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This paper evaluates the adsorption mechanism of perfluorooctanoic carboxylic acid (PFCA) and heptadecafluorooctane sulfonic acid (HFOSA) on magnetic chitosan for the first time via a statistical physics modeling. Magnetic chitosan (MC-CoFe2O4) was produced from shrimp wastes and used in standard batch adsorption systems to remove PFCA and HFOSA. The experimental isotherms indicated that the maximum adsorption capacities ranged from 14 to 27.12 mg/g and from 19.16 to 45.12 mg/g for PFCA and HFOSA, respectively, where an exothermic behavior was observed for both compounds. The adsorption data were studied via an advanced model hypothesizing that a multilayer process occurred for these adsorption systems. This theoretical approach indicated that the total number of formed layers of PFCA and HFOSA adsorbates is about 3 (Nt = 2.83) at high temperatures (328 K) where a molecular aggregation process was noted during the adsorption. The maximum saturation-multilayer adsorption of PFCA and HFOSA on magnetic chitosan was 30.77 and 50.26 mg/g, respectively, and the corresponding adsorption mechanisms were successfully investigated. Two energies were responsible for the formed adsorbate layer directly on the surface and the vertical layers were computed and interpreted, reflecting that physical interactions were involved to bind these molecules on the adsorbent surface at different temperatures where the calculated adsorption energies ranged from 14 to 31 kJ/mol. Overall, this work provides theoretical insights to understand the adsorption mechanism of PFCA and HFOSA using the statistical physics modeling and its results can be used to improve the adsorbent performance for engineering applications. [ABSTRACT FROM AUTHOR]

Resistive-type superconducting fault current limiters (r-SFCLs) have generated great interest for research and technical applications. This is attributed to their superior features, which include self-action, fast response, and simple operation. In low line impedance systems, r-SFCLs are seen as a viable protective mechanism for limiting high-magnitude fault currents. However, overcurrent caused by faults results in an increased temperature of the r-SFCL, possibly damaging the coils. Thus, the r-SFCL must be appropriately engineered to protect it while still allowing for effective fault current limitation. To achieve this goal, an appropriately sized shunt resistor must be used. Adding a shunt resistor benefits the r-SFCL in several ways, from lowering its maximum temperature to speeding up its recovery. Additionally, the shunt resistor protects the r-SFCL from excessive surges in temperature by giving the current an alternative path to flow down, thus saving it from further damage. A multilayer thermoelectric model was developed to examine the thermoelectrical behavior of the r-SFCL coil throughout a fault occurrence and the subsequent recovery period using three shunt resistors ranging from 4 to 16 Ω. MATLAB®/Simulink was used as the simulation platform in this study. The dependence of the current limitation capability and the voltage profile on the shunt resistor value was studied compared to the basic case without an r-SFCL. Increasing the shunt resistor value led to an enhanced ability to limit fault currents, although at the cost of higher temperatures and a longer recovery time. This study also presents guidance for optimizing the design parameters of r-SFCLs. [ABSTRACT FROM AUTHOR]

This study aims to determine the effectiveness of implementing a multilayer model in lesson plan (LP) to increase the vocabulary knowledge of deaf students. This study is single-subject research with an A-B-A design (baseline-intervention-maintenance). The intervention instrument used was a LP that consisted of four units, each containing four words taught using multilayers. The instrument was validated and scored 4.6 on a scale of 1-5. The subjects who participated in the study were two students with severe deafness. Two teachers and two observers were involved in this study. The data were analyzed by inspecting the graph, intracondition, and intercondition. The percentage of non-overlapping data (PND) from the inter-condition was used to indicate the effectiveness of the intervention. It was found that the mean value of PND B/A for all LP from subject-1 was 96.25%, and from subject-2 was 100%. Thus, the multilayer model is very effective in improving vocabulary knowledge. The mean of PND A/B was 93.75%, and subject-2 achieved 89.87%, which means that the subject's vocabulary knowledge is maintained even without intervention. [ABSTRACT FROM AUTHOR]

The interception by the lower (abaxial) side of needle leaves not only contributes to the forest evapotranspiration but will also cause a diffusion barrier of CO2 over the stomata and depresses the plant gas exchange. This study combined the eddy covariance (EC) technique and leaf wetness measurement with a soil–vegetation–atmosphere transfer (SVAT) multilayer model to examine the occurrence of interception evaporation from both sides of leaves at a Japanese cypress forest canopy relating to rainfall intensity and different wetting periods. We compared the measured latent heat flux (λE) with the simulated wet canopy λE with two models that interception evaporation only happens from the upper (adaxial) side of leaves and both sides of leaves. Both models showed a low λE during the rainfall as the EC data did. The simulated λE at the wet period after rainfall indicates that the interception evaporation from both sides of leaves is more likely to happen after heavy rainfall (>15 mm/12 h). However, for the most frequent small rainfall events (0–5 mm/12 h) at this site, interception evaporation is more likely to occur only from the adaxial side than both sides, which helps the wet leaves to maintain stomata opening and process CO2 uptake after rainfall. [ABSTRACT FROM AUTHOR]

This study presents a new approach to solve the one-dimensional solute transport equation with variable coefficients and two input sources in a finite porous media. The medium is divided into m-layers porous media with constant averages coefficients in each transport problem. The transport equations in layer i-1 and i are coupled by imposing the continuity of solute concentration and the dispersive flux at the interfaces of the layers. Unknown functions representing the dispersive flux at the interfaces between adjacent layers are introduced allowing the multilayer problem to be solved separately on each layer in the Laplace domain before being numerical inverted back to the time domain. The obtained solution was compared with the Generalized Integral Transform Technique (GITT) and numerical solutions for some problems of solute transport with variables coefficients in porous medium present in the literature. The results show a good agreement between both solutions for each of the studied problem. An example of application considering an advective-dispersive transport problem with a sinusoidal time-dependent emitting rate at the boundary was study in order to illustrate the effect of sinusoidal frequency on solute concentration. [ABSTRACT FROM AUTHOR]

When an aircraft passes through clouds containing supercooled water droplets, the leading edge's surface will gradually accumulate ice. Ice surface roughness is an important parameter affecting the local convective heat transfer coefficient and the water collection coefficient, which in turn affect the ice's shape. However, because the surface roughness of aircraft icing is a transient value varying in time and space, it is extremely difficult to measure with existing methods in real time. In this study, a noncontact ultrasonic pulse-echo (UPE) technique is applied to characterize the ice roughness of an airfoil model's surface. A multilayer model with equivalent bead-like roughness profiles is established to study the effects of changes in ice roughness on ultrasonic echo signals. A series of simulations indicated that ice roughness can be measured quantitatively and effectively in the range of [11.6, 120] μm. Based on these simulations, an experimental UPE device was developed to measure echo signals on top of the ice corresponding to surface roughness. The results show that for both the regular and irregular surface roughness samples, the maximum relative error in the roughness is less than 15%. Meanwhile, we designed and supplemented the experiment with the NACA-0012 airfoil model to realize the online measurement of ice roughness in an icing research tunnel. [ABSTRACT FROM AUTHOR]

Early detection of faults in photovoltaic (PV) systems is crucial for improving their lifespan and reliability. Conventional protection devices may not be able to detect electrical faults under critical conditions. This usually occurs due to (i) the current-limiting nature and non-linear output characteristics of PV arrays, (ii) the changing environmental conditions (such as irradiance and temperature variations), and (iii) the influence of the maximum power point tracker (MPPT), particularly in the presence of critical fault impedance values or mismatch levels. Therefore, modern data-driven methods are required for fault detection and classification in PV arrays. However, careful investigation in previous studies reveals the existing gaps and limitations, such as poor accuracy, and incomprehensive models which have not considered various electrical faults, low mismatch levels, and critical fault impedance values. To this end, in this study, a comprehensive multilayer model is proposed which consists of six layers for diagnosis, classification and severity identification of electrical faults in PV arrays. Each layer adopts a weighted ensemble learning (WEL) algorithm consisting of three classifiers namely Support Vector Machine (SVM), Naïve Bayes (NB) and Logistic Regression (LR). Besides, a genetic algorithm (GA) is employed in each layer to find the optimal weights for each classifier (i.e., SVM, NB and LR). The initial dataset is acquired through an investigation into the PV array current–voltage (I-V) characteristic curve and extraction of several features under various faulty and normal conditions. To reduce the dataset dimensionality thus computationally simplifying the training process, the sequential floating forward selection (SFFS) algorithm is utilized in each layer as a powerful feature selection technique. The results show a highly accurate performance in fault diagnosis, classification, and severity assessment, with an average simulation and experimental accuracies of 98.9% and 98.37%, respectively. [ABSTRACT FROM AUTHOR]

Resistive-type superconducting fault current limiters (r-SFCLs) have generated great interest for research and technical applications. This is attributed to their superior features, which include self-action, fast response, and simple operation. In low line impedance systems, r-SFCLs are seen as a viable protective mechanism for limiting high-magnitude fault currents. However, overcurrent caused by faults results in an increased temperature of the r-SFCL, possibly damaging the coils. Thus, the r-SFCL must be appropriately engineered to protect it while still allowing for effective fault current limitation. To achieve this goal, an appropriately sized shunt resistor must be used. Adding a shunt resistor benefits the r-SFCL in several ways, from lowering its maximum temperature to speeding up its recovery. Additionally, the shunt resistor protects the r-SFCL from excessive surges in temperature by giving the current an alternative path to flow down, thus saving it from further damage. A multilayer thermoelectric model was developed to examine the thermoelectrical behavior of the r-SFCL coil throughout a fault occurrence and the subsequent recovery period using three shunt resistors ranging from 4 to 16 Ω. MATLAB®/Simulink was used as the simulation platform in this study. The dependence of the current limitation capability and the voltage profile on the shunt resistor value was studied compared to the basic case without an r-SFCL. Increasing the shunt resistor value led to an enhanced ability to limit fault currents, although at the cost of higher temperatures and a longer recovery time. This study also presents guidance for optimizing the design parameters of r-SFCLs.

From the recent empirical discovery of the quantum anomalous Hall effect (QAHE), the interaction of the particle with spin–orbit coupling (SOC) plays an essential role in the cause of the QAHE, which includes three terms: external, internal, and chiral symmetric terms. Then, the non-Abelian quantum field theory was adopted to analyze and prove the conjecture on the causes that can lead to the fractional quantum Hall effect (FQHE). The spontaneously topological chiral symmetry breaking is the main contribution to the FQHE, which also includes two terms: the hopping of sublattice and Coulomb energy by the interaction of many-body particles. More generally, this exciton possesses an intermediate characteristic between the Wannier regimes and displays a peculiar two-dimensional wavefunction in the three-dimensional FQHE states. Finally, a bilayer three-dimensional model is proposed to implement the FQHE on the lattice by incorporating ferromagnetic dopants into three-dimensional topological insulative thin films. This study theoretically predicts the FQHE on the basis of other reports that have experimentally verified the rationality of the proposed model in magnetic topological insulators.

The transition to Industry 4.0 highlights areas of research that require a qualitative description of a complex system, for example, a cyber-physical one, in the form of an adaptive dynamic model since the systems themselves are subject to change over time under various, sometimes unknown factors. In this paper, we test a new method for refining a mathematical model and building a medium-term forecast based on processing dynamic measurements. In the context of the need to reduce processing time and model complexity, we use our multilayer models based on mesh methods applied to a variable-length time interval. The methods we have developed are an alternative way of constructing approximate functional solutions of differential equations. In this paper, this approach is used to solve the Duffing equation with a variable parameter. The basic methods are universal iterative formulas for first-order differential equations in the form of various modifications of the Euler method and Störmer's method for second-order equations. The article presents the results of calculating the execution time of iterations and their comparative analysis, as well as a preliminary assessment of the presence of significant differences in the applied schemes using the Friedman test for a sample with unchanged parameters and pair wise comparison using the Wilcoxon test to determine the nature of the difference in values. We performed the calculations using the Wolfram Mathematica package and analyzed them using the built-in functions of the Excel package. The data obtained help to optimize the use of schemes for practical purposes, thus, our comparative study of the properties of different models allows us to choose the most suitable model depending on the specific problem being solved. On the basis of these data, in the future, it is possible to develop a system that automatically selects the most acceptable method for solving the problem determined by the input data.

Traditional heat transfer analysis has been adopted to predict the damage in a tunnel under fire without considering the effect of concrete spalling, which leads to underestimation of the fire damage of concrete. However, accounting for the spalling effect of concrete under high temperature in an analytical heat transfer model is difficult because of the complexity of the spalling mechanism. This study aims to establish an analytical model to estimate the influence of concrete spalling on the fire-damage depth prediction. To overcome this challenge, first, a series of fire tests were conducted in a unidirectional heating system. The spalling phenomenon and spalling characteristics were observed. Based on the experimental test results, the moisture content of concrete is one of the key factors of spalling. Obvious layered spalling characteristics of concrete samples without drying could be observed under the unidirectional heat conduction system. The critical temperature of spalling is 600 °C, and the thickness of the spalling layer is 2 cm~2.5 cm. These two parameters are critical spalling conditions. Second, a multilayer model for the heat transfer analysis considering the spalling effect of tunnel lining under fire was proposed. By using Laplace transform and the series solving method for ordinary differential equations, the time-dependent temperature and stress fields of concrete lining during tunnel fire could be obtained, which are the basis of damage evolution. The analytical results agreed with the experimental data. The spalling depth of tunnel lining related to the temperature rise of tunnel fire could be predicted by using the proposed analytical model. The results of this research can be used to provide a better damage evaluation of tunnel lining under fire. [ABSTRACT FROM AUTHOR]

[Display omitted] • Hf 4 f peaks identified for hafnia, hafnium silicate, and their nitrided forms. • The composition of nitrided hafnia is HfO 1.66 N 0.33. • A Si2+-2N1- dipole layer at the interface causes a shift of the spectra. • Saturation shows that excited N 2 + ions are the nitridation agent for hafnia. • Hafnium silicate nitrides sooner than hafnia in HfO 2 /Si structures. • Lower plasma pressure enhances the nitridation of hafnia. We report a comprehensive quantitative ARXPS study of 20-cycle ALD-grown HfO 2 films on Si (0 0 1) substrates with and without remote plasma nitridation. The films comprised a 0.6 nm HfO 2 layer atop a 1 nm hafnium-rich silicate interlayer. A detailed analysis of the Hf 4 f , Si 2 p , O 1 s , C 1 s , and N 1 s core level spectra is presented for samples with and without nitridation. The fitting of the Hf 4 f spectra reveals four contributing components associated with silicate, hafnia, and their respective nitrided species. The Hf 4 f , O 1 s , and C 1 s spectra exhibit a negative binding energy shift of about 0.2 eV upon nitridation induced by a Si2+-N dipole formed at the interface. Quantitative ARXPS analysis, employing the MultiLayer Model, enabled the determination of the thicknesses, and composition together with their associated uncertainties. The analysis showed that the composition of the nitrided hafnia is HfO 1.66 N 0.33. There is a higher degree of nitridation in the silicate interlayer compared to the overlying hafnia layer. The degree of nitridation is found to increase with plasma power; N 2 + is identified as the primary plasma species responsible for the nitridation of hafnia. [ABSTRACT FROM AUTHOR]

[Display omitted] • Changes in surface chemistry of a bulk metallic glass upon sliding were evaluated. • The composition of the surface oxide is not affected by tribological conditions. • The oxide thickness is affected by the stress level at contact the trailing edge. Bulk metallic glasses (BMGs) are promising structural materials owing to their high elastic limit and yield strength-to-weight ratio. While BMGs also exhibit attractive tribological properties (e.g. , high wear resistance), the scientific basis for this behavior is not yet established. In particular, tribologically-induced changes in surface chemistry upon sliding are still an open topic of research. Here, we evaluated by X-ray photoelectron spectroscopy (XPS) the evolution of the surface chemistry of Vitreloy 105 (a Zr-rich BMG) upon sliding under different contact conditions against a tungsten carbide countersurface. The spectroscopic results indicate that the relative fraction of the metallic elements in the near-surface region is not affected by the sliding speed when the applied contact pressure is lower than 1.37 GPa, while a decrease in metallic zirconium was observed at lower sliding speeds and higher applied contact pressure (i.e. , 1.71 GPa). Based on the spectroscopic results, a model is proposed for the effect of mechanical stress on the extent of oxidation of the near-surface region of Zr-based BMGs. The results of this work provide novel insights into the surface phenomena occurring on BMGs upon sliding and add significantly to our understanding of the tribological response of this class of promising structural materials. [ABSTRACT FROM AUTHOR]

In this paper, a synthesized zeolite (ZSM-5) is used as an adsorbent to analyze the adsorption phenomenon of carbon dioxide. This investigation, based on the statistical physics treatment, applied the multilayer model with saturation to understand the CO2 adsorption on four samples, namely M-ZSM-5 (M = Na+, Mg2+, Zn2+, La3+), at various temperatures T = 0 °C, 30 °C and 60 °C. The modeling results indicated that CO2 adsorption occurred via a non-parallel orientation on the ZSM-5 surface. The CO2 adsorption capacities varied from 26.14 to 28.65 cm3/g for Na-ZSM-5, from 25.82 to 27.97 cm3/g for Mg-ZSM-5, from 54.82 to 68.63 cm3/g for La-ZSM-5 and from 56.53 to 74.72 cm3/g for Zn-ZSM-5. Thus, Zn-ZSM-5 exhibits the highest adsorption amount. The analysis of the adsorption energies shows that the adsorption of CO2 on ZSM-5 zeolite is a physisorption phenomenon that could be controlled thanks to the energy parameters obtained via the numerical findings using the multilayer statistical model. Finally, the distribution of site energy was determined to confirm the physical character of the interactions between adsorbate/adsorbent and the heterogeneity of the zeolite surface. [ABSTRACT FROM AUTHOR]

Porous materials have been widely investigated as a mean for noise reduction. Numerical simulations can be used to investigate the physical mechanisms responsible for noise reduction; however, a correct modeling of the porous medium through an equivalent fluid model is essential to minimize the computational costs. This paper reports a detailed review of a few applications of the equivalent fluid model based on a three-layer approach, a method that is particularly useful to account for the variation of porous material thickness in aerospace applications. The multilayer approach has been applied in three relevant aerodynamic noise issues: leading-edge impingement noise, turbulent boundary-layer trailing-edge noise, and jet installation noise. Comparison with experiments is used to validate the simulation approach. [ABSTRACT FROM AUTHOR]

When an aircraft passes through clouds containing supercooled water droplets, the leading edge’s surface will gradually accumulate ice. Ice surface roughness is an important parameter affecting the local convective heat transfer coefficient and the water collection coefficient, which in turn affect the ice’s shape. However, because the surface roughness of aircraft icing is a transient value varying in time and space, it is extremely difficult to measure with existing methods in real time. In this study, a noncontact ultrasonic pulse-echo (UPE) technique is applied to characterize the ice roughness of an airfoil model’s surface. A multilayer model with equivalent bead-like roughness profiles is established to study the effects of changes in ice roughness on ultrasonic echo signals. A series of simulations indicated that ice roughness can be measured quantitatively and effectively in the range of [11.6, 120] μm. Based on these simulations, an experimental UPE device was developed to measure echo signals on top of the ice corresponding to surface roughness. The results show that for both the regular and irregular surface roughness samples, the maximum relative error in the roughness is less than 15%. Meanwhile, we designed and supplemented the experiment with the NACA-0012 airfoil model to realize the online measurement of ice roughness in an icing research tunnel.

This paper investigates the topology optimization of planar cooling channels using a low-cost multilayer thermofluid model. A novel three-layer model including the upper/lower cover-plate layers and the central solid-fluid mixing layer is proposed. The flow boundary layer effect and the heat transfer effect in the thickness direction are modeled as the flow coupling and thermal coupling effects between adjacent layers, respectively. Particularly, in order to estimate more accurate temperature fields, the constructed three-layer heat transfer model in the solid-fluid mixing channel is derived based on the assumption of adaptive temperature profiles in the thickness direction. Further, based on the three-layer thermofluid model, the porosity field is introduced to describe the channel's topology, and the corresponding topology optimization scheme is presented. Several optimized channels under different constraints and boundary conditions are shown and discussed in comparison. Optimized channels show streamlined boundaries and reasonable layouts and exhibit competitive heat dissipation performance. Parametric studies are conducted to analyze the effectiveness and reliability of the topology optimization scheme. Further, to evaluate the accuracy and efficiency of the proposed three-layer model, optimized channels are simulated with the full 3D model and previous low-cost models. The proposed three-layer model exhibits good consistency with the full 3D model while achieves great improvement in efficiency. [ABSTRACT FROM AUTHOR]

[Display omitted] • Improved method by fabricating three-layer electrode experimentally. • Comprehensive cross-validation for analysis of binder distribution within electrode. • Simulation for understanding charge-transfer mechanism within the model electrode. The loading levels of composite electrodes are increasing continuously to satisfy the energy density requirements of lithium-ion batteries (LIBs) in electric vehicles (EVs). Furthermore, a faster coating and drying process in the mass-production line yields a nonuniform binder distribution. Thus, it is necessary to understand its distribution within the composite electrode and control it for a better and more reliable electrochemical performance. Therefore, we propose the utilization of an advanced multilayer electrode model consisting of several electrode layers with different binder contents. Using these controlled electrode models, the adhesive strength within each layer was examined using a surface and interfacial cutting analysis system (SAICAS). This was followed by a composition analysis using EDX on each surface. Subsequently, the electronic conductivities of the model electrodes were measured using an electrode resistance meter to determine the bulk and interfacial electrode resistances. Furthermore, the electrochemical properties of each model electrode were evaluated to correlate their relationships and design the optimum binder distribution. Thus, this multilayer model provides a highly effective platform for determining the optimum binder distribution in highly loaded composite electrodes for high-energy–density and long-lasting LIBs. [ABSTRACT FROM AUTHOR]

Traditional heat transfer analysis has been adopted to predict the damage in a tunnel under fire without considering the effect of concrete spalling, which leads to underestimation of the fire damage of concrete. However, accounting for the spalling effect of concrete under high temperature in an analytical heat transfer model is difficult because of the complexity of the spalling mechanism. This study aims to establish an analytical model to estimate the influence of concrete spalling on the fire-damage depth prediction. To overcome this challenge, first, a series of fire tests were conducted in a unidirectional heating system. The spalling phenomenon and spalling characteristics were observed. Based on the experimental test results, the moisture content of concrete is one of the key factors of spalling. Obvious layered spalling characteristics of concrete samples without drying could be observed under the unidirectional heat conduction system. The critical temperature of spalling is 600 °C, and the thickness of the spalling layer is 2 cm~2.5 cm. These two parameters are critical spalling conditions. Second, a multilayer model for the heat transfer analysis considering the spalling effect of tunnel lining under fire was proposed. By using Laplace transform and the series solving method for ordinary differential equations, the time-dependent temperature and stress fields of concrete lining during tunnel fire could be obtained, which are the basis of damage evolution. The analytical results agreed with the experimental data. The spalling depth of tunnel lining related to the temperature rise of tunnel fire could be predicted by using the proposed analytical model. The results of this research can be used to provide a better damage evaluation of tunnel lining under fire.

In this paper, a synthesized zeolite (ZSM-5) is used as an adsorbent to analyze the adsorption phenomenon of carbon dioxide. This investigation, based on the statistical physics treatment, applied the multilayer model with saturation to understand the CO2 adsorption on four samples, namely M-ZSM-5 (M = Na+, Mg2+, Zn2+, La3+), at various temperatures T = 0 °C, 30 °C and 60 °C. The modeling results indicated that CO2 adsorption occurred via a non-parallel orientation on the ZSM-5 surface. The CO2 adsorption capacities varied from 26.14 to 28.65 cm3/g for Na-ZSM-5, from 25.82 to 27.97 cm3/g for Mg-ZSM-5, from 54.82 to 68.63 cm3/g for La-ZSM-5 and from 56.53 to 74.72 cm3/g for Zn-ZSM-5. Thus, Zn-ZSM-5 exhibits the highest adsorption amount. The analysis of the adsorption energies shows that the adsorption of CO2 on ZSM-5 zeolite is a physisorption phenomenon that could be controlled thanks to the energy parameters obtained via the numerical findings using the multilayer statistical model. Finally, the distribution of site energy was determined to confirm the physical character of the interactions between adsorbate/adsorbent and the heterogeneity of the zeolite surface.

The atmospheric gas disturbance effect is modeled using the problem of the cutoff mode of the propagation of an acoustic wave. The atmosphere is approximately described as a 1D multilayer with an exponential density structure in each layer. The cutoff mode determining the propagation direction is defined at the layer boundaries and at the water–air interface. The relationship between atmospheric parameters (pressure, density, and velocity) is found using projection operators on the z-evolution operator subspace for each layer. As a result, we obtain the spectral composition of the acoustic disturbance of the atmosphere at any height, including ionospheric altitudes, which can be used to calculate ionospheric effects. [ABSTRACT FROM AUTHOR]

Wang, G.; Liang, Q.; Zheng, J., and Wan, P., 2019. A new multilayer nonhydrostatic formulation for surface water waves. Journal of Coastal Research, 35(3), 693–710. Coconut Creek (Florida), ISSN 0749-0208. This work presents a new multilayer nonhydrostatic formulation for surface water waves. The new governing equations define velocities and pressure at an arbitrary location of a vertical layer and only contain spatial derivatives of maximum second order. Stoke-type Fourier and shoaling analyses are carried out to scrutinize the mathematical properties of the new formulation, subsequently optimizing the representative interface and the location to define variables in each layer to improve model accuracy. Following the analysis, the one-layer model exhibits accurate linear and nonlinear characteristics up to kd = π, demonstrating similar solution accuracy to the existing second-order Boussinesq-type models. The two-layer model with optimized coefficients can maintain its linear and nonlinear accuracy up to kd = 4π, which boasts of better solution accuracy a larger application range than most existing fourth-order Boussinesq model and two-layer Boussinesq models. The three-layer model presents accurate linear and nonlinear characteristics up to kd = 10π, effectively removing any shallow water limitation. The current multilayer nonhydrostatic water wave model does not predefine the vertical flow structures, and more accurate vertical velocity distributions can be obtained by considering the velocity profiles in coefficient optimization. [ABSTRACT FROM AUTHOR]

Abstract In this research, the physicochemical characteristics of crystal violet (CV) adsorption on raw and modified nanosilica were elucidated through statistical physical models coupled with sites energy distribution. Experimental equilibrium isotherms of Crystal Violet adsorption on raw and modified nanosilica were recorded at four temperatures. Experimental results clearly indicated that the adsorbents presented typical multilayer isotherms and also, that the modified nanosilica was better to remove CV dye. Then, BET, modified BET and infinity multilayer models were fitted with the experimental isotherm data. The infinity multilayer model has agreed satisfactorily with the adsorption data. This model was used to interpret the adsorption process. The model is defined by several parameters which are able to describe the position of CV on the adsorbent surface, the adsorption quantity, the total formed layers during the adsorption process and the adsorption energies. All these parameters were characterized by several physicochemical aspects and interpreted aiming to elucidate the CV adsorption process. The site energy distribution was evaluated at different temperatures to verify the interactions adsorbate/adsorbent and the surface heterogeneity. Highlights • Study of crystal violet adsorption on raw and modified nanosilica. • Application of statistical physics model to attribute new microscopic interpretation • Study of sites energy distribution [ABSTRACT FROM AUTHOR]

Abstract With the rapid development of the fast charge technology and increasing of energy density, battery thermal management system (BTMS) is more and more important to ensure the safety and good performance of the battery system. A multilayer electro-thermal coupling model is developed to study the thermal performance of battery module. It is found that uniform heat source model can lead to great error of the BTMS design. Temperature difference in the multilayer model is as big as two times of that in uniform heat source model when the convective heat transfer coefficient is 5 W*m-2. Increasing the convective heat transfer coefficient can't decrease the temperature difference of the battery module but can decrease the maximum temperature. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • A successful growth method to epitaxy InAsBi layer on (0 0 1) GaAs substrate is proposed. • Significantly reflectivity signal change during both InAsBi and InAs growth stages. • A wide peak of HRXRD that can be attributed to InAsBi inhomogeneous layer. • Our growth method provides inhomogeneous InAsBi layer with different Bi regions. Abstract We suggest a successful growth method for InAsBi layer epitaxy on (0 0 1) GaAs substrate. An alternated trimethylbismuth flows was used during growth. For real time monitoring of the metalorganic vapor-phase epitaxy of InAsBi layer, we use spectral reflectance. Reflectivity signal is found to change significantly during both InAsBi and InAs growth stages. High-resolution X-ray diffraction (HRXRD) curve shows a wide peak that can be attributed to InAsBi inhomogeneous layer. Based on the signals of several wavelengths in situ monitoring system, the related information of growth rate, refractive index n and the extinction coefficient k of InAs and InAsBi sequences were determined. Simulation results indicate different Bi regions. Theoretical simulation of reflectivity signals was carried out by recurrence method using a multilayer model. Results were ex-situ correlated with atomic force microscopy measurements. [ABSTRACT FROM AUTHOR]

Bone marrow biopsy (BMB) needles are frequently used in medical procedures, including extracting biological tissue to identify specific lesions or abnormalities discovered during a medical examination or a radiological scan. The forces applied by the needle during the cutting operation significantly impact the sample quality. Excessive needle insertion force and possible deflection might cause tissue damage, compromising the integrity of the biopsy specimen. The present study aims at proposing a revolutionary bioinspired needle design that will be utilized during the BMB procedure. A non-linear finite element method (FEM) has been used to analyze the insertion/extraction mechanisms of the honeybee-inspired biopsy needle with barbs into/from the human skin-bone domain (i.e., iliac crest model). It can be seen from the results of the FEM analysis that stresses are concentrated around the bioinspired biopsy needle tip and barbs during the needle insertion process. Also, these needles reduce the insertion force and reduce the tip deflection. The insertion force in the current study has been reduced by 8.6% for bone tissue and 22.66% for skin tissue layers. Similarly, the extraction force has been reduced by an average of 57.54%. Additionally, it has been observed that the needle-tip deflection got reduced from 10.44 mm for a plain bevel needle to 6.3 mm for a barbed biopsy bevel needle. According to the research findings, the proposed bioinspired barbed biopsy needle design could be utilized to create and produce novel biopsy needles for successful and minimally invasive piercing operations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Summary: This paper describes a pressure correction method for single‐ and multilayer open flow models. The method does not require any complex procedures to solve the discretization of the Poisson equation and is distinguished by a high computational efficiency. The algorithm can easily be adapted to irregular meshes and parallelized. Parabolic interpolation of the pressure profile is used for the free surface. The discretization of the Poisson equation is written in a matrix form, allowing its usage also in the case of basic function expansion of the depth pressure profile. The paper presents the results of algorithm verification where experimental data sensitive to the numerical dissipation of the calculation model was used. Iteration convergence is high including problems with dry‐bed flooding. The complete described technique of pressure correction is implemented in OpenCL on the GPU. Computation time for a test problem solved using CPU and GPU is compared. [ABSTRACT FROM AUTHOR]

We present here numerical modelling of granular flows with the μ ( I ) rheology in confined channels. The contribution is twofold: (i) a model to approximate the Navier–Stokes equations with the μ ( I ) rheology through an asymptotic analysis; under the hypothesis of a one-dimensional flow, this model takes into account side walls friction; (ii) a multilayer discretization following Fernández-Nieto et al. (2016) [20] . In this new numerical scheme, we propose an appropriate treatment of the rheological terms through a hydrostatic reconstruction which allows this scheme to be well-balanced and therefore to deal with dry areas. Based on academic tests, we first evaluate the influence of the width of the channel on the normal profiles of the downslope velocity thanks to the multilayer approach that is intrinsically able to describe changes from Bagnold to S-shaped (and vice versa) velocity profiles. We also check the well-balanced property of the proposed numerical scheme. We show that approximating side walls friction using single-layer models may lead to strong errors. Secondly, we compare the numerical results with experimental data on granular collapses. We show that the proposed scheme allows us to qualitatively reproduce the deposit in the case of a rigid bed (i.e. dry area) and that the error made by replacing the dry area by a small layer of material may be large if this layer is not thin enough. The proposed model is also able to reproduce the time evolution of the free surface and of the flow/no-flow interface. In addition, it reproduces the effect of erosion for granular flows over initially static material lying on the bed. This is possible when using a variable friction coefficient μ ( I ) but not with a constant friction coefficient. [ABSTRACT FROM AUTHOR]

Questions Multiple potential natural vegetation ( MPNV) is a framework for the probabilistic and multilayer representation of potential vegetation in an area. How can an MPNV model be implemented and synthesized for the full range of vegetation types across a large spatial domain such as a country? What additional ecological and practical information can be gained compared to traditional potential natural vegetation ( PNV) estimates? Location Hungary. Methods MPNV was estimated by modelling the occurrence probabilities of individual vegetation types using gradient boosting models ( GBM). Vegetation data from the Hungarian Actual Habitat Database ( MÉTA) and information on the abiotic background (climatic data, soil characteristics, hydrology) were used as inputs to the models. To facilitate MPNV interpretation a new technique for model synthesis (re-scaling) enabling comprehensive visual presentation (synthetic maps) was developed which allows for a comparative view of the potential distribution of individual vegetation types. Results The main result of MPNV modelling is a series of raw and re-scaled probability maps of individual vegetation types for Hungary. Raw probabilities best suit within-type analyses, while re-scaled estimations can also be compared across vegetation types. The latter create a synthetic overview of a location's PNV as a ranked list of vegetation types, and make the comparison of actual and potential landscape composition possible. For example, a representation of forest vs grasslands in MPNV revealed a high level of overlap of the potential range of the two formations in Hungary. Conclusion The MPNV approach allows viewing the potential vegetation composition of locations in far more detail than the PNV approach. Re-scaling the probabilities estimated by the models allows easy access to the results by making potential presence of vegetation types with different data structure comparable for queries and synthetic maps. The wide range of applications identified for MPNV (conservation and restoration prioritization, landscape evaluation) suggests that the PNV concept with the extension towards vegetation distributions is useful both for research and application. [ABSTRACT FROM AUTHOR]

The problem of the propagation of acoustic wave disturbance initiated by a boundary condition is used to simulate a disturbance of atmospheric gas caused by a rise of water masses. The boundary condition is a function of a dynamic variable that is defined on the border of the problem domain. In this work, it is chosen in such a way that its parameters and form correspond to disturbances in the gas layer produced by a tsunami wave at the air−water interface. The atmosphere is approximately described as a 1D multilayer gas media with an exponential structure of density in each layer. The boundary conditions are set at the interface between water−air and gas layers. These determine the direction of propagation and the ratio of dynamic variables characterizing an acoustic wave. The relationship between such variables (pressure, density, and velocity) is derived by means of projection operators on the subspaces of the z-evolution operator for each layer. The universal formulas for the perturbation of atmospheric variables in an arbitrary layer are obtained in frequency and time domains. As a result, explicit expressions are derived that determine the spectral composition and vertical velocity, by the stationary phase method, of the acoustic disturbance of the atmosphere at an arbitrary height, including the heights of the ionosphere. In return, this can be used to calculate the ionospheric effect. The effect is described by the explicit formula for electron density evolution, which is the solution of the diffusion equation. This forms a quick algorithm for early diagnostics of tsunami waves.

Numerical integration of the instantaneous net photosynthetic rate (An) is a common method for calculating the long-term CO2 uptake of trees, and accurate dynamic simulation of the crown An has been receiving substantial attention. Tree characteristics are challenging to assess given their aerodynamically coarse crown properties, spatiotemporal variation in leaf functional traits and microenvironments. Therefore, the variables associated with the dynamic variations in the crown An must be identified. The relationships of leaf temperature (Tleaf), the vapor pressure deficit (VPD), leaf mass per area (LMA) and the relative depth into the crown (RDINC) with the parameters of the photosynthetic light-response (PLR) model of Larix olgensis Henry were analyzed. The LMA, RDINC and VPD were highly correlated with the maximum net photosynthetic rate (Amax). The VPD was the key variable that mainly determined the variation in the apparent quantum yield (AQY). Tleaf exhibited a significant exponential correlation with the dark respiration rate (Rd). According to the above correlations, the crown PLR model of L. olgensis trees was constructed by linking VPD, LMA and RDINC to the original PLR equation. The model performed well, with a high coefficient of determination (R2) value (0.883) and low root mean square error (RMSE) value (1.440 μmol m−2 s−1). The extinction coefficient (k) of different pseudowhorls within a crown was calculated by the Beer–Lambert equation based on the observed photosynthetically active radiation (PAR) distribution. The results showed that k was not a constant value but varied with the RDINC, solar elevation angle (ψ) and cumulative leaf area of the whole crown (CLA). Thus, we constructed a k model by reparameterizing the power function of RDINC with the ψ and CLA, and the PAR distribution within a crown was therefore well estimated (R2 = 0.698 and RMSE = 174.4 μmol m−2 s−1). Dynamic simulation of the crown An for L. olgensis trees was achieved by combining the crown PLR model and dynamic PAR distribution model. Although the models showed some weakened physiological biochemical processes during photosynthesis, they enabled the estimation of long-term CO2 uptake for an L. olgensis plantation, and the results could be easily fitted to gas-exchange measurements.

In the large caldera of Mt. Aso, Japan, artificial grasslands were converted into forests of different species due to the decline of the livestock industry in this region. These changes in species composition are thought to have changed not only the transpiration rates ( E), but also the responses in E to variations in environmental conditions. For three introduced forest types, we monitored E using sap flux sensors and computed E with a multilayer model parameterized by independently obtained leaf-scale ecophysiological traits. Modeled E replicated the time series of measured E reasonably well, but did not reproduce a decrease in E lasting 20 days after a short rainless period in conifer plantation. Mean leaf-scale stomatal conductance of two deciduous broadleaved tree species was as low as that of trees under dry conditions in other studies, possibly an adaptation for the avoidance of excessive E during rainless periods. These results suggest that land use change influenced E and its response to the rainfall patterns of the region and that drought plays an important role in influencing species-specific E characteristics in this rainy region. The multilayer model in combination with sap flux measurements was found to be a useful tool not only for the extrapolation of E, but also for the detection of the unexpected events, as long as the measured parameter values capture the species-specific seasonality in leaf ecophysiological traits. [ABSTRACT FROM AUTHOR]

A method is presented for changing over from a single-layer shallow-water model to a multilayer model with hydrostatic pressure profile and, then, to a multilayer model with nonhydrostatic pressure profile. The method does not require complex procedures for solving the discrete Poisson's equation and features high computation efficiency. The results of validating the algorithm against experimental data critical for the numerical dissipation of the numerical scheme are presented. Examples are considered. [ABSTRACT FROM AUTHOR]

Throughout the development of the hydropower special attention was paid to the formation of a theoretical framework and methods of parameters and operating modes of powerhouses study. Under current design standards mathematical modeling of powerhouse is performed in two-dimensional for the axisymmetric problem. Up to now this method of simulation in Russia is the determining, although it has long lagged behind the capabilities of modern universal software of finite element analysis.The article presents analysis of the mathematical modeling methods for powerhouses of high-head hydroelectric power plants. Statement of the problem of three-dimensional modeling of the object – powerhouse is given. The procedure for multilayer three-dimensional modeling of water-conveyance conduits is presented. Outlined are the advantages of detailed numerical models of powerhouses in the context of their reliability verification.

Significance: The sensitivity to extracerebral tissues is a well-known confounder of diffuse optics. Two-layer (2L) head models can separate cerebral signals from extracerebral artifacts, but they also carry the risk of crosstalk between fitting parameters., Aim: We aim to implement a constrained 2L head model for hybrid diffuse correlation spectroscopy (DCS) and frequency-domain diffuse optical spectroscopy (FD-DOS) data and to characterize errors in cerebral blood flow and tissue absorption with the proposed model., Approach: The algorithm uses the analytical solution of a 2L cylinder and an a priori extracerebral layer thickness to fit multidistance FD-DOS (0.8 to 4 cm) and DCS (0.8 and 2.5 cm) data, assuming homogeneous tissue reduced scattering. We characterized the algorithm's accuracy for simulated data with noise generated using a 2L slab and realistic adult head geometries and for in vitro phantom data., Results: Our algorithm recovered the cerebral flow index with 6.3 [2.8, 13.2]% and 34 [30, 42]% (median absolute percent error [interquartile range]) for slab and head geometries, respectively. Corresponding errors in the cerebral absorption coefficient were 5.0 [3.0, 7.9]% and 4.6 [2.4, 7.2]% for the slab and head geometries and 8 [5, 12]% for our phantom experiment. Our results were minimally sensitive to second-layer scattering changes and were robust to cross-talk between fitting parameters., Conclusions: In adults, the constrained 2L algorithm promises to improve FD-DOS/DCS accuracy compared with the conventional semi-infinite approach., (© 2023 The Authors.)