology progressions, and can be extended to various nondestructive failure tests for practical use.

Manufacturing composite laminates with controlled void content through process control

To investigate and evaluate the effect of void features on the mechanical performance of composite materials, it is important to be able to manufacture samples with a range of controlled void content. A criterion of less than 2% of porosity is typically acceptable for industry. However, it is important to investigate the effect of void content above and below this range, as voids are typically unevenly distributed in composite parts, and so there are likely to be local void concentrations higher than 2% in some sections of the structures. In this paper, a novel manufacturing process that allows panels with a range of void contents to be manufactured in a controlled manner is introduced. This allowed an investigation of the effect of manufacturing parameters, such as time, pressure and temperature and material systems on the void content and morphology of the voids in specimens produced.

Effect of strain rate on fractography texture descriptor of AA6063/(Si3N4)x/(Cu(NO3)2)y (x=12%, y = 2–6%)composite after multiple ECAP passes: second order statistical texture analysis conjunction with regression analysis

The tensile strength of the ECAP processed composite of AA6063/(Si3N4)x/(Cu(NO3)2)y (x=12%, y=2-6%) at various strain rates from 0.0001 to 1s-1 with an increment of 10 was examined in relation to the seven-fracture image texture descriptor through void features such as void size and distribution. In order to measure the matrices of voids on the fracture surface created through the coalescence of void results to enhance the material hardening as strain rate increases, the second order statistical texture analysis has been used. With respect to the rising strain rate, it was observed that the composite fracture image feature parameter correlation, homogeneity improved by 6 %, and 20.74% for AA6063/12%Si3N4/6%Cu(NO3)2 after I passes as compared to AA6063/12% Si3N4 after III pass. The contrast was reduced by around 58.643% when reinforcement went from a single reinforcement of 12% Si3N4 with I Pass to a composite of two reinforcements (Si3N4, Cu(NO3)2) that had 6% Cu(NO3)2 with I Pass. After three passes on AA6063/12%Si3N4/2%Cu(NO3)2, the maximum entropy was seen due to the material's increased plastic deformation, which led to an uneven particle distribution. As strain rate and copper nitrate percentage grew from 0 to 6 percent, the tensile strength of the composite improved by 34.69%. To assess the importance of fracture image features in relation to tensile strength with respect to strain rate, a regression model was developed. In order to get information about the fracture studies from fractography, the contrast with varying strain rate was nevertheless the aspect, which had the greatest influence.

Microvascular Changes of the Non-surgical Eye after General Anesthesia in Optical Coherence Tomography Angiography

Purpose: To investigate chorioretinal vascular changes in the non-surgical eyes of patients who underwent vitreoretinal surgery under general anesthesia using optical coherence tomography angiography (OCTA).Methods: Data from 40 patients who underwent retinal surgery were retrospectively analyzed. Ophthalmologic examinations (including OCTA) were performed in the morning before and after surgery. The presence of intraoperative hypotension (IOH; mean arterial pressure <70 mmHg) was determined based on medical records. The vessel density of superficial and deep retinal capillary plexus layers, choriocapillaris void features, and thickness of the choroid and retina were quantified after image processing. Associations between retinal OCTA parameters and anesthesia profiles were also assessed.Results: DCP vessel density was increased after general anesthesia (p < 0.05). Among the patients who experienced IOH, there was no statistical difference in chorioretinal vessel parameters before and after general anesthesia. Also, we did not observe a difference in chorioretinal vessel parameters after general anesthesia between healthy patients and patients with chronic disease, including hypertension and diabetes (p > 0.05). The duration of anesthesia and average size of the choriocapillaris void (p < 0.05, r = -0.32), and the intraoperative mean arterial pressure (MAP) fluctuation and DCP, showed statistically significant negative linear correlations (p < 0.05, r = -0.38). The choriocapillaris void size and intraoperative MAP fluctuation also displayed a significant negative correlation (p < 0.05, r = -0.37), while the average size signal void showed a weak positive linear correlation (p < 0.01, r = 0.41; and p < 0.01, r = 0.44, respectively).Conclusions: This is the first study to assess the effects of general anesthesia on chorioretinal vessels using OCTA. The Vessel density of the DCP was significantly increased in the non-surgical eye after total vitrectomy under general anesthesia. Furthermore, we found a correlation between MAP fluctuation and choriocapillaris void features. More studies are needed to confirm and expand on these observations.

Three-field floating projection topology optimization of continuum structures

Topology optimization using the variable substitution among three fields can achieve a design with desired solid and/or void features. This paper proposes a three-field floating projection topology optimization (FPTO) method using the linear material interpolation. The implicit floating projection constraint is used as an engine for generating a 0/1 solution at the design field. The substitution filtering and projection schemes enhance the length scale and solid/void features to accelerate the formation of structural topology in the physical field. Meanwhile, the three-field FPTO method can be extended to robust formulation, which obtains the eroded, intermediate, and dilated designs with the same topology. The most distinct feature of the FPTO method lies in the adoption of the linear material interpolation scheme, which makes many topology optimization problems straightforward. As an example, the proposed three-field FPTO algorithm is further applied to the design of shell-infill structures using the linear multi-material interpolation scheme. The distribution of the shell material is generated through a simple filtering scheme, and the shell thickness is accurately controlled by the filter radius. Numerical examples are presented to demonstrate the effectiveness and advantage of the proposed three-field FPTO method.

Associations between Choriocapillaris Flow on Optical Coherence Tomography Angiography and Cardiovascular Risk Profiles of Patients with Acute Myocardial Infarction.

We evaluated the association between macular perfusion assessed via optical coherence tomography angiography (OCTA) and the cardiovascular risk profiles of patients with acute myocardial infarction (AMI). Patients with AMI who underwent comprehensive ophthalmological examinations and retinal OCTA were evaluated retrospectively. Retinal OCTA was performed for each patient within 3 days of admission. Quantitative analyses of the vessel density (VD) of the superficial capillary plexus (SCP) layers, deep capillary plexus layers (DCP), and choriocapillaris were performed after image processing. The 10-year risk of atherosclerotic cardiovascular disease (ASCVD), Global Registry of Acute Coronary Events (GRACE) score, reduction of atherothrombosis for continued health (REACH) score, and thrombolysis in myocardial infarction (TIMI) risk score were assessed. Sixty patients were included. VD in SCP and DCP was not associated with a 10-year ASCVD risk; however, choriocapillaris flow void features were significantly correlated with the 10-year ASCVD risk: decreased count, increased average size, and increased signal void area were correlated with increased 10-year ASCVD risk, GRACE score, REACH score, and TIMI risk score. In the multivariate analysis, a 10-year ASCVD risk (adjusted odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01–1.08) and brain natriuretic peptide (adjusted OR, 1.00; 95% CI, 1.00–1.01) were significantly associated with the highest tertile of the average size of the choriocapillaris. Choriocapillaris flow void features measured using OCTA were associated with cardiovascular risk profiles in patients with AMI. OCTA may be used as an indicator of cardiovascular risk profiles and could improve cardiovascular risk assessments.

Recognition of void defects in airport runways using ground-penetrating radar and shallow CNN

The interpretation of ground-penetrating radar (GPR) data usually depends on manual work, thus yielding unsatisfactory accuracy when processing complicated cases. To address this issue, the finite-difference time-domain method was adopted to explore the void-related features in GPR images, and guide the field survey to locate the void area. On this basis, a dataset including 811 void features was established from 10 airport runways using an 800 MHz ground-coupled GPR system. Data augmentation was used to enlarge the dataset and train four configurations of a mixed convolution neural network (CNN) model with feature extractors (ResNet18 and ResNet50) and object detectors (YOLOv2 and Faster R-CNN). To make the detection process automatic, an incremental random sampling (IRS) approach was used to generate images from GPR data and then fed into the trained model. The experimental results demonstrated that the shallow ResNet18-YOLOv2 with the IRS method is a promising strategy for void detection in airport runways.

Effect of voids and crystallinity on the interlaminar shear strength of in-situ manufactured CF/PEEK laminates using repass treatment

Voids and crystallinity, both affected by the temperature history, have an effect on the interlaminar shear strength of thermoplastic composites. In this paper, CF/PEEK laminates with varied porosity and crystallinity are manufactured by repass treatment (based on the laser-assisted forming) under different interlaminar temperature and times of treatment. The porosity and microscopic features of voids are characterized via the water displacement method and optical microscope, respectively. And further squeeze flow of fiber-resin composite and percolation flow of resin occur during repass treatment, which account for the inhabitation of voids. Crystallinity is analyzed through differential scanning calorimetry, which is affected by both cooling rate and recrystallization of the amorphous phase during repass treatment. The interlaminar shear strength of laminates with varied voids and crystallinity is tested, and the failure modes are studied by optical microscope and scanning electron microscope. As a result, the interlaminar shear strength of laminates, with less voids and higher degree of crystallinity, is improved 32.87% than that of the laminates without repass treatment.

Accessing greater thickness and new morphology features in polyamide active layers of thin-film composite membranes by reducing restrictions in amine monomer supply.

Polyamide formation, via interfacial polymerization (IP) during thin-film composite (TFC) membrane fabrication, is regarded as self-limiting-in the sense that the polyamide film limits its own growth as it forms. During IP, trimesoyl chloride (TMC) and m-phenylenediamine (MPD) react rapidly to form an incipient polyamide film that densifies and slows the diffusion of the more permeable monomer (MPD), thereby limiting polyamide growth and yielding films that typically exhibit thicknesses <350 nm. The morphology of these polyamide films is characterized by a basal layer of void nodular and leaf-like features that is sometimes overlaid by a secondary layer of overlapping flat features. Here, we present evidence showing that polyamide active layers are substantially permeable to MPD, and that minimizing certain restrictions in the MPD supply conditions during IP can result in polyamide active layers of thicknesses several times greater (>1 μm) than those typically reported in the literature. In addition to the basal layer of void nodular features and secondary layer of overlapping flat features that characterize typical polyamide active layers, the thicker films also exhibited three additional morphological features: blanket-like layers atop the basal layer or other void features, multi-layer void structures, and/or void mega-nodules (up to over a micron in diameter). Overall, the results indicate that reducing restrictions in the MPD supply conditions during IP: (1) overcomes the limited polyamide growth observed in conventional TFC membrane fabrication and (2) leads to film morphologies with a more prominent void structure. This latter observation is consistent with recent literature describing the role of CO2 degassing and nanobubble confinement in the development of polyamide active layer morphology. Future studies could vary MPD supply conditions as a new tool to expand the range of achievable thicknesses in active layer casting, regulate active layer morphology and optimize nanobubble confinement conditions independently of MPD supply. Such capabilities could aid in the development of novel supports and TFC structures.