Layered Model Research Articles

Hybrid mesh for magnetotelluric forward modeling based on the finite element method

Unstructured tetrahedral grids have been applied in magnetotelluric (MT) forward modeling using the finite element (FE) method because of their adaptability to complex anomalies. However, high-quality results require an extreme refinement of the near-surface area, which leads to excessive meshes and an increased degree of freedom (DoF) of the governing equation of the finite element system. To reduce the computational cost, we have developed a hybrid mesh based on triangular prisms and tetrahedrons. The required elements in the near-surface area are reduced because the quality of the triangular prism is not limited by the element aspect ratio. The deep area is discretized by tetrahedral elements to ensure the flexibility of the unstructured grids. The superiority of this hybrid mesh has been tested on a layered model, the DTM1 model and terrain relief models. The results show that the modeling efficiency has been improved, especially for high-frequency data. The accuracy of the modeling using the hybrid mesh is significantly higher than that of the tetrahedral mesh with a similar DoF. Usage of the hybrid mesh can be easily adapted to complex geoelectric models with strong terrain fluctuations, which requires less computational cost than using conventional unstructured elements.

Network-Structured BST/MBO Composites Made from Core-Shell-Structured Granulates.

A finite element method (FEM)-based simulation approach to predict the tunability in composite materials was developed and tested with analytical data. These tests showed good prediction capabilities of the simulation for the test data. The simulation model was then used to predict the tunability of a network-structured composite, where the dielectric phase formed clusters in a paraelectric network. This was achieved by simulating a reciprocal core-shell unit cell of said network. The simulation showed a high tunability for this network model, exceeding the tunability of the analytically evaluated layered, columnar, and particulate model. The simulation results were experimentally verified with a Ba0.6Sr0.4TiO3/Mg3B2O6 (BST/MBO) composite, where core-shell granulates were made with a two-step granulation process. These structured samples showed higher tunability and dielectric loss than the unstructured samples made for comparison. Overall, the structured samples showed higher tunability to loss ratios, indicating their potential for use in tunable radio frequency applications, since they may combine high performance with little energy loss.

Unified framework based parallel FEM code for simulating marine seismoacoustic scattering

The simulation of seismic wave propagation in marine areas, which belongs to seismoacoustic scattering problem, is complicated due to the fluid-solid interaction between seawater and seabed, especially when the seabed is saturated with fluid. Meanwhile, huge computation resources are required for large-scale marine seismic wave simulation. In the paper, an efficient parallel simulation code is developed to solve the near-field seismoacoustic scattering problem. The method and technologies used in this code includes: 1) Unified framework for acoustic-solid-poroelastic interaction analysis, in which seawater and dry bedrock are considered as generalized saturated porous media with porosity equals to one and zero, respectively, and the coupling between seawater, saturated seabed and dry bedrock can be analyzed in the unified framework of generalized saturated porous media and avoid interaction between solvers of different differential equation; 2) Element-by-element strategy and voxel finite-element method (VFEM), with these strategies, it only needs to calculate several classes of element matrix and avoid assembling and storing the global system matrices, which significantly reduces the amount of memory required; 3) Domain-partitioning procedure and parallel computation technology, it performs 3D and 2D model partitioning for the 3D and 2D codes respectively, sets up the velocity structure model for the partitioned domain on each CPU or CPU core, and calculates the seismic wave propagation in the domain using Message Passing Interface data communication at each time step; 4) Local transmitting boundary condition, we adopt multi-transmitting formula, which is independent of specific wave equations, to minimize reflections from the boundaries of the computational model. A horizontal layered model with the plane P-wave incident vertically from bottom is used to demonstrate the computational efficiency and accuracy of our code. Then, the code is used to simulate the wave propagation in Tokyo Bay. All codes were written following to the standards of Fortran 95.

A simplified model for acoustic focalization in environments with seabed uncertainties

Introduction: Parameter mismatch poses a challenge to source localization in cases involving environments with seabed uncertainties. By including environmental parameters in the search space, focalization can be used to estimate the location of the source using environmental information that is limited a priori. Methods: To reduce the number of parameters, a simplified seabed model is proposed here for such focalization. Only two geoacoustic parameters—the amplitude F and phase cF of reflection—are used to describe the seabed. Focalization is generally tested using genetic algorithms for the colored noise case (COLNOISE) benchmark problem. Results: The proposed simplified model can obtain the location of the source more easily than a layered model. Due to its advantage in terms of parameter sensitivity and inter-coupling, the simplified model can ensure the robustness of the results of inversion. The proposed method was tested on a broadband signal in the Asian Seas International Acoustics Experiment (ASIAEX2001), where both the location and the geoacoustic parameters were easily inverted. Discussion: The simplified model provides a sufficiently high acoustic resolution for focalization, and its reduction of the geoacoustic parameters helpes solve the problem of inversion.

Seismic response analysis of slope sites exposed to obliquely incident P waves

This study proposes a seismic input method for layered slope sites exposed to obliquely-incident seismic waves which transforms the waves into equivalent nodal forces that act on the truncated boundary of a finite element model. The equivalent nodal forces at the left and right boundaries are obtained by combining the free field response of a one-dimensional layered model with a viscoelastic boundary. The equivalent nodal forces at the bottom boundary are obtained by combining the incident wave field with the viscoelastic boundary. This proposed seismic input method for slope sites exposed to obliquely incident seismic waves is implemented with the aid of MATLAB software; it is applied to the seismic response analysis of slope sites in the commercial finite element ABAQUS software. The calculation results are compared with the reference solutions obtained by using the extended model to verify the correctness of the established seismic input method. The proposed seismic input method is then employed to investigate the influencing factors of the seismic response of layered slope sites exposed to oblique incidence P waves. The results show that the angle of incidence, location of the interface between soft and hard rocks, and impedance ratio have significant effects on the seismic landslide.

Study on the transmission characteristics and band structure of 2D and 3D plasma photonic crystals.

In this paper, 2D and 3D plasma photonic crystals (PPCs) were constructed using argon-mercury glow discharge tubes. Firstly, the collisional radiative model (CRM) was established for the glow discharge process, the average electron density of plasma in the discharge tube was calculated, and the average electron density was experimentally diagnosed by microwave diagnosis. By comparing the calculated and experimental results, the variation range of the average electron density in the tube was given. Secondly, according to the analysis results of the average electron density, a layered model of the discharge tube was established, and the transmission characteristics of the 2D and 3D PPC were calculated and measured. Finally, to analyze the cause of the photonic bandgap (PBG) in the transmission spectra, the band structures of 2D and 3D PPC were calculated using the plane wave expansion (PWE) method and the symplectic finite difference time domain (SFDTD) method. The results show that: the layered model is a valid discharge tube model; for 2D PPC, the formation of Localized Surface Plasmons (LSPs) under TE polarization is the main cause of PBG generation, and the number of LSP bandgap increases as the electron density rises; The existence of cutoff bandgap under TM polarization is due to the cutoff effect of plasma on electromagnetic waves. For 3D PPC, both cutoff bandgap and LSP bandgap exist in the transmission spectra, and the cutoff bandgap is shifted to lower frequencies due to the presence of Fano mode. The results of the study can be used as a reference for communication, microwave device fabrication, and military target stealth.

One–dimensional magnetotelluric inversion by modified differential evolution algorithm

Traditional methods of solving geophysical inverse problems often used an initial structural model and an iterative process to find solutions. During each iteration, the model was linearized and updated, then the error between the model's response and the observed data were calculated and minimized. The inverse results solved by this method were often strongly dependent on the initial model choice, and the minimum of the objective function found could be the local value but not the global minimum. Global search methods such as genetic algorithm (GA) overcame these limitations of traditional solutions. This paper presented the application of modified differential evolution (MDE) algorithm which was developed from the genetic algorithm, to one-dimension (1D) magnetotelluric inversion. The algorithm had been used to invert two 3-layer geoelectrical models. The results showed that when using a 3-layer model for inversion, the obtained parameters of the subsurface almost coincided with those of the theoretical models. In the case the number of layers used for inversion had more than three layers (four layers and five layers), the obtained results showed that there was still a good agreement between the inverted structure and the theoretical model. Therefore, the algorithm was applied to one-dimensional (1D) inversion for data of one magnetotelluric station measured at Cu Chi district, Ho Chi Minh city. The results showed that the subsurface structure down to a depth of 16 km consisted of 3 layers: the top layer had a resistivity of 119 Ω.m with a thickness of about 760 m, the middle resistive layer with a resistivity of 4353 Ω.m with about 10 km thickness, and the lower half-space with a relatively low resistivity of 41.4 Ω.m. This result was consistent with the geoelectric structure information obtained from other magnetotelluric studies carried out in the studied area, demonstrating the practical applicability of the improved differential evolution algorithm.

Research on Small-Loop Transient Electromagnetic Method Forward and Nonlinear Optimization Inversion Method

The small-loop transient electromagnetic (TEM) method has great application prospects in shallow surface geophysical exploration. However, the theoretical research on the forward and inversion of this method is obviously lagging behind, which seriously affects the application effect in practical engineering. For the oscillation problem of the small-loop TEM response calculated by using the forward theory of the conventional TEM methods, the dipole integral superposition method was proposed to solve the problem in this article. The transmitter source is divided into an infinite number of electric dipoles, and the calculation expressions of the electromagnetic field components satisfied by the electric dipoles are deduced, and the forward calculation problem of the layered model of the small-loop TEM method is solved. For the small-loop TEM method inversion problem, the simulated annealing (SA) method was presented for inversion calculation in this article. First, the influence of the selection of the initial temperature on the inversion result of the SA algorithm was analyzed. Then, we demonstrate the algorithm’s flexibility by choosing different initial models and search ranges and concluded that the different initial models and search ranges do not affect the inversion results of the SA algorithm. Next, the typical layered models were established, and the SA algorithm was used to carry out calculations. The research results show that the SA algorithm is an excellent global optimization algorithm, which can easily jump out of the local minima and converge to the global minima. Finally, we processed the measured data through inversion calculations and compared it with the results of the other three methods to verify the effectiveness and accuracy of the SA algorithm for small-loop TEM data processing. The research content solves the theoretical problem of the small-loop TEM method forward and inversion, promotes the development of the small-loop TEM method technology, and objectively and effectively solves practical engineering application problems.

HYBRID PARTICLE SWARM OPTIMIZATION AND GREY WOLF OPTIMIZER ALGORITHM FOR CONTROLLED SOURCE AUDIO-FREQUENCY MAGNETOTELLURICS (CSAMT) ONE-DIMENSIONAL INVERSION MODELLING

The Controlled Source Audio-frequency Magnetotellurics (CSAMT) is a geophysical method utilizing artificial electromagnetic signal source to estimate subsurface resistivity structures. One-dimensional (1D) inversion modelling of CSAMT data is non-linear and the solution can be estimated by using global optimization algorithms. Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO) are well-known population-based algorithms having relatively simple mathematical formulation and implementation. Hybridization of PSO and GWO algorithms (called hybrid PSO-GWO) can improve the convergence capability to the global solution. This study applied the hybrid PSO-GWO algorithm for 1D CSAMT inversion modelling. Tests were conducted with synthetic CSAMT data associated with 3-layer, 4-layer and 5-layer earth models to determine the performance of the algorithm. The results show that the hybrid PSO-GWO algorithm has a good performance in obtaining the minimum misfit compared to the original PSO and GWO algorithms. The hybrid PSO-GWO algorithm was also applied to invert CSAMT field data for gold mineralization exploration in the Cibaliung area, Banten Province, Indonesia. The algorithm was able to reconstruct the resistivity model very well which is confirmed by the results from inversion of the data using standard 2D MT inversion software. The model also agrees well with the geological information of the study area.

Experimental and modeling analysis on thermoelectric heat recovery to maximize the performance of next-generation diesel engines dedicated for future electrified powertrains

• A fast predictive thermoelectric generator (TEG) model is developed and validated. • A 4-cylinder 2.2 L diesel engine model with TEG is developed and calibrated. • The effective power of 1.1 kW is generated from a 3-layer TEG (1.5 × A4 size). • Brake thermal efficiency of 49.9 % is demonstrated in the next-generation engine. • The TEG system improves the engine brake thermal efficiency by 1.1 %. Thermoelectric generators (TEG) can recover significant energy loss from exhaust heat and improve brake thermal efficiency (BTE) of internal combustion engine (ICE) vehicles. However, its utilization is restricted due to increased pump losses when it is integrated with ICEs. This work uses a model-based design approach to maximize the performances of a next-generation, production-intent 2.2 L diesel engine dedicated to future electrified powertrains via TEG heat recovery. To take full advantage of TEG in the engine, a thermoelectric module (TEM) arrangement in TEG must be optimized, accounting for a tradeoff between increased pump loss and TEG effective power. Firstly, a high-fidelity 1D TEG model is developed, and a novel model calibration method is proposed by using simplified user-defined functions of heat transfer and flow friction factors. Measured thermal performances of the TEG heat exchanger are reproduced under various fin pitches, Reynolds numbers, and inlet gas conditions. The TEG model is integrated with the well-calibrated engine to maximize its BTE and power. Under the most efficient condition (peak BTE at 2250 RPM, 60% load), BTE = 48.7% and 52.1 kW brake power are obtained under the baseline case without TEG. An optimal 9 × 10 TEM arrangement generates a 1.1 kW effective power from the 3-layer TEG model (1.5 × A4 paper size, 150 mm height, 36 kg weight). Finally, a 1.1% BTE improvement is obtained without power loss in the next-generation, highly efficient, hybridized diesel engine.

Radioactive Direction of Arrival Estimation Using Neural Networks Approach

In this paper, we present a comprehensive investigation into improving Direction of Arrival (DOA) estimation for gamma-emitting isotopes using deep neural networks. The direction of arrival estimation is most valuable for Home Land Security (HLS) applications or increased safety in Decontamination and Decommissioning (D&D). Traditional methods, such as beamforming (BF), have limitations in accuracy and sensitivity to noise and background variations. In recent years, data-driven approaches utilizing deep neural networks, including Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) models, have shown promise in enhancing DOA estimation. By considering the full energy spectrum and augmenting recorded data, our neural network models outperform traditional BF methods and exhibit greater resilience in diverse background scenarios. The 2-layer CNN model, in particular, achieves up to 40% improvement in estimation accuracy. Our research provides a reliable and data-driven approach for precise DOA estimation with potential applications in nuclear security and safety in D&D.

Time-Weighted Cumulative LSTM Method Using Log Data for Predicting Credit Card Customer Turnover

One of the most important challenges for credit card companies is to retain customers. To achieve this, they predict whether customers will use credit cards and respond preemptively through marketing. Improper prediction leads to an increase in marketing costs; therefore, improving the performance of the prediction model is an important challenge for credit card companies. Therefore, credit card companies are working toward increasing the predictive power of the model, but the data used for learning are limited to formal data, such as card payment data; the log history stored on the application is not used. Prediction models using sequence data, such as log history, are being studied. However, no studies so far have appropriately utilized card payment data, log history, and information on the timing of the elements constituting the sequence. In this paper, we propose a method for predicting credit card turnover using application log and credit card payment data. The method embeds log data and weights each log using a term-weighting function. In addition, the time difference between the day customers visit the app and the last day of the month in which they leave is calculated. The weight value is higher when the timespan is shorter. The weighted log data were trained with a 2-layer LSTM model and its output layer was combined with the output layer trained with the card payment data for customer turnover prediction. It was verified that the model presented in this paper had a higher performance than the model using only card payment data and the model using only a time-weighted log sequence.

Optimal Inversion Method for Composite Layered Soil Model Considering Outlier Dispersion

Optimal Inversion Method for Composite Layered Soil Model Considering Outlier Dispersion

Study Evaluates Surfactant EOR From Tight Carbonates

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 209418, “Surfactant Enhanced Oil Recovery From Tight Carbonates: Core-Scale Experiments to Reservoir-Scale Modeling,” by Yue Shi, SPE, and Kishore Mohanty, SPE, The University of Texas at Austin. The paper has not been peer reviewed. _ Most carbonate reservoirs are oil-wet/mixed-wet and heterogeneous at multiple scales. The majority of the injected water flows through the high-permeability regions and fractures and bypasses the oil in the matrix because of high negative capillary pressure (Pc). To enhance oil recovery from such reservoirs, the sign of the Pc should be changed by wettability alteration (WA) or the Pc should be reduced by lowering interfacial tension (IFT). In the complete paper, surfactants that can either alter wettability or develop ultralow IFT were identified through laboratory measurements for the target carbonate reservoir. Introduction Contact-angle, IFT, phase-behavior, and imbibition tests were first performed, and surfactants that can either alter wettability or develop ultralow IFT were identified. Then, a laboratory-scale imbibition model was built with commercial reservoir simulation software. A sensitivity study was performed to evaluate the effects of residual oil saturation (Sor), alteration of Pc and relative permeability (Kr), IFT, and matrix scale on oil recovery by surfactant. Next, the laboratory-scale imbibition model was used to history match the experimental data and parameters were tuned for reservoir-scale simulation. Finally, a 3D layered field-scale model was developed to study the performance of the selected surfactants in injection/soak/production (ISP) tests. Materials Eight anionic surfactants (An 1 through An 8) and two quaternary ammonium cationic surfactants (Cat 1 and 2) were used. Silurian dolomite (SD) outcrop cores were used in this study. Fluid samples were obtained from a West Texas dolomite-rich reservoir. The oil has a density of 0.84 g/mL at 25°C and a viscosity of 7.46 cp at reservoir temperature (35°C). It has an acid number of 0.25 mg KOH/g and a base number of 1.0 mg KOH/g. The reservoir has been waterflooded for years, and total dissolved solids of brine has decreased from 112,668 to 40,393 ppm for recent produced water (PW). The authors detail the methodology for aqueous-stability, contact-angle-measurement, IFT-measurement, phase-behavior, and spontaneous-imbibition tests in the complete paper.

Estimation of seismic resistance of multi-story buildings in the framework of the bimoment theory using the plate model

This article is devoted to the development of a continual layered plate model of a multi-story building to dynamically assess the seismic resistance of multi-story buildings in a spatial statement. Seismic vibrations of a building are modeled as a motion of a thick anisotropic cantilevered plate, the deformation of which is described on the basis of the bimoment theory of thick plates.

Comprehensive Evaluation of Pavement Waterproofing Layer Materials for Bridge and Tunnel Projects

In order to achieve the preferential selection of pavement waterproofing layer materials, so that the waterproofing layer material selection is more scientific and objective, eliminating the impact of subjective factors, this paper uses hierarchical analysis to build a hierarchical evaluation model of pavement waterproofing layer. Based on the literature review method, a two-tier evaluation index of the layered evaluation model of pavement waterproofing layer materials was constructed, mainly three first-tier indexes of performance assessment, service life assessment, and cost assessment, under which the second-tier indexes of waterproofing performance, durability, weather resistance, impermeability, crack resistance, thermal stability, aging resistance, low temperature crack resistance, fatigue resistance, material cost, construction cost, and maintenance cost were established. And through the hierarchical analysis method of calculation, test the consistency by deriving the weight of each indicator, where the most important first layer of indicators for performance, the weight of 0.5390, the second layer of indicators is more important for waterproof performance (0.5303), thermal stability (0.3550), low-temperature crack resistance (0.3550), material cost (0.6333). The study provides a scientific and objective evaluation model for the preferential selection of pavement waterproofing layer materials.

Modified Levenberg–Marquardt Inversion for High-Resolution Resistivity Distribution Reconstruction of Multilayered Formation

In this article, a modified Levenberg–Marquardt inversion method is proposed for high-resolution reconstruction of resistivity distribution in multilayered formation. In forward modeling, the finite-element method (FEM) is used to obtain Jacobian matrix. In inversion process, several strategies are proposed to improve inversion performance. First, the logging data are interpolated to refine the layered formation model and improve the spatial resolution in resistivity inversion. Second, the scale of the Jacobian matrix is adjusted dynamically within a sliding window according to the sensitivity distribution obtained from the logging data to reduce the computational complexity. Third, the constrained optimization approach is applied to ensure the stability and accuracy of resistivity distribution inversion. Numerical simulation and in-field experiments were carried out to validate the performance of the proposed method. In the experiments, the proposed method was applied to the real logging data obtained in an oil field, and the accuracy of the inversion is verified using a forward modeling-based evaluation method. Results show that the proposed method has a better boundary discrimination ability and can provide a higher spatial resolution and more precise resistivity distribution of multilayered formations than the traditional apparent resistivity method.

Riemannian geometric modeling of underwater acoustic ray propagation ·application——Riemannian geometric model of convergence zone in deep ocean remote sound propagation

Convergence-zone (CZ) sound propagation is one of the most important hydro-acoustic phenomena in the deep ocean, which allows the acoustic signals with high intensity and low distortion to realize the long-range transmission. Accurate prediction and identification of CZ is of great significance in implementing remote detection or communication, but there is still no standard definition in the sense of mathematical physics for convergence zone. Especially for the issue of systematic error of computation introduced by the earth curvature, there is no exact propagation model. The curvature-correction methods always lead to the imprecision of the ray phase. In previous research work, we realized that the Riemannian geometric meaning of the caustics phenomena caused by ray convergence is that the caustic points are equivalent to the conjugate points, which form on geodesics with positive section curvature. In this work, we present a spherical layered acoustic ray propagation model for CZ based on the Riemannian geometric theory. With direct computation in the curved manifolds of the earth , a Riemannian geometric description of CZ is provided for the first time, on the basis of comprehensive analysis about its characteristics. And it shows that the mathematical expression of section curvature adds an additional item <inline-formula><tex-math id="M1">\begin{document}${{\hat c(l){{\hat c}^\prime }(l)}}/{l}$\end{document}</tex-math><alternatives><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="4-20221495_M1.jpg"/><graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="4-20221495_M1.png"/></alternatives></inline-formula> after considering the earth curvature, which reflects the influence of the earth curvature on the ray topology and CZ. By means of Jacobi field theory of Riemannian geometry, computational rule and method of the location and distance of CZ in deep water are proposed. Taking the typical Munk sound velocity profile for example, the new Riemannian geometric model of CZ is compared with the normal mode and curvature-correction method. Simulation and analysis show that the Riemannian geometric model of CZ given in this paper is a mathematical form naturally considering the earth curvature with theoretical accuracy, which lays more solid scientific foundations for the study of convergence zone. Moreover, we find that the location of CZ moves towards sound source when the earth curvature is considered, and the width of CZ near the sea surface first increases and then decreases with sound propagation proceeding. The maximum width is about 20 km and the minimum is about 4 km.

Optimizacija PMEDM sa više odgovora na Inkonel 718 koristeći hibridni T-GRA, TOPSIS i ANN model

Inconel 718 is one of the Nickel-based superalloys considered one of the most difficult-to-machine materials owing to its property to retain hardness at higher temperatures. This study examined the performance of Edcutor-based PMEDM machining on Inconel 718. Taguchi L9 OA has been used with current, Pulse-OFF time & Pulse-ON time as process parameters with a delivery side pressure of 6 bar for the Alumina mixed dielectric. Material removal rate (MRR), Tool wear rate (TWR), & surface roughness (SR) have been taken as output responses. The results have been investigated by MADM techniques, namely Taguchi-based Grey Relational Analysis (T-GRA) & TOPSIS analysis. Furthermore, the ranks obtained from T-GRA & TOPSIS have been validated by developing a single layered ANN model. Ranks predicted by the ANN model are the same for T-GRA and TOPSIS and the R-values are 0.924 & 0.871, respectively. ANOVA has also been used to analyze parameter effects on output responses.

ASL Recognition by the Layered Learning Model Using Clustered Groups

American Sign Language (ASL) images can be used as a communication tool by determining numbers and letters using the shape of the fingers. Particularly, ASL can have an key role in communication for hearing-impaired persons and conveying information to other persons, because sign language is their only channel of expression. Representative ASL recognition methods primarily adopt images, sensors, and pose-based recognition techniques, and employ various gestures together with hand-shapes. This study briefly reviews these attempts at ASL recognition and provides an improved ASL classification model that attempts to develop a deep learning method with meta-layers. In the proposed model, the collected ASL images were clustered based on similarities in shape, and clustered group classification was first performed, followed by reclassification within the group. The experiments were conducted with various groups using different learning layers to improve the accuracy of individual image recognition. After selecting the optimized group, we proposed a meta-layered learning model with the highest recognition rate using a deep learning method of image processing. The proposed model exhibited an improved performance compared with the general classification model.