Layer Model Research Articles

Heat and mass transfer phenomena for fractal interfacial layer model on metallic-nanomaterials nanofluids flow with chemical reaction effect

This study presents a comprehensive investigation into the intricacies of single-phase simulation concerning the behavior of fractal interfacial magnetized metallic chemical-reactive nanoparticles within fluid systems. The research focuses on unraveling the multifaceted phenomena associated with heat and mass transfer in complex nanoscale environments. To achieve this, we employ numerical techniques to address the intricate fluid flow problems that arise due to the presence of these nanoparticles. Fractal complexities are linked to critical phenomena, such as mixing and mass transport, at the turbulent/non-turbulent interface of shear layers and boundary layers. This study primarily concentrates on the phenomena of heat and mass transfer, with a focus on estimating thermal conductivity models that have significant impacts on the flow of metallic nanofluids under convective conditions. The combination of a high thermal conductivity model with a novel interfacial fractal theory reveals a substantial effect on heat and mass transfer enhancement. Furthermore, this research explores hybrid types of porous channel geometries under the combined influence of magnetohydrodynamics and chemical reaction mechanisms in the presence of metallic nanoparticles. A comprehensive numerical analysis of higher-order nonlinear differential equations is conducted, which exposes the flow field’s behavior concerning momentum, energy, and mass transfer. These insights are envisioned through single-phase simulations of nanofluids. The influence of the nanoparticles’ radius and diameter is found to play a significant role in thermal performance, with nanoparticles ranging from 1% to 8% exhibiting a notable impact on thermal conductivity. Highlights A new mathematical relation of mass, as well as heat transfer for metallic-nanomaterial being affected by thermal conductivity (T.C.), has been established. The important role of the physical number is observed under the effect of T.C. and heat and mass transfer through orthogonal porous surfaces. An injection/suction, as well as an expansion/contraction phenomenon related to the porous surface is observed.

Equivalent thin-layer temperature field model (ETTM) for bolted rotors to describe interface temperature jump

Improving the accuracy and efficiency of predicting the temperature field is a crucial requirement for iteratively calculating and online monitoring the temperature field, particularly for combined structures. The heat flow movement is impeded by incomplete interface contact, resulting in a temperature jump. To address this, the equivalent thin-layer temperature field model (ETTM) is proposed to replace the interface thermal contact conductance (TCC) model. Firstly, the fractal TCC model of a bolt connection is derived based on fractal geometry. Subsequently, the contact surface of the circumferential bolt connection is considered to be the parallel connection of multiple bolt thermal resistances. The TCC of the equivalent thin-layer is obtained. Building on this, the ETTM of the built-up rotor structure is developed. Finally, a temperature field model of the bolted rotor is derived. The validity of models is verified by comparing the model proposed in this paper with the previous research findings and ANSYS analysis results. Numerical simulation results reveal that TCC is influenced by several factors: contact pressure, the nominal contact area within the fractal domain, fractal dimension, fractal roughness, and the root mean square (RMS) height. Furthermore, the effects of the thickness of the thin layer model and the thermal conductivity of the material on heat transfer are examined. Ultimately, the findings indicate that heat transfer at the interface is significantly impeded by thermal contact resistance across various temperature boundary conditions. Notably, lower contact pressure intensifies this impedance.

Cooperative target allocation for air-sea heterogeneous unmanned vehicles against saturation attacks

This paper proposes a cooperative target allocation method for efficiently utilizing air-sea heterogeneous unmanned vehicles to counter saturation attacks by low-cost UAVs. Specifically, a bilevel model that combines the advantages of heuristic algorithms and the coalition formation game (CFG) is constructed by integrating unmanned vehicles' motion and attack attributes. The upper layer model aims to utilize the advantages of the heuristic algorithm to generate a feasible target allocation scheme in a shorter time. A genetic algorithm constrained by inheritance conditions (GAC) is proposed to solve the problem of the low efficiency of traditional genetic algorithms in solving the upper model. The lower layer model is established based on a coalition formation game, which aims to continuously and stably optimize the target allocation scheme. A search method based on mobile players is designed to form a stable coalition structure faster when the number of unmanned vehicles is enormous. Simulation results show the feasibility and superiority of the algorithm proposed in this paper in dealing with allocation tasks of different complexity.

Arsenate and phosphate adsorption onto Mg-Fe layered double hydroxides: The charge-distribution multisite complexation (CD-MUSIC) modeling as a tool to predict competitive oxyanion behavior

The adsorption of arsenate and phosphate onto natural or synthetic layered double hydroxides (LDHs) has emerged as a promising solution to minimize the environmental effects of these compounds in soils and waters. In the present work, the adsorption of these oxyanions onto Mg-Fe LDHs in both single-ion and competitive systems was studied through wet chemistry experiments, solid-state analyses, and advanced surface complexation modeling (SCM). The Mg-Fe LDH showed a good efficiency to remove both As and P, being the pH of the system a major driver for the adsorption levels observed. Adsorption results for competitive systems showed a decrease for both oxyanions compared to the single-ion adsorption systems. The adsorption behavior is mechanistically described using two types of SCM, namely the diffusion layer model (DLM) and the charge-distribution multisite complexation model (CD-MUSIC). The later model captures better the influence of pH and ionic strength on the adsorption of arsenate and phosphate onto LDH in both single-ion and multicomponent systems. The best description of the experimental results was obtained when combining two types of surface complexes, namely monodentate inner-sphere complex at lower pH values and monodentate outer-sphere complex at higher pH values. This model approach provides more detailed information about the surface properties of LDHs, which may be beneficial for future studies dealing with LDHs as reactive phases influencing metal(loid) mobility in water or soil systems.

The method of moments in Jiles–Atherton model based magnetostatic modelling of thin layers

The method of moments in Jiles–Atherton model based magnetostatic modelling of thin layers

Global well-posedness of regular solutions to the 1-D reduced gravity two-and-a-half layer model

Global well-posedness of regular solutions to the 1-D reduced gravity two-and-a-half layer model

Cell sorting by active forces in a phase-field model of cell monolayers.

Cell sorting, the segregation of cells with different properties into distinct domains, is a key phenomenon in biological processes such as embryogenesis. We use a phase-field model of a confluent cell layer to study the role of activity in cell sorting. We find that a mixture of cells with extensile or contractile dipolar activity, and which are identical apart from their activity, quickly sort into small, elongated patches which then grow slowly in time. We interpret the sorting as driven by the different diffusivity of the extensile and contractile cells, mirroring the ordering of Brownian particles connected to different hot and cold thermostats. We check that the free energy is not changed by either partial or complete sorting, thus confirming that activity can be responsible for the ordering even in the absence of thermodynamic mechanisms.

The present-day in-situ stress field and its effect on shale gas development in Zigong area of southern Sichuan Basin

The Zigong area in southern Sichuan Basin is one of the key shale gas production areas in China, and the Longmaxi and Wufeng Formations within it are currently the key exploration and development layers. The present-day in-situ stress field has a significant impact on well trajectory deployment, horizontal well construction, hydraulic fracturing and other aspects. However, it has not been finely quantified in shale gas reservoirs of Zigong area, making it difficult to effectively guide development practice. Therefore, this study constructed a geomechanical model of the target layer in the Zigong area, quantitatively characterized the distribution of present-day in-situ stress, and explored its shale gas development effects. The results show that: (1) Based on the analysis of drilling induced fractures obtained from rock acoustic emission experiments and imaging logging interpretation, the dominant orientation of the maximum horizontal principal stress in the target layer is mainly NW-SE-trending; (2) The horizontal principal stress difference in the Layer S1l1-1−1 and Wufeng Formation is 5–30 MPa (the majority is 6–15 MPa) and 5–35 MPa (the majority is 6–18 MPa), respectively. Low stress difference values are mainly concentrated in the southeastern and northern parts. The overall prediction accuracy is high, with an error rate of less than 8% for the Layer S1l1-1−1 and less than 10% for the Wufeng Formation; (3) Based on rock acoustic emission experiments and finite element model simulation results, the study area is mainly under strike-slip stress faulting mechanism; (4) Due to the influence of the strike-slip faulting stress mechanism, when deploying horizontal wells in the area, priority should be given to selecting areas with low stress mechanism factor (Aφ) and low stress differences, to achieve better fracturing and transformation effects and reduce the risk of casing deformation and wellbore instability.

Tayler–Spruit dynamo simulations for the modeling of radiative stellar layers

Context. Maxwell stresses exerted by dynamo-generated magnetic fields have been proposed as an efficient mechanism to transport angular momentum in radiative stellar layers. Numerical simulations are still needed to understand its trigger conditions and the saturation mechanisms. Aims. The present study follows up on a recent paper where we reported on the first simulations of Tayler-Spruit dynamos. Here we extend the parameter space explored to assess in particular the influence of stratification on the dynamo solutions. We also present numerical verification of theoretical assumptions made previously that were instrumental in deriving the classical prescription for angular momentum transport implemented in stellar evolution codes. Methods. A simplified radiative layer is modeled numerically by considering the dynamics of a stably stratified, differentially rotating, magnetized fluid in a spherical shell. Results. Our simulations display a diversity of magnetic field topologies and amplitudes depending on the flow parameters, including hemispherical solutions. The Tayler-Spruit dynamos reported here are found to satisfy magnetostrophic equilibrium and achieve efficient turbulent transport of angular momentum, following Spruit’s heuristic prediction.

Practical Feature Inference Attack in Vertical Federated Learning During Prediction in Artificial Internet of Things

The emergence of edge computing guarantees the combination of the Internet of Things (IoT) and artificial intelligence (AI). The vertical federated learning (VFL) framework, usually deployed by split learning, can analyze and integrate information on different features collected by different terminals in the IoT. The complete model is divided into a top model and multiple bottom models in a specific middle layer. Each passive party as a terminal with certain features owns a bottom model, and an active party as an edge server with labels holds the top model. Feature inference attack aims to infer the party’s features from the model predictions during prediction in VFL. Existing attacks considered the adversary an active party under the white-box or black-box model. However, an attacker usually is a passive party in practice because terminals are more vulnerable than edge servers. Therefore, this paper discusses a practical feature inference attack in VFL during prediction in IoT under this setting. We design an adversary builds an inference model to minimize the distance between the predictions from the inferred features and target features. Because the information on the top model and other bottom models is unknown, the adversary cannot directly train the inference model. Therefore, we utilize the zeroth-order gradient estimation method to calculate the parameters’ gradients to train the inference model. Experimental results demonstrate that the performance of our attack is comparable to that of the white-box attacks while retaining apparent advantages over the existing black-box attacks.

The Water-Following Performance of Various Lagrangian Surface Drifters Measured in a Dye Release Experiment

Abstract Many different surface drifter designs have been developed recently to track near-surface ocean currents, but the degree to which these drifters slip through the water because of mechanisms associated with the wind is poorly known. In the 2020 Tracer Release Experiment (TReX), 19 drifters of eight different designs, both commercially available and home-built, were simultaneously released with a patch of rhodamine dye. The dye rapidly spread vertically through the mixed layer but also more slowly dispersed horizontally. Although winds were light, drifters moved downwind from the dye patch at speeds of 3–17 cm s−1 (0.6%–4% of wind speed) depending on the design type. Measurements were made of wind and ocean conditions, and these were incorporated into a boundary layer model at the air–sea interface to estimate complete velocity profiles above and below the surface. Then, a steady-state drag model is used with these profiles to successfully predict drifter slip. Drogued drifters (those with a subsurface drag element) can be affected by Eulerian shear in the upper 0.5 m of the water column, as well as the Stokes drift, but undrogued drifters are in addition greatly affected by direct wind drag, and possibly by resonant interactions with waves. The dye, cycling vertically in the mixed layer, is largely unaffected by all of these factors; therefore, even “perfect” surface drifters do not move with a mixed layer tracer. Significance Statement Surface drifters are used by oceanographers to measure ocean surface currents. However, different designs also slip downwind through the water at rates that are poorly known but are typically around a few percent of the wind speed. In 2020 we simultaneously deployed drifters of eight different designs along with rhodamine dye in a field experiment to see how well the different designs track the water. Here we independently and successfully model drifter slippage for the different designs. Slip factors are then estimated for a range of wind and ocean conditions.

Deep Ring-Block-Wise Network for Hyperspectral Image Classification.

Deep learning has achieved many successes in the field of the hyperspectral image (HSI) classification. Most of existing deep learning-based methods have no consideration of feature distribution, which may yield lowly separable and discriminative features. From the perspective of spatial geometry, one excellent feature distribution form requires to satisfy both properties, i.e., block and ring. The block means that in a feature space, the distance of intraclass samples is close and the one of interclass samples is far. The ring represents that all class samples are overall distributed in a ring topology. Accordingly, in this article, we propose a novel deep ring-block-wise network (DRN) for the HSI classification, which takes full consideration of feature distribution. To obtain the good distribution used for high classification performance, in this DRN, a ring-block perception (RBP) layer is built by integrating the self-representation and ring loss into a perception model. By such way, the exported features are imposed to follow the requirements of both block and ring, so as to be more separably and discriminatively distributed compared with traditional deep networks. Besides, we also design an optimization strategy with alternating update to obtain the solution of this RBP layer model. Extensive results on the Salinas, Pavia Centre, Indian Pines, and Houston datasets have demonstrated that the proposed DRN method achieves the better classification performance in contrast to the state-of-the-art approaches.

A study on the Si1-xGex gradual buffer layer of III-V/Si multi-junction solar cells based on first-principles calculations.

III-V/Si multi-junction solar cells have been widely studied in recent years due to their excellent theoretical efficiency (∼42%). In order to solve the problem of lattice mismatch between Si and III-V compounds of III-V/Si solar cells, different hexagonal Si1-xGex buffer layer models on the surface of hexagonal diamond Si(001) were built, and the structural, electronic and optical properties of the proposed models were calculated based on first principles calculations. The results showed that all models of the designed buffer layer could effectively reduce the lattice mismatch, and the buffer layer hex-Si1-xGex (x = 0, 0.75, and 1) is the ideal model and has achieved the best lattice-matching improvement with high defect formation energy, as well as direct band gap properties and a larger light adsorption coefficient. These theoretical models, with their analyzed properties, could offer a promising pathway toward realizing high efficiency and low cost III-V/Si multi-junction solar cells.

Beyond the electrical double layer model: ion-dependent effects in nanoscale solvent organization.

The nanoscale organization of electrolyte solutions at interfaces is often described well by the electrical double-layer model. However, a recent study has shown that this model breaks down in solutions of LiClO4 in acetonitrile at a silica interface, because the interface imposes a strong structuring in the solvent that in turn determines the preferred locations of cations and anions. As a surprising consequence of this organisation, the effective surface potential changes from negative at low electrolyte concentration to positive at high electrolyte concentration. Here we combine previous ion-current measurements with vibrational sum-frequency-generation spectroscopy experiments and molecular dynamics simulations to explore how the localization of ions at the acetonitrile-silica interface depends on the sizes of the anions and cations. We observe a strong, synergistic effect of the cation and anion identities that can prompt a large difference in the ability of ions to partition to the silica surface, and thereby influence the effective surface potential. Our results have implications for a wide range of applications that involve electrolyte solutions in polar aprotic solvents at nanoscale interfaces.

Investigation of transportation infrastructure elements on the example of spherical bridge bearing

Transportation infrastructure consists mainly of critical elements. They are subjected to a large set of requirements for strength, rigidity, reliability. The article considered deformation behavior of spherical bridge bearing at different introduction depth parameters of sliding layer. The influence of contact surface treatment on the character of contact parameters distribution is studied. Earlier the polymers and composites behavior was viewed as an elastic-plastic material. However, for predicting their life-cycle it is necessary to consider them as viscoelastic. The article compared the parameters obtained by modeling elastic-plastic and viscoelastic materials behavior. The influence of sliding layer thickness on the deformation structure behavior was also discussed. It is revealed that sliding layer modeling as an elastic-plastic body is sufficient for numerical calculations on determination of strength characteristics. However, it is necessary to consider the sliding layer as a viscoelastic/viscous-elasticplastic material to design the life cycle of the structure taking into account rheology, thermomechanics and cyclic loads in different directions.

Response surface methodology of the unsteady axisymmetric magnetic hybrid nanofluid flow subject to a shrinking disk

This study examines the unsteady Fe3O4-CoFe2O4/H2O flow over a shrinking disk using both procedures (numerical and statistical). The respective boundary layer model is first transformed into a set of ODEs (ordinary differential equations) using the similarity transformations, and then solved numerically using the bvp4c solver. The duality of solutions is presented within specific use of the parameters such as magnetic field, suction strength and volumetric concentration of hybrid nanoparticles. From the numerical results, the velocity profile increases as the suction and magnetic parameters slightly increase. However, the temperature profile shows a reverse trend as compared to the velocity profile. Meanwhile, the justification of present physical factors (magnetic parameter, suction parameter) whether they are significant or not on the development of responses is tested using the RSM with the fit general linear model in Minitab. In addition, the generated response equation is also beneficial in predicting the flow and thermal distributions of this working fluid for other values of the emerging parameters.

Modeling of the fatigue behavior of functionally graded materials: Study of the residual stresses induced by surface severe plastic deformation

AbstractA new finite elements approach has been used to model the evolution of residual stresses during cyclic loading in functionally graded 316 L stainless steel, obtained by surface severe plastic deformation. The affected layer modeling was divided in two stages: the compressive residual stress state initialization and the update of the mechanical properties characteristic of the gradient microstructure determined from local characterization. The capacity of the model to simulate both the strain‐ and stress‐controlled fatigue behavior was evaluated, and a good consistency between the numerical and experimental results was obtained. Numerical residual stress fields were compared to the experimental measurements, and a very good agreement was observed. A mean error of approximately 65 MPa over all the compared data was measured. Especially, the relaxed and inverted residual stress gradient after the different testing conditions were nicely retrieved, indicating the capabilities of the newly proposed model.

Data-driven semianalytical method for predicting equivalent thickness of flexible pipeline carcass

The carcass layer inside a flexible marine pipeline is a large-angle spiral structure with a complex cross-section. A carcass resists radial loads and prevents flexible pipelines from collapsing under extreme hydrostatic pressures. The accurate evaluation of the critical collapse pressure of a carcass under external pressure is crucial for the safe design of flexible pipelines. Because of the complex cross-section of the carcass, the internal surface of the carcass slides and contacts adjacent layers under external loads, which complicates the analysis. Therefore, the complex cross-section of the carcass is often simplified into a uniform section with a fixed thickness during analysis. In this study, parametric models of the carcass with different cross-sectional parameters were established, and the radial stiffness of the carcass under symmetric radial compression was calculated numerically. Next, the calculated equivalent radial stiffness was introduced into the analytical model to obtain geometric coefficients with different cross-sectional parameters. Finally, symbolic regression was used to derive a mathematical equation relating the equivalent thickness and critical cross-sectional parameters of the carcass. The results showed that the Minimum error in the buckling eigenvalue between the equivalent models and full carcass layer model was 6.2 %, the error in the critical collapse pressure was 14.5 %. Meanwhile, the influence of different parameters on the critical collapse pressure of the carcass was discussed.

Performance of three anion-exchange membranes in fluoride ions removal by electrodialysis.

The performance of three anion-exchange membranes (AEMs) in the fluoride ions reduction by electrodialysis (ED) is performed on real and synthetic water. The electric potential method measures the potential difference (PD) between two synthetic anion solutions separated by ACS, AFN and AXE membranes. The selectivity of these three AEMs coupled with the membrane CMX, is a cation-exchange membrane (CEM) towards different ions. The removal rate is influenced by the thickness of the polarization layer (PL) which reduces the material transfer and provides an additional barrier. The greater the thickness δ of the PL, the longer the passage time and consequently the removal rate of anions is small. Using the unstirred layer model, δ for each ion will be determined. According to the potential measurement method, none of the tested AEMs are selective to fluoride ions and the order of selectivity is as follows: AFN> AXE> ACS. Best membrane couple selected for fluoride ion removal is ACS/CMX and ion selectivity follows the order: Cl-> NO-3>F-> HCO-3> SO42-. For ACS membrane, both the demineralization rate (DR) and δ of fluoride ions are influenced by the initial concentration of the co-ion according to the following order: NO-3> Cl-> HCO-3> SO2-4.

Wetting and Adhesive Properties of Biopolymer-Based Organized Condensed Phases as Drug Delivery Systems

Lyotropic liquid crystalline systems are of great interest as carriers of biological substances for targeted delivery, mainly for transdermal administration of drugs and their application to the skin and mucous membranes. The wetting and adhesive interactions of lyomesophases and gel based on a chitosan polysaccharide in lactic acid solution on a glass substrate (base surface) and the surface of a semi-permeable polytetrafluoroethylene membrane (model of epidermis horny layer) were studied. The effect of the riboflavin drug (vitamin B2) on the surface tension of studied samples and the amount of adhesion work has been established. It is shown that biocompatible chitosan-containing systems can be used as drug carriers for various biomedical purposes, including transdermal drug delivery.