One-layer Model Research Articles

Influence of the layered Moon and Earth’s orientation on lunar rotation

One of the most efficient ways to probe the lunar inner structure at present is through the study of its rotation. Range and range rate (Doppler) data between the Chang’E-3 lander and station on the Earth were collected from the beginning of the Chang’E-3 lunar mission in 2013. These observation data, taken together with the existing lunar laser ranging data, provide a new approach to extend research on the Earth-Moon system. The high precision of current observation data imposes exacting demands, making it necessary to include previously neglected factors. In this paper, motivated by progress of the Chinese lunar exploration project and to use its data in the near future, two lunar models: a one-layer model and a two-layer model with a fluid core, were applied to the rotational equations based on our implemented algorithm of the Moon’s motion. There was a difference of about 0.5″ in ϕ and ψ, but 0.2″ in θ between the two models. This result confirms that stratification of the inner structure of the Moon can be inferred from rotation data. We also added precise Earth rotation parameters in our model; the results show that this factor is negligible at present, due to the limited precision of the existing data. These results will help us understand the rotational process clearly and build a more realistic Earth-Moon model when we combine Lunar Laser Ranging data with high precision radio data to fit lunar motion in the near future.

Sparse deep nonnegative matrix factorization

Nonnegative matrix factorization is a powerful technique to realize dimension reduction and pattern recognition through single-layer data representation learning. Deep learning, however, with its carefully designed hierarchical structure, is able to combine hidden features to form more representative features for pattern recognition. In this paper, we proposed sparse deep nonnegative matrix factorization models to analyze complex data for more accurate classification and better feature interpretation. Such models are designed to learn localized features or generate more discriminative representations for samples in distinct classes by imposing $L_1$-norm penalty on the columns of certain factors. By extending one-layer model into multi-layer one with sparsity, we provided a hierarchical way to analyze big data and extract hidden features intuitively due to nonnegativity. We adopted the Nesterov's accelerated gradient algorithm to accelerate the computing process with the convergence rate of $O(1/k^2)$ after $k$ steps iteration. We also analyzed the computing complexity of our framework to demonstrate their efficiency. To improve the performance of dealing with linearly inseparable data, we also considered to incorporate popular nonlinear functions into this framework and explored their performance. We applied our models onto two benchmarking image datasets, demonstrating our models can achieve competitive or better classification performance and produce intuitive interpretations compared with the typical NMF and competing multi-layer models.

Quantitative Invulnerability Analysis of Artificial Spider-Web Topology Model Based on End-to-End Delay

This paper presents an artificial spider-web topology model inspired by the structure and invulnerability of a spider web. A hierarchical clustering routing rule is accordingly established using the vibration transmission features of the natural spider web as a reference. Furthermore, the end-to-end delay is applied as the quantitative indicator of invulnerability for analyzing the communication performance and characteristics of the artificial spider-web topology. The simulation tests of a one-layer and 3-layer artificial spider-web model are implemented to obtain the importance and destructive tolerance of network components based on OPNET, with the change of communication conditions and fault types. This paper can provide a practical analysis method for the invulnerability of the artificial spider-web topology and offer important implications for the construction and maintenance of wireless sensor networks based on the topology.

Improving the estimating accuracy of extinction coefficient of surface aerosol with a new layer-resolved model in China

The aerosol extinction coefficient was an important factor for air quality. To estimate the aerosol extinction levels, widely used pure statistical models are generally not based on aerosol vertical structures. In this study, we estimated large-scale aerosol extinction coefficients by developing a new layer-resolved model with explicit inference for aerosol vertical distribution. The CALIOP aerosol profile, MODIS AOD and reanalysis boundary layer height data are used. The layer-resolved model was formulated by developing an explicit, steady and straightforward relationship between aerosol within boundary layer and corresponding AOD values. The estimated surface extinction coefficient from this model was compared against the values derived from station visibility observations in China in 2016. The results revealed that our model had outperformed the traditional one-layer model and the simplified two-layer model. Specifically, the numbers of ground stations with an NME value < 0.4 are enhanced by a percentage > 100%, with the NME values significantly decreased from 46%, 48% to 36% and RMSE values from 0.27, 0.25 to 0.21 km−1. Our model is easy for operational implementation thanks to its clear structure and input, and also informative to understand aerosol vertical distributions. Furthermore, this work will also be beneficial to air quality modeling studies to improve accuracy estimating ground-level PM2.5 concentrations.

CHLOROPHYLL-A CONCENTRATION RETRIEVAL USING CONVOLUTIONAL NEURAL NETWORKS IN LAGUNA LAKE, PHILIPPINES

Abstract. Two existing chlorophyll-a (chl-a) concentration retrieval procedures, which are analytical and empirical, are hindered by the complexity in radiative transfer equation (RTE) and in statistical analyses, respectively. Another promising model in this direction is the use of artificial neural networks (ANN). Mostly, a pixel-to-pixel with one-layer ANN model is used; where in fact that the satellite instrumental errors and man-made objects in water bodies might affect the retrieval and should be taken into account. In this study, the mask-based neural structure, called convolutional neural networks (CNN) model containing both the target and neighborhood pixels, is proposed to reduce the influence of the aforementioned premises. The proposed model is an end-to-end multiple-layer model which integrates band expansion, feature extraction, and chl-a estimation into the structure, leading to an optimal chl-a concentration retrieval. In addition to that, a two-stage training is also proposed to solve the problem of insufficient in-situ samples which happens in most of the time. In the first stage, the proposed model is trained by using the chl-a concentration derived from the water product, provided by satellite agency, and is refined with the in-situ samples in the second stage. Eight Sentinel-3 images from different acquisition time and coincide in-situ measurements over Laguna Lake waters of Philippines were utilized to conduct the model training and testing. Based on quantitative accuracy assessment, the proposed method outperformed the existing dual- and triple- bands combinations in chl-a concentration retrieval.

A consistent reduction of the two-layer shallow-water equations to an accurate one-layer spreading model

The gravity-driven spreading of one fluid in contact with another fluid is of key importance to a range of topics. These phenomena are commonly described by the two-layer shallow-water equations (SWE). When one layer is significantly deeper than the other, it is common to approximate the system with the much simpler one-layer SWE. It has been assumed that this approximation is invalid near shocks, and one has applied additional front conditions to correct the shock speed. In this paper, we prove mathematically that an effective one-layer model can be derived from the two-layer equations that correctly capture the behavior of shocks and contact discontinuities without additional closure relations. The result shows that simplification to an effective one-layer model is justified mathematically and can be made without additional knowledge of the shock behavior. The shock speed in the proposed model is consistent with empirical models and identical to front conditions that have been found theoretically by von Kármán and Benjamin. This suggests that the breakdown of the SWE in the vicinity of shocks is less severe than previously thought. We further investigate the applicability of the SW framework to shocks by studying one-dimensional lock-exchange/-release. We derive expressions for the Froude number that are in good agreement with the widely employed expression by Benjamin. The equations are solved numerically to illustrate how quickly the proposed model converges to solutions of the full two-layer SWE. We also compare numerical results from the model with results from experiments and find good agreement.

Design of Wideband Implantable Antenna for Wireless Capsule Endoscope System

In order to adapt to the applications of the wireless capsule endoscope (WCE) system, a wideband implantable antenna is designed. We engrave some slots on both the radiator and the ground plane to miniaturize the size and expand the impedance bandwidth of the antenna. The capacitance loading technique is used to improve the impedance match. The influence of different organs such as the stomach, small intestine, and colon is discussed when the antenna is embedded in the WCE system. Compared to other implantable antennas with similar performance, impedance bandwidth, radiation pattern, and specific absorption rate in one-layer skin phantom model, this design has the best performance. Finally, experiments are carried out on a chicken breast slab to validate our design. Results are shown the proposed antenna available.

Investigations and modeling aspects of the influence of the high energy and high dose implantation on the optical and transport parameters of implanted layers in silicon

This paper presents results of investigations and modeling aspects of the influence of Ge+ high energy (100 keV) and high dose (1014 cm−2) implantation on the optical and recombination parameters of implanted layers in silicon. The nondestructive and contactless MFCA (Modulated Free Carrier Absorption) method was used as it is sensitive to changes of these parameters expected for implanted layers. Several model cases describing the MFCA spectrum as a function of the energy of photons of the excitation laser light are presented, compared and discussed. The simplified one-layer model and the full two-layer model of the MFCA signal have been analyzed and compared. The possibility and correctness of determination of the optical absorption coefficient spectra of the implanted layers with the use of the one-layer simplified model has been discussed.

Miniaturised and radiation efficient implantable antenna using reactive impedance surface for biotelemetry

This study presents the realisation of reactive impedance surface (RIS) in an implantable environment to design a compact wideband antenna for biotelemetry communication. The antenna is designed to operate at 2.45 GHz industrial, scientific and medical (ISM) band using a one-layer skin model. The proposed mushroom-based circular RIS successively improves the impedance matching, gain, and bandwidth of the antenna. The improvement in −10 dB impedance bandwidth and gain is observed by 270 MHz and 7 dB, respectively. The overall volume of the antenna is compact and measured only 99.69 mm3. The peak specific absorption rate value of the loaded antenna is noted at 595 W/kg for input power of 1 W, while the radiation efficiency of the antenna is noted by 7.5% at the resonance. The fabricated prototype is inserted into the minced pork and dipped into a skin mimicking gel for the measurement purpose. Furthermore, the link margin has been analysed, which predicts a possible transmission range up to 40 m for a signal bit rate ≤5 Mbps. The impact of associated circuit components on the antenna performance has also been investigated.

Topology optimization of microchannel heat sinks using a two-layer model

This paper investigates the topology optimization of microchannel heat sinks. A two-layer heat sink model is developed allowing to do topology optimizations at close to two-dimensional computational cost. In the model, reduced two-dimensional fluid dynamics equations proposed in the literature based on a plane flow assumption are adopted. By assuming a fourth-order polynomial temperature profile of the heat sink thermal-fluid layer and a linear temperature profile in the substrate, two-dimensional heat transfer governing equations of the two layers are obtained which are thermally coupled through an out-of-plane heat flux term. Topology optimizations of a square heat sink are carried out using the two-layer model. Comparison with a three-dimensional conjugate heat transfer analysis of optimized designs in COMSOL Multiphysics validates the accuracy of the two-layer model. The re-evaluation of an optimized design by a one-layer model commonly seen in the literature shows the inadequacy of the one-layer model in predicting physical fields properly. In addition, the influence of physical and optimization parameters on the layout complexity of optimized designs is studied and related to the Peclet number. Optimizations under diffusion-dominated conditions are performed and typical optimized topologies for heat conduction structures are seen.

Contact model analysis on cladding designs against thermal shock for the lower head of central measuring shroud in a fast reactor

The central measuring shroud in the fast reactor has the function to support the in-vessel measuring equipment and control rods. Ensuring its integrity is an important part of guaranteeing the safety of the reactor’s operation. When the fast reactor is under the scram condition, however, the coolant temperature drops rapidly at almost 14 K per second. Such a large temperature change will bring strong thermal shock to the lower head of central measuring shroud (LHCMS), which is located above the core outlet. Since thermal shock is one of the factors to cause initial crack or even damage of the LHCMS, cladding is always added to the LHCMS to protect it from thermal shock damage. However, there are no general design guidelines for the cladding. In the process of design, selection of the number of layers and layout schemes between layers require detailed numerical calculations, and the stress levels of different design schemes need to be analyzed. At present, most of the research focuses on the influence of material properties on thermal shock, and lacks of research on the effect of different cladding design on the stress of the cladding and LHCMS. In the paper, therefore, the finite element software was used to establish two models to analyze the stress difference between one-layer cladding model and two-layer cladding model with contact. The temperature and stress distribution of the two models were calculated according to the scram temperature curve of the fast reactor. And fatigue analysis was applied to give fatigue damage factors of two models. The results indicate that the maximum stress in the thickness direction appears on the surfaces in contact with the external fluid at the last moment, rather than the time temperature drops the fastest. Furthermore, because of irregular thermal expansion between layers, stress step shows on the contact surfaces, and the stress of the outermost cladding of the two-layer model is greater than the stress at the same position of the one-layer model, which means when the cladding layers are contacted with each other, even if the cladding is divided into multiple layers, which should reduce the stress, the stress caused by thermal shock cannot be reduced, but increased. Besides, the results of fatigue analysis also prove that the stress of two-layer model is greater than that of one-layer model. The study is useful for the cladding design of components in a fast reactor.

Regional ionospheric TEC modeling based on a two-layer spherical harmonic approximation for real-time single-frequency PPP

The ionosphere has been considered as one of the major error sources in GNSS signal propagation, and it is still difficult to be modeled precisely, especially for real-time positioning applications. The commonly used ionospheric models are usually based on the one-layer approximation, which neglects the ionospheric variation in the vertical domain and limits the scope of improvement over one-layer models. A new ionospheric model based on the two-layer approximation and two spherical harmonic (SH) functions is proposed in this contribution, where a quasi-globe projection is designed to avoid the inherent ill-posed problem and retain the physical meaning of the SH when regional data are used. GPS and BDS data from the National Positioning Infrastructure of Australia and Crustal Movement Observation Network of China are used for validating the new model’s performance in different areas and different periods. Results show (1) the precision of ionospheric TEC estimates from the new model can be improved by about 26% and 31% in the cross-validation experiment compared to the traditional one-layer model in Australian and Chinese regions, respectively; (2) the positioning accuracy of kinematic single-frequency precise point positioning (SF-PPP) in the experimental regions using the new model reaches about 0.7 m and 0.8 m in the horizontal and vertical components, respectively, in comparison with the one-layer model’s 1.0 m (horizontal) and 1.4 m (vertical); (3) the convergence time of the SF-PPP using the new model is 5–10 min for achieving a sub-meter level of positioning accuracy in both horizontal and vertical components, whereas it needs 30–40 min in case the one-layer model is used.

Multiobjective Optimization of a Tubular Coreless LPMSM Based on Adaptive Multiobjective Black Hole Algorithm

In most multiobjective optimization problems of electrical machines, the weighted function method is used to convert them into single-objective optimization problems. This paper applies a kind of new multiobjective evolutionary algorithms (MOEAs), called adaptive multiobjective black hole (AMOBH) algorithms, to achieve effective multiobjective optimization of a tubular coreless linear permanent magnet synchronous motor (LPMSM). To reduce the computation cost of the MOEAs, a one-layer analytical model (AM) is presented for the tubular coreless LPMSM in this paper. The accuracy of the simplified one-layer AM is verified by comparisons with multilayer AM and finite element analysis (FEA) under different structure parameters. It is found that the simplified AM has good accuracy and can decrease the computation cost significantly. AMOBH algorithm is subsequently introduced. The optimal Pareto front with regard to thrust, copper loss, and permanent magnet volume are analyzed, and more diversified optimization results are provided. The final Pareto solution can be selected directly by practical physical values according to the application requirements. Finally, a prototype is fabricated for the selected design; its experimental results are provided and compared with those of the FEA results.

A New Multilayer Nonhydrostatic Formulation for Surface Water Waves

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.

On simple representations of the climate response to external radiative forcing

Global warming in response to external radiative forcing is determined by the feedback of the climate system. Recent studies have suggested that simple mathematical models incorporating a radiative response which is related to upper- and deep-ocean disequilibrium (ocean heat uptake efficacy), inhomogeneous patterns of surface warming and radiative feedbacks (pattern effect), or an explicit dependence of the strength of radiative feedbacks on surface temperature change (feedback temperature dependence) may explain the climate response in atmosphere-ocean coupled general circulation models (AOGCMs) or can be useful for interpreting the instrumental record. We analyze a two-layer model with an ocean heat transport efficacy, a two-region model with region specific heat capacities and radiative responses; a one-layer model with a temperature dependent feedback; and a model which combines elements of the two-layer/region models and the state-dependent feedback parameter. We show that, from the perspective of the globally averaged surface temperature and radiative imbalance, the two-region and two-layer models are equivalent. State-dependence of the feedback parameter introduces a nonlinearity in the system which makes the adjustment timescales forcing-dependent. Neither the linear two-region/layer models, nor the state-dependent feedback model adequately describes the behavior of complex climate models. The model which combines elements of both can adequately describe the response of more comprehensive models but may require more experimental input than is available from single forcing realizations.

A stepwise method for estimating optical properties of two-layer turbid media from spatial-frequency domain reflectance.

This research was conducted to estimate the optical absorption and reduced scattering coefficients of two-layer turbid media using a stepwise method from the spatial-frequency domain reflectance generated by Monte Carlo (MC) simulation. The stepwise method's feasibility for optical property estimations was first investigated by comparing the reflectance generated by the diffusion model and MC simulation for one-layer and two-layer turbid media. The results showed that, with proper frequency selection, the one-layer model could be used for estimating the optical properties of the first layer of the two-layer turbid media. A sample-based calibration method was proposed for calibrating discrepancies of the reflectance between the diffusion model and MC simulation. This significantly improved the parameter estimation accuracy. Results showed that the stepwise method's parameter estimation efficacy and accuracy were much better than that for the one-step method. This was especially true when estimating the absorption coefficient. Absolute error contour maps were generated in order to determine the constraining conditions for the first-layer thickness. It was found that, when each layer's optical properties are within the range of 0.005 mm-1 ≤ μa ≤ 0.04 mm-1 and 0.69 mm-1 ≤ μs'≤ 2.2 mm-1, the first-layer's minimum thickness-for which the first layer's optical properties could be accurately estimated-could be as small as 0.2 mm. Further, the first layer's maximum thickness could not exceed 2.0 mm, in order to have acceptable estimations of the optical properties of the second layer.

Antenna-in-Package Design and Robust Test for the Link Between Wireless Ingestible Capsule and Smart Phone

An antenna-in-package is proposed for a wireless ingestible capsule operated at ISM (2.4–2.48 GHz) band and also experimentally tested in a system level. The proposed antenna is designed for data transmission between the ingestible capsule and a smart phone using Bluetooth. A modified planar inverted-F structure is proposed for the antenna design, whose end section is bent to be vertical with respect to the substrate, mainly for the considerations of frequency tuning, size reduction, and polarization diversity. First, a one-layer cube muscle phantom model is used for initial design and optimization. Then, a comprehensive evaluation method, with considerations of the polarization mismatch loss, is proposed to analyze the radiation performance using a CST human body model. The evaluated results indicate that the proposed design can ensure enough margins for the link budget despite the relative position between the capsule and the smart phone. In addition to the advantages stated above, the proposed antenna is not sensitive to different digestive organs. Reflection measurement is presented using a muscle-mimicking phantom. Radiation characteristics are presented using a simple human torso model filled with pork by measuring the received power in a system. Successful data transmission, between a transmitter using the proposed antenna and a receiver using a smart phone, is performed in a temperature monitoring system.

Multi-layer Long Short-term Memory based Condenser Vacuum Degree Prediction Model on Power Plant

A multi-layer LSTM (Long short-term memory) model is proposed for condenser vacuum degree prediction of power plants. Firstly, Min-max normalization is used to pre-process the input data. Then, the model proposes the two-layer LSTM architecture to identify the time series pattern effectively. ADAM（Adaptive moment）optimizer is selected to find the optimum parameters for the model during training. Under the proposed forecasting framework, experiments illustrates that the two-layer LSTM model can give a more accurate forecast to the condenser vacuum degree compared with other simple RNN (Recurrent Neural Network) and one-layer LSTM model.

Transitions from low-density state towards high-density state in stochastic bistable plasma-condensate systems

In this article we study transitions from low-density states towards high-density states in bistable plasma-condensate systems. We take into account an anisotropy in transference of adatoms between neighbour layers induced by the electric field near substrate. We derive the generalized one-layer model by assuming that the strength of the electric field is subjected to both periodic oscillations and multiplicative fluctuations. By studying the homogeneous system we discuss the corresponding mean passage time. In the limit of weak fluctuations, we show the optimization of the mean passage time with variation in the frequency of periodic driving in the non-adiabatic limit. Noise induced effects corresponding to asynchronization and acceleration in the transition dynamics are studied in detail.

Fragment-Based Approaches for Supramolecular Interaction Energies: Applications to Foldamers and Their Complexes with Anions.

We explore the application of our multilayer Molecules-in-Molecules (MIM) fragment-based method for the study of the energies in supramolecular systems, viz. foldamers and their anion bound complexes. The performance of five different density functional theory (DFT) methods in conjunction with the fragmentation-based method is evaluated against the unfragmented energies for a test set of 5 foldamers (82 to 170 atoms). A systematic protocol has been developed to account for the π···π interactions in such systems in addition to the traditional fragmentation of the system along the backbone comprised of covalently bonded dimer (or trimer) units. We find a significant improvement in the performance of the method on going from a one-layer MIM1 model (errors >10 kcal/mol) to a two-layer MIM2 model (errors 0-2 kcal/mol), due to the incorporation of long-range interactions in the latter approach. Furthermore, we extend the applicability of MIM2 models to determine accurate binding energies of macromolecular receptor-anion complexes. For three different anion bound macrocycles, our MIM2 protocol provides total energies within 1.5 kcal/mol of the unfragmented energies for most of the DFT methods. The corresponding anion binding energies are calculated within 0.5 kcal/mol of the unfragmented binding energies due to systematic error cancellation between the macrocycle and the macrocycle-anion complex. Finally, we have calibrated the absolute accuracy in the calculated binding energies by comparison with unfragmented DLPNO-CCSD(T) calculations on three macromolecule-chloride anion complexes. The most accurate results are obtained using a MIM2 model using DLPNO-CCSD(T) calculations on trimer units as the high level and DFT-D3 (e.g., M06-2X-D3) as the low level of theory, yielding sub kcal/mol errors in the anion binding energies. Our protocol can be an accurate method to calculate anion binding energies for very large supramolecular systems.