Layer Model Research Articles

MATHEMATICAL MODELING OF THE PROCESS OF SEPARATION OF MIXTURES BY LIQUID EXTRACTION

While designing liquid-phase extraction processes, one of the main conditions is to determine the kinetic characteristics of the exchange processes necessary to determine the flows and masses of the components. Existing mass transfer models describe mass transfer processes on a semi-empirical and empirical basis with a limited range of applications, simplifying the real picture in most cases. In this regard, the development of models that more widely describe the processes of liquid-phase extraction and allow their application is considered one of the important tasks. Based on the generalization of the Chilton-Colborne hydrodynamic analogy in gradient flows and further development of the Landau-Levich boundary layer model, a mathematical model has been developed to determine the mass transfer coefficients in the extraction process in continuous and dispersed phases using minimal experimental data obtained at the stage of hydrodynamic studies

Effect of Dielectric Properties of Cochlea on Electrode Insertion Guidance Based on Impedance Variation

The cochlear neuromodulator provides substantial auditory perception to those with impaired hearing. The accurate insertion of electrodes into the cochlea is an important factor, as misplaced may lead to further damage. The impedance measurement may be used as a marker of the electrode insertion guidance. It is feasible to investigate the impact of the dielectric properties of the cochlea tissue layers on the electrode insertion guidance using sophisticated bio-computational methods that are impractical or impossible to perform in cochlear implant (CI) patients. Although previous modeling approaches of the cochlea argued that the capacitive impact of the tissue layer can be neglected using the quasi-static (QS) approximation method, it is widely accepted that tissue acts as a frequency filter. Thus, the QS method may not always be appropriate due to short-duration pulses. This study aimed to investigate the impact of the frequency-dependent dielectric properties of the cochlea tissue layers on the impedance variation by following a systematic approach. The volume conductor model of the cochlea layers was developed, the dielectric properties of each tissue layer were attained, and the cochlea neuromodulator settings were applied to obtain the results based on both QS and transient solution (TS) methods. The results based on the QS and TS methods were compared to define to what extent these parameters affect the outcome. It was suggested that the capacitive impact of the cochlea layers should be considered after a certain frequency level.

Simplification of solvation shell with water clusters in the simulation of electrochemical nitrogen reduction reaction.

Electrochemical methods for nitrogen reduction have received extensive attention due to the mild reaction conditions. In order to gain an insight into the mechanism of the electrochemical nitrogen reduction process, theoretical simulations are necessary. However, current simulation studies contain many imprecise approximations that may hinder the real recognition of the reaction process. Although solvation methods have recently been developed to provide efficient descriptions, their further applications are hindered by controversy over modeling of solvents and the enormous computational effort required. In this work, we simplify the solvation conditions by using water clusters and compare them with an accurate water layer model. The results demonstrate that the simplified water clusters can effectively capture protons, simulate the surface electric environment, and enable the calculation of the activation energy of the reaction. This method offers an affordable approach for simulating the surface potentials and solvents and provides a new reference for the theoretical study of the electrochemical nitrogen reduction reaction.

Modeling Borehole Resistivity Logs with Exponentially Graded Multilayered Soil Inversion for Electrical Engineering Applications

In this paper, we present the application of a special soil resistivity model, the Exponentially Graded Multilayered Soil model, to the interpretation of Borehole Resistivity Logging surveys. The model, which was recently introduced by the authors, offers an alternative to the interpretation provided by constant resistivity layer models. The model is applied to synthetic soil surveys as well as to a real survey that is not satisfactorily interpreted using conventional models. This model aids in the design and calculation of grounding systems in electrical engineering, providing an alternative to calculations performed by traditional layered models.

Two highly-ordered global structures observed in packed beds of balls inside vibrated cylinder: Experiment and modelling of layers

Two highly-ordered global structures observed in packed beds of balls inside vibrated cylinder: Experiment and modelling of layers

Lithospheric magnetic structure of cratonic regions in Central-Eastern China inferred from aeromagnetic anomalies: Insights into magnetization in the uppermost mantle

Most of the subcontinental lithospheric mantle (SCLM) beneath Proterozoic cratons consists of refertilized Archaean SCLM. Variations in SCLM composition and its physical properties significantly affect the stabilization and preservation of the ancient continents. In this paper, aeromagnetic data are analyzed to reveal the magnetic structure of the lithospheric mantle beneath two major Precambrian blocks in central-eastern China, i.e., the Upper Yangtze Block (UYB) and Ordos Block (OB). After being reduced to the pole, the Fourier power spectrum of the aeromagnetic anomalies is calculated to determine the depth to magnetic sources. Considering the lower spatial resolution of the power spectral analysis in dealing with the long-wavelength aeromagnetic anomalies, we applied the scale-normalized continuous wavelet transform (CWT) on the magnetic data to trace the magnetic sources, with special focus on deeper ones. Synthetical model of a magnetic layer and application to the profile data validate the effectiveness of this scale normalization scheme in improving the wavenumber/spatial resolution in the CWT scalogram.In order to present a detailed magnetic structure, we carried out 2.5D forward modeling work on the magnetic data of a 2280 km-long nearly N-S profile across the UYB and OB. Due to the inherent ambiguity in the modeling results, the CWT-based spectral analysis is successfully adopted to provide source depth constraints for the initial model. The constrained forward modeling results indicate strong inhomogeneities among main tectonic blocks of studied area, like humans have different fingerprints. The magnetization of OB is larger than that of UYB since its Archean to Paleoproterozoic metamorphic basement are widely exposed at the surface, while the Precambrian basement of UYB is mostly overlain by unmetamorphosed Sinian cover and weakly metamorphosed Neoproterozoic strata. The most interesting aspect is that deep-seated magnetic sources might reside in the uppermost mantle of UYB and OB, suggesting vertical layering in the SCLM in cold cratonic regions.

Characterization of optical depth for laser produced plasma extreme ultraviolet source

This study investigates the emission mechanism of laser-produced plasma extreme ultraviolet source (LPP-EUV). In the experiment, the EUV radiation is generated by a 1064 nm laser interacting with slab Sn target. The EUV emission is characterized by EUV energy monitors and an EUV spectrometer. The dependency of CE on laser intensity and plasma relative optical depth is explored by a plasma emission-absorption layer model. The dependency is confirmed by an optical interferometry measurement of plasma electron density for the first time. Our work provides a method for characterizing and optimizing the optical depth of laser driven EUV source.

Study on Shear Strength of Soil-Root Systems of Different Vegetation Types.

The root systems of vegetation significantly contribute to enhancing slope stability. The shear strength of soil-root systems is a crucial parameter for assessing slope stability. This study focuses on six types of vegetation in the Yellow River Basin of China (woodland: Populus przewalskii and Broussonetia papyrifera; shrubland: Periploca sepium and Ziziphus jujuba; grassland: Artemisia hedinii and Setaria viridis), employing in situ shear tests and the Wu-Waldron model (Wu model) to investigate the shear strength of soil-root systems. The results show that the shear stress-displacement curves for P. przewalskii, B. papyrifera, and Z. jujuba are higher and steeper, with clear inflection points. The tensile strength of the roots from the six vegetation types decreases as the root diameter increases. According to the Wu model, the additional root cohesion is ranked as follows: A. hedinii > B. papyrifera > P. przewalskii > Z. jujuba > P. sepium > S. viridis. Based on the in situ shear tests, the shear strength increments are ranked as follows: Z. jujuba > B. papyrifera > P. przewalskii > A. hedinii > P. sepium > S. viridis. Overall, the additional root cohesion obtained by the Wu model in each soil layer is greater than the shear strength increment measured from the in situ shear tests. In the 0-30 cm soil layers, the soil-root systems of Z. jujuba, B. papyrifera, P. przewalskii, and A. hedinii exhibit a better shear strength, whereas P. sepium and S. viridis perform poorly. A principal component analysis reveals that the shear strength of the soil-root systems of different vegetation types is primarily influenced by the soil moisture content and root mass density. Z. jujuba, B. papyrifera, P. przewalskii, and A. hedinii are recommended for ecological restoration projects in the Yellow River Basin of China.

A Real-Time System Status Evaluation Method for Passive UHF RFID Robots in Dynamic Scenarios

In dynamic scenarios, the status of a Radio Frequency Identification (RFID) system fluctuates with environmental changes. The key to improving system efficiency lies in the real-time monitoring and evaluation of the system status, along with adaptive adjustments to the system parameters and read algorithms. This paper focuses on the status changes in RFID systems in dynamic scenarios, aiming to enhance system robustness and reading performance, ensuring high link quality, reasonable resource scheduling, and real-time status evaluation under varying conditions. This paper comprehensively considers the system parameter settings in dynamic scenarios, integrating the interaction model between readers and tags. The system’s real-time status is evaluated from both the physical layer and the Medium Access Control (MAC) layer perspectives. For the physical layer, a link quality evaluation model based on Uniform Manifold Approximation and Projection (UMAP) and K-Means clustering is proposed from the link quality. For the MAC layer, a multi-criteria decision-making evaluation model based on combined weighting and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is proposed, which comprehensively considers both subjective and objective factors, utilizing the TOPSIS algorithm for an accurate evaluation of the MAC layer system status. For the RFID system, this paper proposes a real-time status evaluation model based on the Classification and Regression Tree (CART), which synthesizes the evaluation results of the physical layer and MAC layer. Finally, engineering tests and verification were conducted on the RFID robot system in mobile scenarios. The results showed that the clustering average silhouette coefficient of the physical layer link quality evaluation model based on K-Means was 0.70184, indicating a relatively good clustering effect. The system status evaluation model of the MAC layer, based on the combined weighting-TOPSIS method, demonstrated good flexibility and generalization. The real-time status evaluation model of the RFID system, based on CART, achieved a classification accuracy of 98.3%, with an algorithm runtime of 0.003 s. Compared with other algorithms, it had a higher classification accuracy and shorter runtime, making it well suited for the real-time evaluation of the RFID robot system’s status in dynamic scenarios.

Reconstruction and Modeling of Porous Transport Layers Based on X-ray Computed Tomography Imaging

Reconstruction and Modeling of Porous Transport Layers Based on X-ray Computed Tomography Imaging

Comparison of passive and semi-active piezoelectric transducer damping of cantilever oscillation

The aim of this work is the analysis of passive and semi-active damping methods on the model woven beam with a piezoelectric (PZ) layer. The mathematical model of the PZ layer on cantilever beam is derived. For modeling, real product parameters of PZ layer are used, and through simulation find the optimal values to dampen it. The resistive-inductance passive model, and State-Switch Damping SSD semi-active model are used in this work. The models are processed in the MATLAB Simulink environment and the results of the behavior of the models compared to each other. The program involving passive and semi-active systems, where analyze the behavior of the model for different parameters and the damping capabilities of individual methods are compared. The simulation results show the effectiveness of the semi-active system in comparison with the passive systems, also it shows the passive method is not so effective at low frequency as it in high frequency, and the semi-active method is not optimal for high frequency vibration.

Mechanisms and models of the turbulent boundary layers at transcritical conditions

Mechanisms and models of the turbulent boundary layers at transcritical conditions

Estimating Models and Evaluating their Efficiency under Multicollinearity in Multiple Linear Regression: A Comparative Study

Multicollinearity between independent variables occurs in multiple linear regression analysis characterized by high correlations, which complicates discerning individual variable effect, impacting model accuracy, stability, and interpretation of relationships. The research aims to diagnose the multicollinearity problem between explanatory variables in the linear regression model and identifying the variables causing this problem based on the variance inflation factor (VIF), then estimation and evaluate the performance of three alternative methods, which are Ridge regression, principal components analysis, and Feedforward Neural Networks (FFNN) models with one and two hidden layers and application of the models to compressive strength data for high-performance concrete. The results showed that Ridge regression and PCA effectively addressed multicollinearity problem, but the single hidden layer model FFNN showed superior predictive accuracy in estimating the compressive strength of high-performance concrete when comparing RMSE, MAE, and R2 values.

Pest and Disease Video Classification with Convolutional Neural Network and Transfer Learning

The important field crops of agriculture are affected due to attack of various pests and diseases which leads to reduction in crop production. Early classification and identification of pests and diseases in plant helps farmers to take mitigation steps. To address this issue with computer vision based techniques, convolutional neural network (CNN) based deep learning models were studied for classification of pests and diseases videos. Six different CNN models were developed. Two approaches namely from scratch learning and transfer learning were used. Data augmentation techniques such as reflection, scaling, rotation, and translation were also applied to prevent the network from overfitting. The classification accuracy of 99.19%, 99.08% and 98.80% was attained in VGG19, DENSENET201 and CNN 5 Layer model. The results demonstrated that CNN models with good architecture can classify pests and diseases with good performance.

A deep autoencoder for electric double layer capacitance prediction in electrochemical sensors

This study explores the application of a deep autoencoder neural network to accurately predict the electric double layer capacitance from real-world parameters in binary, asymmetric electrolytes under low concentration conditions. By utilizing a modest simulation-based dataset of just 250 samples, the deep autoencoder neural network model developed in this study effectively predicted the capacitance by learning the critical features and relationships of the electric double layer model and encoding this learned representation into a low-dimensional latent space. From the latent variables, the decoder block of the neural network learned to effectively recreate the high-dimensional input. To enhance the model's robustness, prevent overfitting, and better simulate real-world conditions, noise was incorporated into the training and test data. The model demonstrated strong performance across various conditions, such as ionic size, ionic charge, and surface potential, yielding satisfactory results on both clean and noisy test datasets. A key feature of this approach was the mapping of real-world electric double layer parameters to the latent variables of the model, allowing for direct input of physical parameters to predict the electric double layer capacitance. This research highlights the potential of machine learning techniques to expedite the design and analysis of complex multi-physics systems such as electrochemical sensors by reducing the dependence on extensive domain expertise throughout the design process.

Modeling of Melting Layer in Cross‐Platforms Radar Observation Operator ZJU‐AERO: Multi‐Stage Melting Particle Model, Scattering Computation, and Bulk Parameterization

AbstractThis study presents an implementation of a new melting layer model in the ZJU‐AERO radar observation operator (Accurate and Efficient Radar Operator designed by ZheJiang University). The proposed model utilizes a coated spheroid to represent melting snow and graupel. It consists of three stages–coating, soaking, and melting–to account for the dielectric and density effects of melting particles. The scattering properties of the melting particles are computed with the Invariant‐Imbedding T‐Matrix (IITM) method, and the results are tabulated as look‐up tables for the radar operator. Regarding the parameterization of bulk optical properties, a flux‐conservation scheme is employed to estimate the size distribution of melting particles. To demonstrate its flexibility and superiority, the single and bulk scattering properties of our multi‐stage melting model are compared against the traditional homogeneous model, which uses the effective medium approximation (EMA). The effectiveness of the multi‐stage melting model has also been assessed by mapping model states in the regional mesoscale model of the China Meteorology Administration (CMA‐MESO) to radar observations. In the microphysics package of CMA‐MESO, the melting process is not explicitly represented, and we assume that melting hydrometeors occur where solid and liquid phases overlap. When compared with observations, the present multi‐stage melting model successfully reproduces melting layer signatures, highlighting its potential for microphysic validation, quantitative precipitation estimations, and data assimilation studies.

Acoustic radiation characteristics of shark skin inspired surface modified plates

This paper aims to evaluate the acoustic radiation characteristics of thin plates featuring a layer of small-scale biomimetic shark skin type additive surface treatment. The shark skin dermal denticles are modelled as point masses arranged in a bi-directional pattern on both the upper and lower surfaces of the plate. The governing equations are obtained through a variational approach, incorporating the Dirac Delta function in the derivation of the proposed semi-analytical model for the shark skin layer. A semi-analytical method based on the Rayleigh–Ritz formulation is utilized to analyze the vibrations of these plates with surface modification. The sound radiation characteristics are then derived from the solution of the Rayleigh integral. A comprehensive investigation is performed on the influence of surface modification on different vibro-acoustic characteristics, using a continuous structural mode and power transfer matrix-based approach. Notable observations include a reduction in peak vibro-acoustic responses with dense denticle arrangements, especially at resonance, demonstrating a direct relationship with mass ratios, i.e., the ratio of denticle mass to plate mass. The study further reveals a shift of vibro-acoustic responses towards low frequencies with an increase in mass ratios. A thorough comparative study indicates that while additive surface modifications inspired by shark skin may weaken sound radiation characteristics at resonance frequencies, a reverse effect can be observed at intermittent operational frequencies.

The Effect of Ratio of Fiber Bundles in the Textile Composite Layer

Abstract The article shows how the orthotropic material properties of the textile composite layer change if the ratio of longitudinal and transversal fiber bundles in the textile is modified in the case of a composite reinforced with plain weave textile. I determine the material properties using model-cell and finite element simulation. The density of the longitudinal fiber bundles is the same in each of the five examined layer models. I change the ratio of the fiber bundles of the textile by varying the distance of the transversal roving’s in each model.

A novel pretreatment approach on titanium alloys for electroless nickel

To augment the wear resistance of the titanium alloy, electroless nickel (EN) is an effective method to strengthen the surface properties. However, the oxide layer on the surface of titanium alloy will inhibit the adhesion of EN. Meanwhile, the traditional pretreatment methods are cumbersome steps and time-consuming. To overcome these limitations, this study systematically explores a one-step pretreatment approach through amino tris(methylenephosphonic acid) (ATMPA) and HF, which is designed to improve the binding strength of EN. The results exhibit that the compact composite membrane with Ti-ATMPA and TiF3 are successfully prepared under pH 3.0, which has provided a pretreatment layer to replace the oxidation of titanium alloy during EN process, and the adhesion of EN coating (EN-3.0) based on the pretreatment layer reaches 22.46 MPa. The wear resistance of titanium alloy and EN plating system studied via a friction measurement, and the lowest wear rate exhibit in EN-3.0 plating (880.9 × 10-10mm3/Nm) that is lower than EN-traditional pretreatment with a decrease of 32 %. Moreover, the formation and catalytic model of medial layer are also discussed.

Study on construction technology and bearing mechanism of pressure cast-in-situ pile with spray-expanded frustum

The pressure cast-in-situ pile with spray-expanded frustum (PCPSF) is a new type of pile developed by the last author, which is composed of pile body, ribbed plate and expanded body with double-frustum. This paper presents the equipment used to produce the PCPSF and the spray-expansion extrusion vibration and pressure method used for construction of the PCPSF. The PCPSF model of cement soil transition layer around pile is built with finite element software. The accuracy of the numerical calculations is verified through a comparison with the results of static load tests conducted on PCPSF. Furthermore, the impact of the expanding ratio, expanded body location, and ribbed plate length on the response of the PCPSF is investigated. The results show that: (1) the ultimate bearing capacity (UBC) of PCPSF single pile is proportional to the diameter expanding ratio and the length of the ribbed plate; (2) the improvement of the bearing capacity of single cubic concrete of PCPSF decreases with the increase of expanding ratio; (3) the bearing capacity of expanded body can be activated ahead of time as it advances up in position, and there is a trend toward a steady increase in the combined bearing capacity of the expanded body and pile end; (4) as the expanded body moves up, the vertical stress of the soil below pile tip decreases, the rate of decay of additional stress is accelerated; (5) under the identical circumstances, the PCPSF's bearing capacity is 1.5 times greater than the traditional cast-in-place pile's, and the presence of cement soil transition layer contributes 15 % of the lateral resistance of the PCPSF.