A symmetric substructuring method for analyzing the natural frequencies of conical origami structures

Conical origami structures are characterized by their substantial out-of-plane stiffness and energy-absorptioncapacity.Previous investigations have commonly focused on the static characteristics of these lightweight struc-tures.However,the efficient analysis of the natural vibrations of these structures is pivotal for designing conicalorigami structures with programmable stiffness and mass.In this paper,we propose a novel method to analyzethe natural vibrations of such structures by combining a symmetric substructuring method(SSM)and a gener-alized eigenvalue analysis.SSM exploits the inherent symmetry of the structure to decompose it into a finiteset of repetitive substructures.In doing so,we reduce the dimensions of matrices and improve computationalefficiency by adopting the stiffness and mass matrices of the substructures in the generalized eigenvalue analysis.Finite element simulations of pin-jointed models are used to validate the computational results of the proposedapproach.Moreover,the parametric analysis of the structures demonstrates the influences of the number of seg-ments along the circumference and the radius of the cone on the structural mass and natural frequencies of thestructures.Furthermore,we present a comparison between six-fold and four-fold conical origami structures anddiscuss the influence of various geometric parameters on their natural frequencies.This study provides a strategyfor efficiently analyzing the natural vibration of symmetric origami structures and has the potential to contributeto the efficient design and customization of origami metastructures with programmable stiffness.

Unified deep learning model for predicting fundus fluorescein angiography image from fundus structure image

The prediction of fundus fluorescein angiography(FFA)images from fundus structural images is a cutting-edge research topic in ophthalmological image processing.Prediction comprises estimating FFA from fundus camera imaging,single-phase FFA from scanning laser ophthalmoscopy(SLO),and three-phase FFA also from SLO.Although many deep learning models are available,a single model can only perform one or two of these prediction tasks.To accomplish three prediction tasks using a unified method,we propose a unified deep learning model for predicting FFA images from fundus structure images using a supervised generative adversarial network.The three prediction tasks are processed as follows:data preparation,network training under FFA supervision,and FFA image prediction from fundus structure images on a test set.By comparing the FFA images predicted by our model,pix2pix,and CycleGAN,we demonstrate the remarkable progress achieved by our proposal.The high performance of our model is validated in terms of the peak signal-to-noise ratio,structural similarity index,and mean squared error.

Band structure calculation of scalar waves in two-dimensional phononic crystals based on generalized multipole technique

A multiple monopole （or multipole） method based on the generalized mul- tipole technique （GMT） is proposed to calculate the band structures of scalar waves in two-dimensional phononic crystals which are composed of arbitrarily shaped cylinders embedded in a host medium. In order to find the eigenvalues of the problem, besides the sources used to expand the wave field, an extra monopole source is introduced which acts as the external excitation. By varying the frequency of the excitation, the eigenvalues can be localized as the extreme points of an appropriately chosen function. By sweeping the frequency range of interest and sweeping the boundary of the irreducible first Brillouin zone, the band structure is obtained. Some numerical examples are presented to validate the proposed method.

Generalized Pareto Distribution Model and Its Application to Hydrocarbon Resource Structure Prediction of the Huanghua Depression

The generalized Pareto distribution model is a kind of hydrocarbon pool size probability statistical method for resource assessment. By introducing the time variable, resource conversion rate and the geological variable, resource density, such model can describe not only different types of basins, but also any exploration samples at different phases of exploration, up to the parent population. It is a dynamic distribution model with profound geological significance and wide applicability. Its basic principle and the process of resource assessment are described in this paper. The petroleum accumulation system is an appropriate assessment unit for such method. The hydrocarbon resource structure of the Huanghua Depression in Bohai Bay Basin was predicted by using this model. The prediction results accord with the knowledge of exploration in the Huanghua Depression, and point out the remaining resources potential and structure of different petroleum accumulation systems, which are of great significance for guiding future exploration in the Huanghua Depression.

Generalized Artificial Life Structure for Time-dependent Problems

In recent years, more attention has been paid on artificial life researches. Artificial life（AL） is a research on regulating gene parameters of digital organisms under complicated problematic environments through natural selections and evolutions to achieve the final emergence of intelligence. Most recent studies focused on solving certain real problems by artificial life methods, yet without much address on the AL life basic mechanism. The real problems are often very complicated, and the proposed methods sometimes seem too simple to handle those problems. This study proposed a new approach in AL research, named ＂generalized artificial life structure（GALS）＂, in which the traditional ＂gene bits＂ in genetic algorithms is first replaced by ＂gene parameters＂, which could appear anywhere in GALS. A modeling procedure is taken to normalize the input data, and AL ＂tissue＂ is innovated to make AL more complex. GALS is anticipated to contribute significantly to the fitness of AL evolution. The formation of ＂tissue＂ begins with some different AL basic cells, and then tissue is produced by the casual selections of one or several of these cells. As a result, the gene parameters, represented by ＂tissues＂, could become highly diversified. This diversification should have obvious effects on improving gene fitness. This study took the innovative method of GALS in a stock forecasting problem under a carefully designed manipulating platform. And the researching results verify that the GALS is successful in improving the gene evolution fitness.

GENERALIZED STRUCTURE OF LAX REPRESENTATIONS FOR NONLINEAR EVOLUTION EQUATION

A new production form for a hierarchy of nonlinear evolution equations (NLEEs) is given in this paper. The form contains productions of isospectral and non-isospectral hierarchy. Under this form a generalized structure of Lax representations for the hierarchy of NLEEs is this presented. As a concrete example, the Levi-hierarchy of evolution equations are discussed at the end of this paper.

ON A GENERALIZED MODULUS OF CONVEXITY AND UNIFORM NORMAL STRUCTURE

In this article, the authors study a generalized modulus of convexity, δ（α） （ε）. Certain related geometrical properties of this modulus are analyzed. Their main result is that Banach space X has uniform normal structure if there exists ε, 0 ≤e≤ 1, such that δ^（α）（1＋ε ） 〉 （1- α）ε.

Dual Characteristic Pairs in Generalized Complex Structures

This paper presents the relations between spinors and dual characteristic pairs, and gives a way to get the dual characteristic pairs of Dirac structure associated to a generalized complex structure.

gscaLCA in R: Fitting Fuzzy Clustering Analysis Incorporated with Generalized Structured Component Analysis

Clustering analysis identifying unknown heterogenous subgroups of a population(or a sample)has become increasingly popular along with the popularity of machine learning techniques.Although there are many software packages running clustering analysis,there is a lack of packages conducting clustering analysis within a structural equation modeling framework.The package,gscaLCA which is implemented in the R statistical computing environment,was developed for conducting clustering analysis and has been extended to a latent variable modeling.More specifically,by applying both fuzzy clustering(FC)algorithm and generalized structured component analysis(GSCA),the package gscaLCA computes membership prevalence and item response probabilities as posterior probabilities,which is applicable in mixture modeling such as latent class analysis in statistics.As a hybrid model between data clustering in classifications and model-based mixture modeling approach,fuzzy clusterwise GSCA,denoted as gscaLCA,encompasses many advantages from both methods:(1)soft partitioning from FC and(2)efficiency in estimating model parameters with bootstrap method via resolution of global optimization problem from GSCA.The main function,gscaLCA,works for both binary and ordered categorical variables.In addition,gscaLCA can be used for latent class regression as well.Visualization of profiles of latent classes based on the posterior probabilities is also available in the package gscaLCA.This paper contributes to providing a methodological tool,gscaLCA that applied researchers such as social scientists and medical researchers can apply clustering analysis in their research.

ON A GENERALIZED GEOMETRIC CONSTANT AND SUFFICIENT CONDITIONS FOR NORMAL STRUCTURE IN BANACH SPACES

In this paper, we introduce a new geometric constant C;（a, X） of a Banach space X, which is closely related to the generalized von Neumann-Jordan constant and analyze some properties of the constant. Subsequently, we present several sufficient conditions for normal structure of a Banach space in terms of this new constant, the generalized James constant, the generalized Garc′?a-Falset coefficient and the coefficient of weak orthogonality of Sims. Our main results of the paper generalize some known results in the recent literature.

SIMILARITY TRANSFORMATION, THE STRUCTURE OF THE TRAVELING WAVES SOLUTION AND THE EXISTENCE OF A GLOBAL SMOOTH SOLUTION TO GENERALIZED KURAMOTO SIVASHINSKY TYPE EQUATIONS

The existence of a global smooth solution for the initial value problem of generalized Kuramoto-Sivashinsky type equations have been obtained. Similarty siolutions and the structure of the traveling waves solution for the generalized KS equations are discussed and analysed by using the qualitative theory of ODE and Lie's infinitesimal transformation respectively.

An Overview of the Multi-Band and the Generalized BCS Equations-Based Approaches to Deal with Hetero-Structured Superconductors

We trace the conceptual basis of the Multi-Band Approach (MBA) and recall the reasons for its wide following for composite superconductors (SCs). Attention is then drawn to a feature that MBA ignores: the possibility that electrons in such an SC may also be bound via simultaneous exchanges of quanta with more than one ion-species—a lacuna which is addressed by the Generalized BCS Equations (GBCSEs). Based on several papers, we give a concise account of how this approach: 1) despite employing a single band, meets the criteria satisfied by MBA because a) GBCSEs are derived from a temperature-incorporated Bethe-Salpeter Equation the kernel of which is taken to be a “superpropagator” for a composite SC-each ion-species of which is distinguished by its own Debye temperature and interaction parameter and b) the band overlapping the Fermi surface is allowed to be of variable width. GBCSEs so-obtained reduce to the usual equations for the Tc and Δ of an elemental SC in the limit superpropagator → 1-phonon propagator;2) accommodates moving Cooper pairs and thereby extends the scope of the original BCS theory which restricts the Hamiltonian at the outset to terms that correspond to pairs having zero centre-of-mass momentum. One can now derive an equation for the critical current density (j0) of a composite SC at T = 0 in terms of the Debye temperatures of its ions and their interaction parameters— parameters that also determine its Tc and Δs;3) transforms the problem of optimizing j0 of a composite SC, and hence its Tc, into a problem of chemical engineering;4) provides a common canopy for most composite SCs, including those that are usually regarded as outside the purview of the BCS theory and have therefore been called “exceptional”, e.g., the heavy-fermion SCs;5) incorporates s±-wave superconductivity as an in-built feature and can therefore deal with the iron-based SCs, and 6) leads to presumably verifiable predictions for the values of some relevant parameters, e.g., the effective mass of electrons, for the SCs for which it has been employed.

Characterization of the generalized permeability jail in tight reservoirs by analyzing relative-permeability curves and numerical simulation

This study comprehensively characterizes the boundary values of generalized permeability jail in tight reservoirs through relative-permeability curve analysis,numerical simulation,and economic evaluation.A total number of 108 relative-permeability curves of rock samples from tight reservoirs were obtained,and the characteristics of relative-permeability curves were analyzed.The irreducible water saturation(Swi)mainly ranges from 20% to 70%,and the residual gas saturation(Sgr)ranges from 5% to 15% for 55% of the samples.The relative-permeability curves are categorized into six types(Category-Ⅰ to Ⅵ)by analyzing the following characteristics:The relative permeability of gas at Swi,the relative permeability of water at Sgr,and the relative permeability corresponding to the isotonic point.The relative permeability curves were normalized to facilitate numerical simulation and evaluate the impact of different types of curves on production performance.The results of simulation show significant difference in production performance for different types of relative-permeability curves:Category-Ⅰ corresponds to the case with best well performance,whereas Categories-Ⅴ and Ⅵ correspond to the cases with least production volume.The results of economic evaluation show a generalized permeability jail for Categories-Ⅳ,Ⅴ,and Ⅵ,and the permeability jail develops when the relative permeability of gas and water is below 0.06.This study further quantifies the range of micro-pore parameters corresponding to the generalized permeability jail for a tight sandstone reservoir.

A GENERALIZED LIPSCHITZ SHADOWING PROPERTY FOR FLOWS

In this paper,we define a generalized Lipschitz shadowing property for flows and prove that a flowΦgenerated by a C1vector field X on a closed Riemannian manifold M has this generalized Lipschitz shadowing property if and only if it is structurally stable.

Global interpolating meshless shape function based on generalized moving least-square for structural dynamic analysis

A global interpolating meshless shape function based on the generalized moving least-square （GMLS） is formulated by the transformation technique. Both the shape function and its derivatives meet the Kronecker delta function property. With the interpolating GMLS （IGMLS） shape function, an improved element-free Galerkin （EFG） method is proposed for the structural dynamic analysis. Compared with the conven- tional EFG method, the obvious advantage of the proposed method is that the essential boundary conditions including both displacements and derivatives can be imposed by the straightforward way. Meanwhile, it can greatly improve the ill-condition feature of the standard GMLS approximation, and provide good accuracy at low cost. The dynamic analyses of the Euler beam and Kirchhoff plate are performed to demonstrate the feasi- bility and effectiveness of the improved method. The comparison between the numerical results of the conventional method and the improved method shows that the proposed method has better stability, higher accuracy, and less time consumption.

The characteristics of tectonic stress field about strike slip earthquake－generating structure in the Chinese mainland

This paper is one of the series papers about the study on strike-slip earthquake-generating structure in the Chinese mainland. In the first part of this paper, based on the large amount of data from large earthquake investigation and the latest results of focal mechanism, the earthquake-generating structure in the Chinese mainland interior and its neighbouring region is discussed. It is concluded that the absolutely predominated earthquake, not only in number, but also in intensity, as well as in distributing area, is strike slip earthquake, and it is further stressed that the study on the strike slip earthquake-generating structure is significant for seismic risk analysis. In the second part, the characteristics of tectonic stress field about strike slip earthquake-generating structure and the compiled distribution outline of strike slip earthquake-generating fault, normal fault, and thrust fault in the Chinese mainland interior and its neighbouring region, in the light of stress characteristics of fault plane solutions, are also discussed.

Ventilation Structure Optimization and Performance Analyses of Permanent Magnet Wind Generators

为了提高永磁风力发电机的通风冷却效果,以一台2.5 MW永磁风力发电机为例,基于计算流体力学（computational fluid dynamics,CFD）以及传热传质学基本理论,根据流–热协同机理,建立了包括外部通风系统的三维流体流动与传热的求解模型。应用有限体积元法,对电机通风冷却性能进行了数值研究,并与实验数据进行对比分析,实验结果验证了计算结果的准确性以及求解方法的合理性。通过改变电机内径向通风沟结构尺寸,提出4种优化方案,通过对不同结构方案条件下通风冷却性能进行对比研究,给出了发电机最佳的结构方案。所得结论可以为永磁风力发电机通风结构的设计提供参考。

Estimation of generalized soil structure index based on differential spectra of different orders by multivariate assessment

Better soil structure promotes extension of plant roots thereby improving plant growth and yield.Differences in soil structure can be determined by changes in the three phases of soil,which in turn affect soil function and fertility levels.To compare the quality of soil structure under different conditions,we used Generalized Soil Structure Index(GSSI)as an indicator to determine the relationship between the“input”of soil three phases and the“output”of soil structure.To achieve optimum monitoring of comprehensive indicators,we used Successive Projections Algorithm(SPA)for differential processing based on 0.0–2.0 fractional orders and 3.0–10.0 integer orders and select important wavelengths to process soil spectral data.In addition,we also applied multivariate regression learning models including Gaussian Process Regression(GPR)and Artificial Neural Network(ANN),exploring potential capabilities of hyperspectral in predicting GSSI.The results showed that spectral reflection,mainly contributed by long-wave near-infrared radiation had an inverse relationship with GSSI values.The wavelengths between 404-418 nm and 2193–2400 nm were important GSSI wavelengths in fractional differential spectroscopy data,while those ranging from 543 to 999 nm were important GSSI wavelengths in integer differential spectroscopy data.Also,non-linear models were more accurate than linear models.In addition,wide neural networks were best suited for establishing fractional-order differentiation and second-order differentiation models,while fine Gaussian support vector machines were best suited for establishing first-order differentiation models.In terms of preprocessing,a differential order of 0.9 was found as the best choice.From the results,we propose that when constructing optimal prediction models,it is necessary to consider indicators,differential orders,and model adaptability.Above all,this study provided a new method for an in-depth analyses of generalized soil structure.This also fills the gap limiting the detection of soil three phases structural characteristics and their dynamic changes and provides a technical references for quantitative and rapid evaluation of soil structure,function,and quality.

PHYSICAL STRUCTURE OF GEOGRAPHICAL ENVIRONMENT-INTEGRITY AND DISPARITY,GENERALITY AND INDIVIDUALITY

Integrity and disparity are two of the basic characteristics implied in the scientific connotation of the physical environment as a material system. From a dialectical materialistic point of view the physical character of geographical environment of the earth surface is the unity in diversity. It is on such grounds that the two basic characteristics were put forth by the author in his monograph 'Physical Structure of South American Geographical Environment' as the underlying theme. This holds true for the hierarchy of physical regions. For instance, the physical environment of the earth surface in unity behaves as a huge whole, yet, in differentiation into continents, it displays disparity; each continent differs from others and becomes an integrity in its own right. The same is true of regions of lower levels. In the case of generality and individuality of regional types and their constituent distributive areas in different continents, the same relationship exists among them. Owing to similar origin

The structure features of stick-slip mechanism of the strike-slip earthquake generating structure in the interior of the Chinese mainland

This is the third one of the paper series on the strike slip earthquake generating structure in the interior of the Chinese mainland. The features of the tectonic stress field of strike slip earthquake generating structure were discussed in the first paper (Huan et al ., 1994), and the features of the deformation field of strike slip earthquake were presented in the second paper (Hun et al ., 1994). In the first section of this paper, through the analysis of the strike slip earthquake generating structure of several dozen large earthquakes with magnitude greater than 6.0, it is concluded that almost all strike slip earthquake generating faults are characterized by the oblique arranged distribution, and the barrier structure mode about the adhesive slip movement of strike slip is put forward; then in the second section, its four types, due to the different fracture form of the barrier at the ends, are also discussed; finally in the third section, the fracture terminating scale of the barrier of strike slip earthquake generating fault is also discussed.