Planar Model Research Articles

Prediction of Shear Strength in Anisotropic Structural Planes Considering Size Effects

It is essential to elucidate the shear mechanical behavior of structural planes to assess the risk to rock masses and protect them from shear failure. Current research on shear mechanical behavior is focused on isotropic structural planes with the same lithology on both sides. However, anisotropic structural planes, commonly found in nature, may exhibit unique mechanical behavior that differs from isotropic structural planes. Therefore, it is necessary to study the factors affecting the shear strength of the anisotropic structural planes. In this paper, the direct shear numerical tests on anisotropic structural planes were carried out using the three-dimensional distinct element code (3DEC) based on the laboratory test. The numerical test results illustrate that the error between the peak shear strength of the numerical test and the laboratory test is basically within 10%. The shear stress-displacement curves of the numerical and laboratory tests are similar, which verifies the accuracy of the numerical test. According to the Barton standard sections, anisotropic structural plane models with different roughness and size were established, and the direct shear numerical tests with different normal stresses were carried out. To predict the peak shear strength of the anisotropic structural planes, one hundred and eighty-one sets of direct shear numerical test data were selected. Normal stress, roughness, compressive strength of soft and hard rock masses, basic friction angle of soft and hard rock masses, and structural plane size were used as input parameters to establish a back propagation (BP) neural network model. The research results show that, under identical conditions, the shear strength of the anisotropic structural planes decreases as the structural plane size increases. On the contrary, the shear strength increases with the increasing structural plane roughness and normal stress. For the BP neural network prediction model, the root mean square error (RMSE) and coefficient of determination (R2) of the training set are 0.441 and 0.957. For the test set, the RMSE is 0.489, and R2 is 0.947, which indicates that the predicted values are in good agreement with the actual values.

Critical manifolds in the dynamics of a two-wheel model of an automobile

Abstract Insight into steering and stability properties of automobiles in critical driving conditions is essential to advance driver assist systems and autonomous driving functions. To study the dynamic properties of an automobile with rear-wheel drive, methods of geometric singular perturbation theory are applied to a planar two-wheel vehicle model. Following a branch of periodic solutions bifurcating from the steady state of the vehicle at the limits of handling, a behaviour similar to a cycle near a homoclinic orbit is observed. The periodic orbit spends most of its period on a segment with an almost constant sideslip angle and slowly varying velocity. This behaviour can be explained by the nearby existence of a critical manifold consisting of a family of stationary solutions and a heteroclinic orbit connecting two points of this critical manifold. For slightly perturbed parameter values the critical manifold is replaced by a slow manifold with very slow dynamics, which governs the dynamics along the observed slow segment. The critical manifold and the heteroclinic orbit are calculated numerically, and good agreement with the derived approximations is obtained.

Photoelasticity as a Tool for Stress Analysis of Re-Entrant Auxetic Structures

The presented study illustrates the use of photoelasticity as an effective tool for validating the results of finite element method (FEM) simulations of auxetic structures. This research focuses on comparing stress distributions in planar auxetic models under symmetrical and asymmetrical loading conditions. Experimental measurements, conducted using an optically sensitive material (PSM-1), were found to align closely with FEM predictions, with deviations within 5%. This agreement highlights the accuracy of both methods, though discrepancies were noted in areas with lower stress levels due to fringe order reading precision. The experimental process makes it possible to take into account real conditions and inaccuracies in production, while numerical modelling is based on ideal conditions. The findings affirm the value of photoelasticity for stress field analysis in complex geometries, particularly for auxetic structures, and underscore its role in verifying and refining computational models. The study concludes that photoelasticity can be a valuable tool for designers and engineers in verifying FEM simulations, even without the use of digital processing and the evaluation of measured data.

ERROR ANALYSIS OF THE MULTI-STAGE METHOD OF DETERMINING THE TRAJECTORY PARAMETERS OF LOW-ORBITAL SPACE OBJECTS DURING EXPERIMENTAL TESTING OF INFORMATION AND COMMUNICATION CONTROL SYSTEMS AND SPACE ENVIRONMENT ANALYSIS

The repulsion of large-scale Russian aggression and other existing threats in the sphere of national security and defense of Ukraine require the accelerated development of space information technologies in the state and determine the urgent need to improve the organization of the use of space technologies in the interests of defense, the creation of the necessary organizational structures, the deployment of modern information and communication systems with the aim of increasing space situational awareness. One of the main tasks of space situational awareness is the necessary level of knowledge about outer space, the characteristics of space objects of various origins, previous, current and projected knowledge about the parameters of their orbital motion. This task becomes particularly relevant due to the adversary's use of its space means of special and radio- technical intelligence and means of commercial organization, including microsatellites, as a result of which there is a need to control the routes of the passage of surveillance satellites with the subsequent development of plans for camouflage and other types of countermeasures and protection of troops. The article formulates the task of evaluating the effectiveness of information and communication systems that are being improved as part of conducting experimental tests as part of the System of Control and Analysis of the Space Situation, which are based on algorithms for processing the results of optical observations for maintaining a catalog of space objects. The value of the systematic errors of the initial determination of the motion parameters of a low-orbit circum-circular space object based on the results of optical observations using a multi-stage method based on the approximation of measurements by a circular model and consistent evaluation of planar and in-plane parameters of the orbit was evaluated. Methodological errors introduced when describing the circular motion model of a low-orbit space object along an elliptical trajectory with a small eccentricity are: according to the parameters of the orbit plane, up to 0,80; by period - up to 4 minutes; by the latitude argument – 0,2. In the case when the observation interval does not exceed 1 minute, the maximum errors in angular parameters do not exceed 0,1, which is quite acceptable for solving practical tasks of determining the orbits of small space objects. The systematic error of the period estimation can be compensated by joint processing of the results of optical observations on different turns of the flight.

Substructural Damage Identification by Reduced‐Order Substructural Boundaries and Improved Particle Filter With Unknown Input for Non‐Gaussian Measurement Noises

Substructural identification has shown privileges compared with direct identification of structures. However, unknown substructural interface forces between adjacent substructures are the key but difficult issues in substructural identification. Current substructural identification methods with full‐order substructural models still encounter ill‐posed identification problems when there are many unknown substructural interaction forces. Thus, it is necessary to study the identification of substructures with reduced‐order substructural boundaries. In addition, current substructural identification based on Kalman filtering still assumes that measurement noises are random Gaussian processes. In this paper, a method is proposed for the identification of substructural damage by reduced‐order substructural boundaries and an improved particle filter with unknown input for non‐Gaussian measurement noises. First, the boundary degrees of freedom of substructural boundaries together with the number of unknown boundary interaction forces are reduced by the characteristic constraint mode approach. Then, based on the reduced‐order model of substructure in modal coordinate, an improved particle filter with unknown inputs is proposed, in which the importance density function and particle generation in particle filtering are established by the unscented Kalman filter with unknown inputs. Finally, substructural damage can be identified without the full observations of acceleration responses at the substructure boundaries. The effectiveness of the proposed method is verified through a numerical substructural damage of a planar frame model.

NUMERICAL INVESTIGATION ON THE INFLOW MACH NUMBER VARIATIONS IN A STRUT INJECTED CAVITY-BASED SCRAMJET COMBUSTORS

The effect of enhancing the air inflow Mach number of a strut-injected cavity incorporated into a scramjet combustor is numerically studied. The computational investigations are performed using the commercial code Ansys Fluent software. The simulation is carried out using the SST k-ω turbulence model with single-step reaction chemistry and a two-dimensional planar model using the Reynolds-averaged Navier-Stokes (RANS) method. The cavities are positioned downstream of the strut injector that are fixed to the top and bottom walls. This configuration enables the analysis of the shock wave pattern and its correlations with shear layer mixing features. Three inflow Mach numbers are opted for the present investigation, i.e., Mach 2.0, 2.5, and 3.0. The investigations are accomplished on the flow pattern, static pressure, and temperature distributions. Performance analyses for the twin cavity designs that fit into the German Aerospace Center (DLR) scramjet are performed throughout the entire combustor length. A reduction in combustion chamber length by 20% and complete combustion is achieved from the twin cavity configuration as compared to the baseline model. The overall pressure drop is increased around 23% due to the formation of additional shock waves from the cavities. Moreover, the combustion zone prolongs along the flow direction due to the increase in the inflow Mach numbers.

CFD ANALYSIS ON DART PAPERPLANE

This research aims to analyze the aerodynamic performances surrounding paper planes. The dart paper plane model was chosen for this work based on the availability of experimental work done by previous researchers. The dart paper plane can be categorized as one of the micro air vehicles (MAV), however, the basic aerodynamic performances have been underestimated by previous researchers and are still open to be explored. In this work, a CFD simulation study on the dart paper plane was utilized by using the ANSYS-CFX module platform. A steady state, incompressible flow Navier-Stokes equation (RANS) combined with the Shear Stress Turbulence (SST) model was used to analyze the flow structure over the dart paper planes. Experimental data availability is used to compare experimental and our simulation results. Based on the validation work, the highest average percentage difference between CLmagnitude, CLmax, and AOAstall between our results and the experimental ones is 11.9%, 29.5%, and 24.2%. However, overall CL trends similarly exhibited with experimental results since the average percentage difference of CLincre magnitude is continuously reduced from 6.48% to 0.9% towards increment of AOA. For drag performance analysis, the overall trend magnitude distribution of our simulation and experimental results consistently increases towards the increment of AOA. The massive CD distribution had overcome the consecutive CL generation, thus decreasing the overall CL/CDmax magnitude.

Comparative analysis of numerical modeling of methods for intensifying inflow to the well, including hydrochloric acid treatment

Relevance. The need to enhance oil recovery from horizontal wells under complex geological and technical conditions. The use of more accurate numerical models, including chemical reactions and the modeling of complex fracture systems, allows optimization of well stimulation, significantly improving both economic and technological efficiency. This is particularly important for developing low-permeability reservoirs and operating under challenging conditions. This work examines the numerical modeling of well inflow stimulation methods using various approaches. For acid treatment modeling, approaches based on changes in well productivity and the use of chemical reactions in the hydrodynamic model were applied. The quality of forecasted technological performance was assessed using real data from an analogous well. As a result, in the case of a real field with extended horizontal wells, additional oil production was achieved through different approaches to acid treatment modeling. Multistage hydraulic fracturing was modeled using planar and discrete fracture models, with only minor discrepancies in the hydrodynamic modeling results between these methods. Aim. To assess the effectiveness of various numerical modeling approaches for well inflow stimulation methods, such as acid treatment and aimed at optimizing oil production from extended horizontal wells. Methods. Numerical models were used to evaluate the effectiveness of stimulation methods, focusing on changes in productivity, the impact of chemical reactions, and sensitivity analysis of treatment parameters. Results and conclusions. It was found that the use of negative skin factors significantly increases oil production compared to models accounting for chemical reactions. Sensitivity analysis of acid volume and concentration helped identify optimal parameters for enhancing acid treatment efficiency. Both modeling approaches (planar and discrete fracture systems) yielded comparable results. Multistage hydraulic fracturing demonstrated a 25000-ton increase in oil production over three years, making it a more effective method than acid treatment.

Toward Spatial Control of Reaction Selectivity on Photocatalysts Using Area-Selective Atomic Layer Deposition on the Model Dual Site Electrocatalyst Platform.

Photocatalytic water splitting is a promising route to low-cost, green H2. However, this approach is currently limited in its solar-to-hydrogen conversion efficiency. One major source of efficiency loss is attributed to the high rates of undesired side and back reactions, which are exacerbated by the proximity of neighboring oxidation and reduction sites. Nanoscopic oxide coatings have previously been used to selectively block undesired reactants from reaching active sites; however, a coating encapsulating the entire photocatalyst particle limits activity as it cannot facilitate both half-reactions. In this work, area selective atomic layer deposition (AS-ALD) was used to selectively deposit semipermeable TiO2 films onto model metallic cocatalysts for enhancing reaction selectivity while maintaining a high overall activity. Pt and Au were used as exemplary reduction and oxidation cocatalyst sites, respectively, where Au was deactivated toward ALD growth through self-assembled thiol monolayers while TiO2 was coated onto Pt sites. Electroanalytical measurements of monometallic thin film electrodes showed that the TiO2-encapsulated Pt effectively suppressed undesired H2 oxidation and Fe(II)/Fe(III) redox reactions while still permitting the desired hydrogen evolution reaction (HER). A planar model photocatalyst platform containing patterned interdigitated arrays of Au and Pt microelectrodes was further assessed using scanning electrochemical microscopy (SECM), demonstrating the successful use of AS-ALD to enable local reaction selectivity in a dual-reaction-site (photo)electrocatalytic system. Finally, interdigitated microelectrodes having independent potential control were used to show that selectively deposited TiO2 coatings can suppress the rate of back reactions on neighboring active sites by an order of magnitude compared with uncoated control samples.

Multi-objective optimization of unconventional airfoils at low Reynolds numbers

The widespread exploration of drones has generated increasing interest in Micro Aerial Vehicles (MAVs). Furthermore, an application that has gained notoriety is the use of aerial vehicles for exploration on Mars. Thus, the quest for efficient aerodynamic profiles for these applications has been intensified. These types of applications operate in a Reynolds number range from 10^4 to 10^5, which is significantly smaller than those commonly found in conventional low Reynolds regimes, such as when commercial drones are adopted. The main objective here is to identify more efficient shapes for airfoils, optimizing them through a multi-objective process aiming to maximize the lift coefficient and minimize the drag coefficient. To achieve this goal, two models of unconventional airfoils were optimized using the Generalized Differential Evolution 3 (GDE3) algorithm. The acquisition of aerodynamic coefficients, essential for evaluating the performance of the evolutionary algorithm, was carried out through simulations using Computational Fluid Dynamics (CFD). The method applied to describe the aerodynamic behavior of the structures proved to be consistent with experimental data. We used two base structures: a cubic Bézier-profile plate and a planar model with two inflections. Employing the aircraft's range or autonomy as decision criteria, it was observed that the cubic Bézier-profile plate presented superior results. Analyzing the graphs of the aerodynamic coefficients in relation to the angle of attack, the considerable increase in the stall point and lift provided by this model is notable. Such improvements, however, were accompanied by a slight disadvantage in the drag coefficient for small or negative angles of attack. It was also found that the evolutionary algorithm resulted in aerodynamic profiles with interesting characteristics for these applications when compared to existing models in the literature. In conclusion, the proposed cubic Bézier-profile plate model proved to be an interesting alternative for applications with a significantly small Reynolds number.

Widths of crossings in Poisson Boolean percolation

Abstract We answer the following question: if the occupied (or vacant) set of a planar Poisson Boolean percolation model contains a crossing of an $n\times n$ square, how wide is this crossing? The answer depends on whether we consider the critical, sub-, or super-critical regime, and is different for the occupied and vacant sets.

Area Selective Atomic Layer Deposition for Spatial Control of Reaction Selectivity on Modelphotocatalysts

Photocatalytic water splitting is one promising route to reducing the cost of H2 production to industrially relevant levels. However, these systems are currently limited in their solar-to-hydrogen efficiency requiring further development in designing highly active and selective reaction sites. Reverse reactions, such as hydrogen oxidation or oxygen reduction, can greatly reduce overall system efficiency and are exacerbated by the close proximity of neighboring particles, which creates locally high concentrations of reactants. Metal oxide coatings have previously been used to selectively block undesired reactants from reaching the active sites, but can be limited in their ability to allow two different desired half reactions to occur as required for photocatalysts. In this work, we target selectively-deposited ALD of oxide films (e.g., TiO2 and SiO2) onto metallic co-catalysts for enhancing reaction selectivity while maintaining a high overall activity. Pt and Au were used an exemplary reduction and oxidation co-catalysts sites, where Au was deactivated towards ALD growth through self-assembled thiol monolayers while TiOx coated Pt suppressed Fe(II) redox reactions while maintaining the hydrogen evolution reaction (HER). The efficacy of the selective ALD growth was assessed through ellipsometry and X-ray photoelectron spectroscopy (XPS), while reaction selectivity was assessed through cyclic voltammetry. A planar photocatalyst model of patterned interdigitated arrays of Au and Pt was developed to further assess the selective ALD on the micron scale. Patterned electrodes were evaluated through cross-sectional scanning transmission electron microscopy with energy dispersive X-ray spectroscopy (STEM-EDS) and XPS, while reaction selectivity towards the HER over Fe(II) reduction was estimated using scanning electrochemical microscopy (SECM). Finally, interdigitated electrodes were used to simulate the effect of neighboring particle photocatalysts, where selectively deposited TiOx showed a significant reduction in reverse reactions over the uncoated samples.

Human-Induced Pluripotent Stem Cell-Derived Neural Organoids as a Novel In Vitro Platform for Developmental Neurotoxicity Assessment.

There has been a recent drive to replace in vivo studies with in vitro studies in the field of toxicity testing. Therefore, instead of conventional animal or planar cell culture models, there is an urgent need for in vitro systems whose conditions can be strictly controlled, including cell-cell interactions and sensitivity to low doses of chemicals. Neural organoids generated from human-induced pluripotent stem cells (iPSCs) are a promising in vitro platform for modeling human brain development. In this study, we developed a new tool based on various iPSCs to study and predict chemical-induced toxicity in humans. The model displayed several neurodevelopmental features and showed good reproducibility, comparable to that of previously published models. The results revealed that basic fibroblast growth factor plays a key role in the formation of the embryoid body, as well as complex neural networks and higher-order structures such as layered stacking. Using organoid models, pesticide toxicities were assessed. Cells treated with low concentrations of rotenone underwent apoptosis to a greater extent than those treated with high concentrations of rotenone. Morphological changes associated with the development of neural progenitor cells were observed after exposure to low doses of chlorpyrifos. These findings suggest that the neuronal organoids developed in this study mimic the developmental processes occurring in the brain and nerves and are a useful tool for evaluating drug efficacy, safety, and toxicity.

Stopping Sets of Algebraic Geometry Codes over Hyperelliptic Curves of Genus Two

Stopping sets are useful for analyzing the performance of a linear code under an iterative decoding algorithm over an erasure channel. In this paper, we consider stopping sets of one-point algebraic geometry codes defined by a hyperelliptic curve of genus g=2 defined by the plane model y2=f(x), where the degree of f(x) was 5. We completely classify the stopping sets of the one-point algebraic geometric codes C=CΩ(D,mP∞) defined by a hyperelliptic curve of genus 2 with m≤4. For m=3, we proved in detail that all sets S⊆{1,2,⋯,n} of a size greater than 3 are stopping sets and we give an example of sets of size 2,3 that are not.

Design of multi-hidden-layer Bayesian neural networks for model updating

Structural health monitoring (SHM) based on artificial neural networks (ANN) has received a lot of attention in recent decades, especially the Bayesian neural network (BNN) approach, which is more robust to noise for training and generalization. Since building a high-quality BNN architecture suitable for a specific task depends highly on user experience, the existing literature generally studies BNNs with simple single-hidden-layer architectures designed by empirical formulas or very few tailor-made algorithms. Multiple hidden layer BNN (MBNN) has a more complex architecture than single hidden layer BNN (SBNN) and is expected to achieve better generalization performance for complex problems. But the corresponding architectural design problem is much more complex, and there is no previous experience in the literature. To achieve this for MBNN, this paper proposes two feasible algorithms to optimize the number of neurons in each hidden layer simultaneously, where a logarithmic evidence metric is introduced to quantitatively characterize the performance of MBNN for a given multi-hidden-layer architecture. The feasibility and effectiveness of the proposed method are verified by the finite element (FE) model updating of both a planar truss model and a real-life pedestrian bridge. The verification results show that the second algorithm is much more computationally efficient for the optimal design of the MBNN architecture and has the potential for practical application.

Experimental and theoretical study of 90Sr/90Y-n-Si/ZnO betavoltaic battery and theoretical prediction of homojunction betavoltaic cells performance

Today, betavoltaic batteries has been considered due to their high energy density and long life for operating electrical systems in inaccessible and hostile environments. Conventional electrochemical batteries, despite their widespread use in electronic devices, have a limited lifetime and tend to degrade in extreme environmental conditions. The current paper pursues three goals. The first goal is to the experimental and theoretical investigation of a n-Si/ZnO heterojunction betavoltaic battery based on 90Sr/90Y source. The second goal is to optimize ZnO, SnO2, BN, and diamond homojunction betavoltaic cells in two planar and cubical models by Monte Carlo simulation (MCNP code). The third goal is to present a new approach for estimating the standard error in calculating the parameters of betavoltaic batteries. In order to fabrication of a n-Si/ZnO heterojunction, the ZnO nanospheres were placed on the n-Si (100) substrate using chemical bath deposition (CBD) technology. The Al and Au electrodes were deposited on the formed sample. Then this sample was exposed to the radiation of an external 90Sr/90Y source with an activity of 12.8 mCi. The experimental values obtained for the short circuit current (Isc), open circuit voltage (Voc), efficiency (η), and maximum output power (Pmax) were 0.047 μA, 0.015 V, 3.4 × 10−4 percent, and 0.141 nW, respectively. To compare with the experiment, we investigated the n-Si/ZnO betavoltaic cell by MCNP code. In the simulation, the beta spectrum of the 90Sr/90Y source was considered. The calculated theoretical values for Isc, Voc, η, and Pmax were 0.063 μA, 0.020 V, 6.4 × 10−4 percent, and 0.265 nW, respectively. The experimental results show that the simulation results can be valid. In the optimization of ZnO, SnO2, BN, and diamond homojunction betavoltaic cells in two planar and cubical models by MCNP code, it was found that the Isc, Voc, η, and Pmax of the cubical model are better compared to the planar model. In the cubical model, Pmax of ZnO, SnO2, BN, and diamond betavoltaic batteries is 2633.34 nW ± 0.16 %, 1670.49 nW ± 0.15 %, 198.20 nW ± 0.17 %, and 1315.24 nW ± 0.15 %, respectively. In other words, Pmax of the ZnO betavoltaic battery is about 58 %, 1229 %, and 100 % more than Pmax of SnO2, BN, and diamond betavoltaic batteries, respectively. Pmax of the SnO2 betavoltaic battery is about 743 % and 27 % more than Pmax of BN and diamond betavoltaic batteries, respectively. The results show that ZnO and SnO2 betavoltaic batteries can perform better compared to BN and diamond betavoltaic batteries. Also, their growth process is less expensive compared to BN and diamond.

Planar cell polarity zebrafish models of congenital scoliosis reveal underlying defects in notochord morphogenesis.

Congenital scoliosis (CS) is a type of vertebral malformation for which the etiology remains elusive. The notochord is pivotal for vertebrae development, but its role in CS is still understudied. Here, we generated a zebrafish knockout of ptk7a, a planar cell polarity (PCP) gene that is essential for convergence and extension (C&E) of the notochord, and detected congenital scoliosis-like vertebral malformations (CVMs). Maternal zygotic ptk7a mutants displayed severe C&E defects of the notochord. Excessive apoptosis occurred in the malformed notochord, causing a significantly reduced number of vacuolated cells, and compromising the mechanical properties of the notochord. The latter manifested as a less-stiff extracellular matrix along with a significant reduction in the number of the caveolae and severely loosened intercellular junctions in the vacuolated region. These defects led to focal kinks, abnormal mineralization, and CVMs exclusively at the anterior spine. Loss of function of another PCP gene, vangl2, also revealed excessive apoptosis in the notochord associated with CVMs. This study suggests a new model for CS pathogenesis that is associated with defects in notochord C&E and highlights an essential role of PCP signaling in vertebrae development.

Stretch-induced wrinkling analysis and experimental validation of creased membranes

Creases and wrinkles are crucial factors affecting the accuracy of membrane structures. In this paper, we study the stretch-induced wrinkling of creased membrane based on a proposed planar crease model by characterizing the crease as an orthotropic rigid strip with effective bending stiffness and initial stress. A control equation of wrinkling of a stretched rectangular membrane with a vertical crease is deduced to understand the crease-wrinkle interaction. Then, a set of scaling laws for the wrinkles is discussed in detail, and it is concluded that the ratio of the bending stiffness of the crease to that of the membrane is the key influence factor. Furthermore, the analysis reveals that wrinkling in the small-strain stage is a localized wrinkling behavior independent of the crease parameters. The wrinkling wavelength and amplitude at large strains decrease with increasing crease angle. Finally, experiments verify the correctness and validity of the theoretical model and analytical method.

Simulation and experimental verification of the orthogonal friction continuous wear of PTFE-Kevlar fabric liner

Woven fabric liners, which are customizable and maintenance-free, have extensive applications in self-lubricating spherical bearings. However, owing to the orthogonal anisotropy and non-homogeneous characteristics, their frictional and wear behaviors are complex. Currently, average performance testing is primarily based on long-term macroscopic wear experiments. However, unobservable parameters such as mesoscopic stress and pressure distribution in liners are bottlenecks in the experimental exploration of wear sources and mechanisms. Therefore, an innovative strategy for modeling orthogonal friction and continuous wear in non-homogeneous liners is presented. This approach has the potential to overcome experimental limitations and significantly expedite liner design and cost-effective validation. The initial step involves establishing a mesoscopic voxel-based planar model of the liner that maintains the topological relationship during wear processes. This is achieved by introducing a circular voxel mesh and spatial transformation methods. Based on orthogonal friction and wear assumptions, separate constitutive models for orthogonal friction and wear are developed. Using the CETR UMT-3 friction and wear testing machine, GCr15 is selected as the counterface material, the pin disc wear method is adopted to conduct sliding test on PTFE and Kevlar fibers, and the required wear constitutive parameters are fitted. Furthermore, incremental equations for the total wear are derived. An element wear fusion strategy is introduced. This approach leads to the development of a continuous wear algorithm for liners and subsequently to the establishment of a voxel-based finite element model with continuous wear capability in the form of a circular voxel grid. This method transcends experimental methods and allows for the determination of the mesoscopic contact pressure, stress distribution, and variations in the contact material composition patterns of liner. The accuracy of the average macroscopic wear prediction is validated experimentally. This method has the potential for practical applications in bearing design.

Fabrication of B-C-N nanosheets on Rh(111) from benzene – borazine mixtures

Atomic level studies of solid state surfaces performed in ultra-high vacuum (UHV) had already an energetic 15–20 years past when our research group in Szeged started working in this field in mid 1970s. Till then several very important methods had been developed, like UHV technology, commercially available electron and photoelectron spectroscopy techniques, etc. Characterization of metal and semiconductor (oxide) surfaces and their adsorption properties had already been widely studied. In any case, the last 40–50 years also witnessed great discoveries and exciting new techniques. Considering only the activity related to heterogeneous catalysis, the main focus of our research group, new breakthrough methods emerged like HREELS, RAIRS, SPM, NAPXPS, EXAFS, NEXAFS. Along this path, new experimental and theoretical approaches appeared like planar model catalysts and inverse catalysts, atomic level investigation and understanding of surface diffusion-controlled phenomena (particle growth and disruption, strong metal-support interaction (SMSI), decoration, spillover), atomic level identification of active sites, self-organized nano-systems, surface alloys and nanotemplates. It was great to participate in this magical activity for more than 50 years. Both internationally and locally in Szeged, in the last two decades, surface science has opened to the wide world of 2D materials like the semimetal graphene and the insulator hexagonal boron nitride. However, the formation of a mixed layer of C, B and N proved to be a difficult task due to the primary tendency for phase separation. In the present work, we report on a preparation method of honeycomb “BCN” materials on Rh(111) by using benzene/borazine mixtures as precursors. It was demonstrated that by a suitable choice of the growth parameters, the formation of large, separated graphene and h-BN islands can be avoided.