Number Of Layers Research Articles

Robustness of multilayer interdependent higher-order network

In real-world complex systems, most networks are interconnected with other networks through interlayer dependencies, forming multilayer interdependent networks. In each system, the interactions between nodes are not limited to pairwise but also exist in a higher-order interaction composed of three or more individuals, thus inducing a multilayer interdependent higher-order network (MIHN). First, we build four types of artificial MIHN models (i.e., chain-like, tree-like, star-like and ring-like), in which the higher-order interactions are described by the simplicial complexes, and the interlayer dependency is built via a one-to-one matching dependency link. Then, we propose a cascading failure model on MIHN and suggest a corresponding percolation-based theory to study the robustness of MIHN by investigating the giant connected components (GCC) and percolation threshold. We find that the density of the simplicial complexes and the number of layers of the network affect its penetration behavior. When the density of simplicial complexes exceeds a certain threshold, the network has a double transition, and the increase in network layers significantly enhances the vulnerability of MIHN. By comparing the simulation results of MIHNs with four types, we observe that under the same density of simplicial complexes, the size of the GCC is independent of the topological structures of MIHN after removing a certain number of nodes. Although the cascading failure process of MIHNs with different structures is different, the final results tend to be the same. We further analyze in detail the cascading failure process of MIHN with different structures and elucidate the factors influencing the speed of cascading failures. Among these four types of MIHNs, the chain-like MIHN has the slowest cascading failure rate and more stable robustness compared to the other three structures, followed by the tree-like MIHN and star-like MIHN. The ring-like MIHN has the fastest cascading failure rate and weakest robustness due to its ring structure. Finally, we give the time required for the MIHN with different structures to reach the stable state during the cascading failure process and find that the closer to the percolation threshold, the more time the network requires to reach the stable state.

Critical-Layered MoS2 for the Enhancement of Supercontinuum Generation in Photonic Crystal Fibre.

Supercontinuum generation (SCG) from silica-based photonic crystal fibers (PCFs) is of highly technological significance from microscopy to metrology, but has been hindered by silica's relatively low intrinsic optical nonlinearity. The prevailing approaches of filling PCF with nonlinear gases or liquids can endow fibre with enhanced optical nonlinearity and boosted SCG efficiency, yet these hybrids are easily plagued by fusion complexity, environmental incompatibility or transmission mode instability. Here this work presentsa strategy of embedding solid-state 2D MoS2 atomic layers into the air-holes of PCF to efficiently enhance SCG. This work demonstrates a 4.8 times enhancement of the nonlinear coefficient and a 70% reduction of the threshold power for SCG with one octave spanning in the MoS2-PCF hybrid. Furthermore, this work finds that the SCG enhancement is highly layer-dependent, which only manifests for a real 2D regime within the thickness of five atomic layers. Theoretical calculations reveal that the critical thickness arises from the trade-off among the layer-dependent enhancement of the nonlinear coefficient, leakage of fundamental mode and redshift of zero-dispersion wavelength. This work provides significant advances toward efficient SCG, and highlights the importance of matching an appropriate atomic layer number in the design of functional 2D material optical fibers.

Ultrathin natural biotite crystals as a dielectric layer for van der Waals heterostructure applications

Biotite, an iron-rich mineral belonging to the trioctahedral mica group, is a naturally abundant layered material (LM) exhibiting attractive electronic properties for application in nanodevices. Biotite stands out as a non-degradable LM under ambient conditions, featuring high-quality basal cleavage-a significant advantage for van der Waals heterostructure (vdWH) applications. In this work, we present the micro-mechanical exfoliation of biotite down to monolayers (1Ls), yielding ultrathin flakes with large areas and atomically flat surfaces. To identify and characterize the mineral, we conducted a multi-elemental analysis of biotite using energy-dispersive spectroscopy mapping. Additionally, synchrotron x-ray fluorescence and infrared nano-spectroscopy were employed to probe its iron content and vibrational signature in few-layer form, respectively, with sensitivity to the layer number. We have also observed good morphological and structural stability in time (up to 12 months) and no important changes in their physical properties after thermal annealing processes in ultrathin biotite flakes. Conductive atomic force microscopy evaluated its electrical capacity, revealing an electrical breakdown strength of approximately 1 V nm-1. Finally, we explore the use of biotite as a substrate and encapsulating LM in vdWH applications. We have performed optical and magneto-optical measurements at low temperatures. We find that ultrathin biotite flakes work as a good substrate for 1L-MoSe2, comparable to hexagonal boron nitride flakes, but it induces a small change of the 1L-MoSe2g-factor values, most likely due to natural impurities on its crystal structure. Furthermore, our results show that biotite flakes are useful systems to protect sensitive LMs such as black phosphorus from degradation for up to 60 days in ambient air. Our study introduces biotite as a promising, cost-effective LM for the advancement of future ultrathin nanotechnologies.

Tunability of plasmonic resonances in stratified hyperbolic metamaterials

We numerically and experimentally demonstrate the tunability of plasmonic resonances in the spectral range from 550 nm to 900 nm for type II hyperbolic metamaterials, as a function of their number of layers, period, and filling fraction. The type II hyperbolic metamaterial consisted of stratified periodic arrays of gold and titanium dioxide thin layers on top of a glass substrate. Through numerical and experimental characterization of the totally internally reflected spectra as a function of incidence angle, we show that the tunability of the plasmonic resonance mainly depends on the filling fraction, while the number of layers and the period of the structure only affect the contrast of attenuated reflected spectra. In addition to demonstrating the capability of tuning plasmonic resonances in simplistic stratified mediums, this work contributes to the understanding of light interaction with hyperbolic metamaterials for the improvement of optical devices for sensing applications.

Influence of mechanical anchors on bond performance of fiber fabric-steel joints

This study proposes an experimental model for anchor reinforcement and conducts uniaxial static tensile tests. The influence of anchor reinforcement on the failure mode of specimens is revealed. This includes the effects of bond length, number of layers, and types of fiber fabric under anchor reinforcement on the ultimate bearing capacity and bond-slip curve. The results demonstrate that anchors can effectively increase the ultimate bearing capacity of the test specimens. There are differences in bond-slip behavior between the anchors near the free end and the joint end. Higher stresses are experienced near the joint end. The use of anchor reinforcement can significantly enhance the load-bearing capacity of multi-layer carbon fiber specimens. Increasing the number of anchors and reducing the distance between the anchor and the joint end can further improve the stiffness of the specimens. A finite element model is established using ANSYS, which agrees well with the experimental results and parameterized analysis results reveal a linear increase in load-bearing capacity and stiffness with higher anchor bolt preload, achieving an 84.42 % increase at 11kN. Increased preload enhances friction at the carbon fiber-steel interface, reducing deformation. Similarly, expanding anchor width from 9 mm to 39 mm improves load-bearing capacity by 54.28 %, with larger anchors significantly boosting stiffness and bonding performance, which can be used to predict the mechanical properties of fiber fabric-steel reinforced by anchors.

Comparative morphology and anatomy of Korean Boehmeria achenes and their taxonomic significance

This study confirmed the taxonomic significance of achenes by observing and comparing the morphology and anatomical characteristics of 13 taxa of the genus Boehmeria in Korea. The results confirmed that the achenes studied here are the drupe-like fruit type with mucilage in the exocarp, and during the fruiting season, the perianth persists on the pericarp. The morphological characteristics of the achenes, specifically the number per glomerule as well as the size, shape, color, and trichome were taxonomically significant. The anatomical characteristics of the transverse sectional shape and wings, the thickness of each pericarp layer, the shape of the crystalliferous cells in the mesocarp, and the number of sclereid cell layers in the endocarp were also found to be important. Particularly, the size and wings of the achenes were informative for distinguishing between Sect. Tilocnide and Sect. Duretia, while other characteristics were differentiated among series or certain taxa within the series. The taxonomic significance of the achenes is discussed through comparisons with previously studied taxa and their characteristics. Accordingly, the results of this study can provide valuable insight for those seeking to understand the evolutionary trends of achenes in Boehmeria in the future.

Statistical Analysis of the Influence of Various Types of Graphite Precursors and Oxidation Methods on the Gas Sensor Properties of Reduced Graphene Oxide.

The fabrication process of reduced graphene oxide depends on many factors (e.g., graphite precursor, methods of oxidation, reduction, and exfoliation) which have a significant influence on the properties of this material. Therefore, their selection is not easy due to the large number of possible combinations of these factors. To overcome this problem, we proposed to use a multivariate analysis of variance method of finding associations between the qualitative type of independent variables and the quantitative type of dependent variable. Using ANOVA, we showed that the combination (interaction) of these variables is more important than the individual influence of the variables on the fabricated rGO. Knowing how the particular variables and their combinations affect the properties of rGO, it is easier to plan the fabrication process of this material. In this paper, we analyzed the number of oxide layers and designated the most promising oxides in terms of sensor gas application. Independently, we fabricated chemiresistor sensors and studied their response to NO2 in the analyzed atmosphere. We were able to combine the experimental results with statistical analysis indicating which oxidation methods and which graphite precursors will provide the best sensitivity.

Liquid-phase shear exfoliation of graphite and its application as corrosion protection coating on aluminum substrate

Although aluminum (Al) or its alloys are moderately protected by a native oxide layer, the presence of chloride ions in aqueous media in direct contact causes pitting attacks and accelerates corrosion. Using graphene as a coating protector can obstruct corrosion due to its numerous chemical and physical properties. This study investigates corrosion protection of Al using graphene nanosheets (GNSs) produced by liquid phase shear exfoliation method (LPE). To do so, few layer-thick graphene nanosheet colloidal solutions were produced by a scalable eco-friendlier lower cost approach. The GNSs were thoroughly characterized using complementary characterization techniques to determine its quality. Spectroscopic and microscopic analyses indicate the synthesis of few-layers graphene (≤ 5 layers) with a high quality. Once approved, the colloidal solution of GNSs was spread over Al substrate by spray coating method, widely used in industrial manufacturing. Raman and near infrared spectroscopies, X-ray diffraction, microscopy techniques including scanning electron, transmission electron and atomic force microscopies were used to investigate morphological and structural behavior of coated GNSs films either on glass or Al substrates. Density functional theory (DFT) calculations revealed the interaction between the two materials is of the physisorption type, with almost no charge transfer and almost no effect of the number of graphene layers. Electrochemical measurements enabled to investigate the corrosion resistance of GNSs films and its stability over time in a 0.5 M sodium chloride (NaCl) solution, similar to marine surroundings. It was found that introducing a GNSs film can indeed reduce the corrosion rate and preserve Al substrate for an extended period.

DETERMINING THE OPTIMAL NUMBER OF STRETCH FILM LAYERS FOR ENSURING PALLETIZED CARGO STABILITY: A SIMULATION STUDY

Numerical simulation tests were carried out to determine the influence of the characteristic features of a load unit (such as: weight, height, number of load layers, coefficient of friction between the layers) per number of wraps with stretch film necessary to ensure unit stability. Manufacturers of stretch film sometimes provide guidelines on how many layers of film should be used depending on the weight and height of the load. But they do not explain on the basis of which studies these values were determined. Performing simulations similar to those made in this work in laboratory conditions would be very expensive. The work attempts to determine such relationships by simulation methods. A developed by the author in his earlier works dynamic model of a layered cargo unit wrapped with stretch film was used. The study plan was to check 108 cases. On the basis of the collected data, an attempt was made to develop a mathematical formula that would allow to estimate the optimal number of foil wraps when certain parameters of the load unit are known. In the author's opinion such an estimate could reduce film consumption, which would have a positive impact on the environment.

Estimating the parameters of trypillia proto-cities using plans and magnetic surveys with the help of neural networks.

The Tryplian culture was considered the largest of all other archaeological cultures that existed on the territory of modern Ukraine. The method for analyzing magnetic images has been described, which allows archaeologists to assess the scale of settlements without excavating them. It is noted that one of the tasks during the analysis of the settlement is to find out its characteristics: counting the number of buildings, calculating the area, etc. However, in the majority of cases, counting the number of structures is currently unfeasible, as Trypillian proto-cities are situated within the cultural layer relatively close to the surface, and any economic activities disturb this cultural layer. The capabilities of the existing system (application) are described, which solved the problem by the method of average values and had differences from the commonly accepted method. It was concluded that a more automated version of this system could be an option where the number of sites in the image will be calculated by the average number of pixels per site, that is, the number of black and gray pixels in the image, divided by the average number of pixels in the site. It was decided to use neural network models. As an example, the largest of the famous Trypil proto-cities in Ukraine - Talyanka with an area of 450 hectares - is considered. Pictures taken between 1971 and 1974 were used because they are in the public domain. A list of actions for image preprocessing is described. A decision was made to train the model to input square images of 15 by 15 pixels, for this the entire image was divided into 748 square images, the number of buildings in each of them was determined manually. A four-point work algorithm is formulated, and it is also presented in the form of a UML class diagram and an activity diagram. The algorithm for creating a training sample for the second neural network from four points is also formulated (for the case when the zone of squares with lost information will run along the entire length of the picture, as it happens in the photo of Talyanok), presented in the form of a UML activity diagram. The neural network will accept 10 values as input, and will output one - the number of sites in the square, information about which is lost. Tensorflow and keras frameworks were used to create all models. The most successful model has almost 2.5 million parameters, the model requires 9.36 MB of RAM. During the tests, it was found that increasing the number of convolution layers does not increase the result. For testing the first model, a picture of the settlement of Maidanetske was submitted, for training a picture of the settlement of Talyanka was used. For the training set, the recognition accuracy was 92%, for testing - 86.5%. The neural network, which implements the algorithm for predicting the number of buildings on lost plots, provides an accuracy of 58% for the Talyanka settlement and 42% for the Maidanetske settlement. This accuracy is much better than a random guess, the probability of which is just over 6%.

Prediction of Sand Production from Poorly Consolidated Formations Using Artificial Neural Network: A Case Study, Nahr Umr Formation in Subba Oil Field

Sand production in poorly consolidated formations is a significant challenge to the oil and gas industry, resulting in reduced production and compromised equipment integrity. The oil and gas industry has recently become interested in data analytics because it has significantly simplified, accelerated, and reduced the cost of data visualization. The intriguing new approaches in artificial intelligence development promise to offer long-term solutions to the increasing problems affecting the petroleum industry's operations. Any completion operation in sandstone formations is based on determining whether or not a well will produce sand. It is economically unfavorable to the Nahr Umr Formation to install sand control equipment for wells that don't produce sand. This study aims to create an efficient and precise artificial neural network that can predict sanding in sandstone formations. To achieve this, we developed a two-layered ANN with a back-propagation algorithm using JMP software. The model formulation included various geological and mechanical factors that could impact sand detachment, such as Young’s modulus (YME), Poisson’s ratio, minimum and maximum horizontal stresses (SHMIN and SHMAX), pore pressure, shale volume, and formation strength. The study acquired data from both local fields, specifically the Amarah oilfield, and non-local fields from the literature. Two sets were created from the data: a training set comprising 75% of the data, and a test set comprising 25% of the data, both of which were classified. The speed and accuracy of a learning process in an Artificial Neural Network depends on the size of the data set, the number of hidden layers, and the input parameters. The statistical measures such as accuracy, confusion matrix, root mean square error, and generalized RSquare demonstrate the strong efficacy of the created Artificial Neural Network model. The results indicate a significant likelihood of sand production occurring over the perforation intervals across Su-4 and Su-5 wells. The method's unique feature is its ability to isolate shale areas and identify weak areas capable of producing sand in sandstone formations. In conclusion, it is determined that an Artificial Neural Network employing the back-propagation algorithm is a simple, reliable, and easy-to-use method for accurately predicting sand production.

Flexural behavior of innovative multifunctional concrete sandwich shells with different types of connectors

AbstractThis study develops an innovative multifunctional concrete sandwich shell based on a combined experimental and finite element (FE) study on its flexural behavior. The sandwich shell is made up of inner and outer concrete layers connected by connectors, with a middle functional layer that provides various functions such as insulation, acoustic, and vibration control. Bending tests were conducted on four groups of specimens, including three groups of sandwich shells with different types of connectors, that is, truss, grid, and plate connectors, and one reference group of solid shells. Loads, displacements, and strains were recorded during the tests. The FE analysis showed good correlation with the experimental results. Furthermore, a parametric study was conducted using the FE model to evaluate the influence of different parameters, such as middle layer thickness and number of connectors. The results show that the performance of the sandwich shell is comparable to, and in some cases better than, that of the solid shell, depending on the type of connectors used. This study provides a proof of concept for the sandwich shell and establishes a prototype structure for future research.

The Impact of 3D Printing Technology on the Improvement of External Wall Thermal Efficiency—An Experimental Study

Three-dimensional printing technology continues to evolve, enabling new applications in manufacturing. Extensive research in the field of biomimetics underscores the significant impact of the internal geometry of building envelopes on their thermal performance. Although 3D printing holds great promise for improving thermal efficiency in construction, its full potential has yet to be realized, and the thermal performance of printed building components remains unexplored. The aim of this paper is to experimentally examine the thermal insulation characteristics of prototype cellular materials created using 3D additive manufacturing technologies (SLS and DLP). This study concentrates on exploring advanced thermal insulation solutions that could enhance the energy efficiency of buildings, cooling systems, appliances, or equipment. To this end, virtual models of sandwich composites with an open-cell foam core modeled after a Kelvin cell were created. They were characterized by a constant porosity of 0.95 and a pore diameter of the inner core of the composites of 6 mm. The independent variables included the different material from which the composites were made, the non-uniform number of layers in the composite (one, two, three, and five layers) and the total thickness of the composite (20, 40, 60, 80, and 100 mm). The impact of three independent parameters defining the prototype composite on its thermal insulation properties was assessed, including the heat flux (q) and the heat transfer coefficient (U). According to the experimental tests, a five-layer composite with a thickness of 100 mm made of soybean oil-based resin obtained the lowest coefficient with a value of U = 0.147 W/m2·K.

Anomalous Behavior in Dark-Bright Splitting Impacts the Biexciton Binding Energy in (BA)2(MA)n-1PbnBr3n+1 (n = 1-3).

Two-dimensional Ruddlesden-Popper series are an excellent system for tuning physical properties of the perovskite by controlling the layer number (n). For instance, bandgap and exciton binding energies of the series gradually increase upon reducing n via enhanced quantum and dielectric confinements. Here, we present findings that challenge the anticipated trend in electron-hole exchange interaction within (BA)2MAn-1PbnBr3n+1 (n = 1-3), which causes spin-dependent exciton level splitting into bright and dark states, where the latter is partially visible near the surface of the Br-based two-dimensional Ruddlesden-Popper series. Contrary to expectations, the smallest gap between bright and dark exciton levels is observed from n = 2 at 10 K. This anomaly results in the strongest biexciton binding between two dark excitons occurring at n = 2, rather than at n = 1 as initially hypothesized. The observed anomaly arises from a phase transition induced by octahedral tilting occurring only for n = 2 near 100 K as confirmed by temperature-dependent optical and X-ray diffraction measurements. Our results show that Coulomb interaction need not vary gradually with n, which can impact the optoelectronic properties of the Ruddlesden-Popper series.

Unraveling the electronic structure and magnetic transition evolution across monolayer, bilayer, and multilayer ferromagnetic Fe3GeTe2

Two-dimensional (2D) van der Waals (vdW) magnets have sparked widespread attention due to their potential in spintronic applications as well as in fundamental physics. Ferromagnetic vdW compound Fe3GeTe2 (FGT) and its Ga variants have garnered significant interest due to their itinerant magnetism, correlated states, and high magnetic transition temperature. Experimental studies have demonstrated the tunability of FGT’s Curie temperature, TC, through adjustments in quintuple layer numbers (QL) and carrier concentrations, n. However, the underlying mechanism remains elusive. In this study, we employ molecular beam epitaxy (MBE) to synthesize 2D FGT films down to 1 QL with precise layer control, facilitating an exploration of the band structure and the evolution of itinerant carrier density. Angle-resolved photoemission spectroscopy (ARPES) reveals significant band structure changes at the ultra-thin limit, while first-principles calculations elucidate the band evolution from 1 QL to bulk, largely governed by interlayer coupling. Additionally, we find that n is intrinsically linked to the number of QL and temperature, with a critical value triggering the magnetic phase transition. Our findings underscore the pivotal role of band structure and itinerant electrons in governing magnetic phase transitions in such 2D vdW magnetic materials.

Experimental study on the heat storage characteristics of rock bed heat storage system with different packing structure

Establishing energy storage systems can provide an effective solution to the challenges posed by the variability and intermittency of renewable energy sources. Among the available options for energy storage, rock-packed bed thermal energy storage systems are widely favored for their performance, cost-effectiveness, and reliability. The more compact the rock packing, the more adequate the heat exchange of the system; however, poorer permeability increases fluid friction losses and pressure drop, which is detrimental to heat transport within the system. The permeability and heat exchange of the system jointly determines its thermal energy storage performance. This study proposes a composite packing scheme utilizing intact rock slabs and broken rock to enhance the thermal energy storage performance of the packed bed. This approach aims to augment heat exchange efficiency and elevate energy storage density while maintaining the bed's commendable permeability. Heat injection and heat extraction experiments of rock beds were conducted to study the heat storage characteristics of the rock-packed bed thermal storage system under different packing structure. In addition, this study investigates the effect of different injection pressures on the storage and release of heat in the system. The results show that the volume of the pore space of the filled bed, serving as the primary domain for gas flow and gas-rock heat exchange, is a decisive factor affecting the packed bed's permeability and heat exchange performance. When the porosity of the packed bed increased from 5.5 % to 9.9 %, its permeability increased from 1.42 × 10−13 m2 to 3.20 × 10−13 m2, yet the thermal exchange efficiency declined from 67.2 % to 65.3 %. Reasonably arranging intact rock slabs and broken rock fill can alter the path of heat transfer within the packed bed, thereby effectively enhancing its heat storage and release performance. For the same pore volume conditions, the heat exchange efficiency of the packed bed is increased by about 10 % by increasing the number of layers of broken rock fill. Additionally, high gas injection pressures can facilitate heat storage and release processes, but it does not mean that this is more efficient. The research findings can guide the selection of packing and injection schemes in packed bed thermal energy storage systems.

On the nonlinear mechanics of hybrid skew aerospace structures

This study proposes a functionally graded (FG) nanocomposite hybrid skew plate element which is fabricated from a polymeric matrix and is reinforced with two well-known nanoscale reinforcements, namely, carbon nanotubes (CNTs) and graphene platelets (GPLs). The Mori–Tanaka approach, the Halpin-Tsai scheme and standard rule of mixtures are employed to estimate the effective mechanical properties of the hybrid plates. To model this structural element, Reddy's third-order shear deformation theory (TSDT) is used. By considering the von-Kármán assumptions and using the Hamilton's principle, the nonlinear static bending and free vibration governing equations are determined. Then the isogeometric analysis (IGA) is employed to establish the structural stiffness and mass matrices of the skew hybrid plates. After validating the correctness of the presented solution procedure with the previously published results, the effects of various variables such as number of layers, distribution pattern of reinforcements (CNTs and GPLs) and their volume fractions, skew angle and width-to-thickness ratio are investigated. It is found that with considering nonlinear von-Kármán relationship in the strain field, the distributions of σxx and σyy about the mid-plane are no longer symmetric.

Enhancement of high-frequency harmonics in resonators using multilayered structures with polarity-inverted layers

Periodically Poled Piezoelectric Film (P3F) stacks have recently been reported as a promising platform for next-generation radio-frequency acoustic filters that extend into cm- and mm-wave bands. By demonstrating the potential for developing high-performance acoustic devices with frequencies up to 20 GHz, P3F structures based on lithium niobate (LiNbO3) films have opened up new possibilities. In this study, the influence of key parameters such as the number of layers, crystal orientation, duty factor, and variation in thicknesses between the layers on the efficiency of the n-th harmonic excitation and spurious modes was examined. To enhance higher-order harmonics, which are suppressed in P3F structures, a novel multilayered stack with Aperiodically Polarized Piezoelectric Films (APPF) is proposed. Optimizing the ratio between layer thicknesses can enhance higher-order harmonics. An optimization principle is described and illustrated by examples of three-layered APPF structures optimized for the generation of antisymmetric Lamb wave harmonics A3-A17, with electromechanical coupling continuously decreasing with frequency. High-frequency modes excited in APPF structures fill the gaps in frequencies and electromechanical coupling coefficients between the modes generated in P3F stacks and can provide greater diversity of device performance.

Fatigue delamination damage analysis in composite materials through a rule of mixtures approach

The present study investigates delamination damage initiation and propagation within a homogenization theory of mixtures, using the concept of virtual layers and virtual interfaces. It eliminates spatial discretization of layers, introducing a resultant damage variable to capture structure’s bulk response under both monotonic and cyclic loads. Fatigue-induced deterioration is classified into sub-critical, critical, and over-critical stages based on interfacial stresses. Calibration is conducted employing the widely-available Wöhler curves for each loading mode independently. An advance-in-time strategy is included in the model to enhance the simulation speed. The reliability of the approach is assessed for crack initiation and propagation separately through standard test coupons, showing good correlation with experimental data in mode I, mode II, and mixed-mode loading conditions. Depending on the calibration procedure adopted, the model is applicable to a wide range of stress ratios. In addition, it could be integrated into any standard finite element framework using the desired number of elements through the thickness regardless of the physical amount of layers. This allows easy modification of stacking sequences or the number of layers within the constitutive law without mesh structure changes, facilitating simulation of large-scale composite laminates with minimal accuracy loss and reduced computational costs.

Influence of Supercritical Conditions on Isothermal Adsorption Capacity Calculation of Methane and Model Optimization.

The study of isothermal adsorption models for coal and methane under supercritical conditions helps us to understand the gas content distribution in coal seams and improve gas management in coal mines. Coal samples from the Hebi mine and Longshan coal mine were selected for this research. Using the weight method, isothermal adsorption curves of supercritical methane at temperatures of 308, 313, and 318 K were measured. The adsorption phase density of supercritical methane was obtained by using the intercept method and model fitting, and the absolute adsorption capacity of methane was calculated. Simultaneously, the pore volume and specific surface area of the coal samples were tested, and the isothermal adsorption model for supercritical methane was studied and optimized. The results indicate that using mercury intrusion, low-temperature N2, and low-temperature CO2 adsorption methods for testing coal sample pore structures allows for multiscale characterization of the coal pore structure. Based on the Gibbs excess adsorption theory, the phase density of methane obtained from the intercept method and model fitting effectively represent the isothermal adsorption curve of supercritical methane. By combination of the specific surface area and pore volume distribution of the coal with the absolute adsorption capacity of methane, the number of methane adsorption layers on the coal surface was calculated to be between 1.11 and 1.3 layers. This suggests that the isothermal adsorption model for supercritical methane on coal is not solely micropore filling or single molecular layer adsorption but primarily single molecular layer adsorption with concurrent micropore filling adsorption. Based on this adsorption mechanism, an L-DA isothermal adsorption model for supercritical methane on coal was established. The L-DA isothermal model shows good fitting results and effectively explains the adsorption characteristics of supercritical methane on coal.