Application of the Conditional Nonlinear Local Lyapunov Exponent to Second-Kind Predictability

In order to quantify the influence of external forcings on the predictability limit using observational data,the author introduced an algorithm of the conditional nonlinear local Lyapunov exponent(CNLLE)method.The effectiveness of this algorithm is validated and compared with the nonlinear local Lyapunov exponent(NLLE)and signal-to-noise ratio methods using a coupled Lorenz model.The results show that the CNLLE method is able to capture the slow error growth constrained by external forcings,therefore,it can quantify the predictability limit induced by the external forcings.On this basis,a preliminary attempt was made to apply this method to measure the influence of ENSO on the predictability limit for both atmospheric and oceanic variable fields.The spatial distribution of the predictability limit induced by ENSO is similar to that arising from the initial conditions calculated by the NLLE method.This similarity supports ENSO as the major predictable signal for weather and climate prediction.In addition,a ratio of predictability limit(RPL)calculated by the CNLLE method to that calculated by the NLLE method was proposed.The RPL larger than 1 indicates that the external forcings can significantly benefit the long-term predictability limit.For instance,ENSO can effectively extend the predictability limit arising from the initial conditions of sea surface temperature over the tropical Indian Ocean by approximately four months,as well as the predictability limit of sea level pressure over the eastern and western Pacific Ocean.Moreover,the impact of ENSO on the geopotential height predictability limit is primarily confined to the troposphere.

An Improved Unique Fatigue Crack Growth Rate Curve Model and Determination of the Model Shape Exponents

It is essential to precisely predict the crack growth,especially the near-threshold regime crack growth under different stress ratios,for most engineering structures consume their fatigue lives in this regime under random loading.In this paper,an improved unique curve model is proposed based on the unique curve model,and the determination of the shape exponents of this model is provided.The crack growth rate curves of some materials taken from the literature are evaluated using the improved model,and the results indicate that the improved model can accurately predict the crack growth rate in the nearthreshold and Paris regimes.The improved unique curve model can solve the problems about the shape exponents determination and weak ability around the near-threshold regime meet in the unique curve model.In addition,the shape exponents in the improved model at negative stress ratios are discussed,which can directly adopt that in the unique curve model.

A Direct Calculation of Critical Exponents of Two-Dimensional Anisotropic Ising Model

Using an exact solution of the one-dimensional quantum transverse-field Ising model, we calculate the critical exponents of the two-dimensional anisotropic classical Ising model （IM）. We verify that the exponents are the same as those of isotropic claesical IM. Our approach provides an alternative means of obtaining and verifying these well-known results.

General mapping of one-dimensional non-Hermitian mosaic models to non-mosaic counterparts:Mobility edges and Lyapunov exponents

We establish a general mapping from one-dimensional non-Hermitian mosaic models to their non-mosaic counterparts.This mapping can give rise to mobility edges and even Lyapunov exponents in the mosaic models if critical points of localization or Lyapunov exponents of localized states in the corresponding non-mosaic models have already been analytically solved.To demonstrate the validity of this mapping,we apply it to two non-Hermitian localization models:an Aubry-Andre-like model with nonreciprocal hopping and complex quasiperiodic potentials,and the Ganeshan-Pixley-Das Sarma model with nonreciprocal hopping.We successfully obtain the mobility edges and Lyapunov exponents in their mosaic models.This general mapping may catalyze further studies on mobility edges,Lyapunov exponents,and other significant quantities pertaining to localization in non-Hermitian mosaic models.

Unusual Behaviour of Dislocation Velocity Exponent in Dislocation Multiplication Model

The chaotic behaviour of dislocation multiplication process was investigated. The change of Lyapunov exponent which is used to determine the stability of quasi-periodic and chaotic behavior as well as that of equilibrium points, and periodic solution was reported by using an iteration model of dislocation multiplication. An unusual behavior of Lyapunov exponent and Feigenbaum exponent which respond to the geometric convergence of orbit from bifurcation to chaos was shown by dislocation velocity exponent m and there is a distinction on the tendency of convergence for the dislocation multiplication model when it was compared with logistic map. It is reasonable for the difference to be analyzed from the materials viewpoint. (Edited author abstract) 9 Refs.

Exponent及Gauss型遥测数据建模初始化算法

在对某大型航天电子设备的遥测数据建模时,经常遇到含有指数类变化规律的数据,对其进行建模可以为研究设备性能的变化规律、实际与设计的差异等提供手段。针对有指数变化趋势的遥测数据,采用Exponent模型、Gauss模型对遥测数据建模,给出了这种数据模型的表达式,研究了2种模型的参数初始化算法。通过数值实验说明模型参数初始化算法的有效性,为后续利用最优化理论求解模型精确参数提供了良好的初试点。

Influence of velocity spatiotemporal correlations on the anomalous scaling exponents of passive scalars

In this paper, we consider spatial-temporal correlation functions of the turbulent velocities. With numerical simulations on the Gledzer-Ohkitani-Yamada （GOY） shell model, we show that the correlation function decays exponentially. The advecting velocity field is regarded as a colored noise field, which is spatially and temporally correlative. For comparison, we are also given the scaling exponents of passive scalars obtained by the Gaussian random velocity field, the multi-dimensional normal velocity field and the She-Leveque velocity field, introduced by She, et al. We observe that extended self-similarity sealing exponents H（p）/H（2） of passive scalar obtained by the colored noise field are more anomalous than those obtained by the other three velocity fields.

The Isentropic Exponent of Single-Ionized Mono-Atomic Plasmas

The isentropic exponent of single-ionized mono-atomic plasmas in thermal equilib- rium is studied. Its behavior as a function of the ionization degree and temperature is examined for argon and zinc plasmas at two pressures （1 bar and 1 mbar, 1 mPa and 1 Pa）, respectively. The results show that for the two sorts of plasma the isentropic exponent equals typically about 1.1-1.2 within a considerably wide range of the ionization degree （5%-80%）.

Percolation Network Modeling of Electrical Properties of Reservoir Rock*

Based on the percolation network model characterizing reservoir rock＇s pore structure and fluid characteristics, this paper qualitatively studies the effects of pore size, pore shape, pore connectivity, and the amount of micropores on the I - Sw curve using numerical modeling. The effects of formation water salinity on the electrical resistivity of the rock are discussed. Then the relative magnitudes of the different influencing factors are discussed. The effects of the different factors on the I - Sw curve are analyzed by fitting simulation results. The results show that the connectivity of the void spaces and the amount of micropores have a large effect on the I - S, curve, while the other factors have little effect. The formation water salinity has a large effect on the absolute resistivity values. The non-Archie phenomenon is prevalent, which is remarkable in rocks with low permeability.

THE AVALANCHE DYNAMICS IN RANDOM NEAREST NEIGHBOR MODELS OF EVOLUTION WITH INTERACTION STRENGTH

A generalized Bak-Sneppen model （BS model） of biological evolution with intcraction strength θ is introduced in d-dimensional space, where the “nearest neighbors” are chosen among the 2d neighbors of the extremal site, with the probabilities rebated to the sizes of the fitnesses. Simulations of one- and two-dimensional models arc given.For given θ 〉 0, the model can self-organize, to a critical state, and the critical threshold fc（θ） decreases as θ increases. The exact gap equation depending on θ is presented, which reduces to the gap equation of BS model as θ tends to infinity. An exact cquation for the critical exponent γ（θ） is also obtained. Scaling relations are established among the six critical exponents of the avalanches of the model.

Dynamics Modeling and Stability Analysis of Tilt Wing Unmanned Aerial Vehicle During Transition

In the transition mode of quad tilt wing-unmanned aerial vehicle(QTW-UAV),the system stability of UAV will change with the tilt angle changes,which will cause serious head drop down.Meanwhile,with the complex air flow and other disturbances,the system is prone to side bias,frying,stall and other kinetic stability problems,hence the system stability analysis has become an urgent problem to be solved.To solve the stability problem,we need the quantitative criteria of system stability and effective tool of stability analysis,and can improve the stability of the motion control by optimizing the structural parameters of the aircraft.Therefore,based on the design of the mechanical structure,the quantitative relationship between the structure parameters of the aerial vehicle and kinetic stability of the system transition mode is established by the Lyapunov exponent method.In this paper,the dynamic modeling of the position and attitude angle is carried out and the stability of the system is analyzed by Lyapunov exponent,the results show that changing the mechanical structure of the system can improve the flight stability for the system transition mode and lay a theoretical foundation for the system stability analysis.Compared with the Lyapunov direct method,this method can be construct easily,has a simple calculation process and so on.We improve the flight stability by optimizing the structure and the experiment confirms that expanding area can enhance flight stability within limits.

A time fractional model to represent rainfall process

This paper deals with a stochastic representation of the rainfall process. The analysis of a rainfall time series shows that cumulative representation of a rainfall time series can be modeled as a non-Gaussian random walk with a log-normal jump distribution and a time-waiting distribution following a tempered a-stable probability law. Based on the random walk model, a fractional Fokker-Planck equation （FFPE） with tempered a-stable waiting times was obtained. Through the comparison of observed data and simulated results from the random walk model and FFPE model with tempered a-stable waiting times, it can be concluded that the behavior of the rainfall process is globally reproduced, and the FFPE model with tempered a-stable waiting times is more efficient in reproducing the observed behavior.

Critical Finite Size Scaling Relation of the Order-Parameter Probability Distribution for the Three-Dimensional Ising Model on the Creutz Cellular Automaton

We study the order parameter probability distribution at the critical point for the three-dimensional spin-1/2 and spin-1 Ising models on the simple cubic lattice under periodic boundary conditions. The finite size scaling relation for the order parameter probability distribution is tested and verified numerically by microcanonical Creutz cellular automata simulations. The state critical exponent δ, which characterizes the far tail regime of the scaling order parameter probability distribution, is estimated for three-dimensional Ising models using the cellular automaton simulations at the critical temperature. The results are in good agreement with the Monte Carlo calculations.

THE NON-LINEAR CHAOTIC MODEL RECONSTRUCTIONFOR THE EXPERIMENTAL DATA OBTAINED FROMDIFFERENT DYNAMICSYSTEM

The non_linear chaotic model reconstruction is the major important quantitative index for describing accurate experimental data obtained in dynamic analysis. A lot of work has been done to distinguish chaos from randomness, to calulate fractral dimension and Lyapunov exponent, to reconstruct the state space and to fix the rank of model. In this paper, a new improved EAR method is presented in modelling and predicting chaotic timeseries, and a successful approach to fast estimation algorithms is proposed. Some illustrative experimental data examples from known chaotic systems are presented, emphasising the increase in predicting error with time. The calculating results tell us that the parameter identification method in this paper can effectively adjust the initial value towards the global limit value of the single peak target function nearby. Then the model paremeter can immediately be obtained by using the improved optimization method rapidly, and non_linear chaotic models can not provide long period superior predictions. Applications of this method are listed to real data from widely different areas.

Finite-Size Scaling Analysis of a Three-Dimensional Blume-Capel Model in the Presence of External Magnetic Field

The Blume-Capel model in the presence of external magnetic field H has been simulated using a cellular automaton algorithm improved from the Creutz cellular automaton in three-dimension lattice. The field critical exponent 5 is estimated using the power law relations and the finite size scaling functions for the magnetization and the susceptibility in the range -0.1≤ h = H/J ≤0. The estimated value of the field critical exponent 5 is in good agreement with the universal value （δ = 5） in three dimensions. The simulations are carried out on a simple cubic lattice under periodic boundary conditions.

Proof of the Monotonicity of Grid Size and Its Application in Grid-Size Selection for Mesoscale Models

Terrain characteristics can be accurately represented in spectrum space. Terrain spectra can quantitatively reflect the effect of topographic dynamic forcing on the atmosphere. In wavelength space, topographic spectral energy decreases with decreasing wavelength, in spite of several departures. This relationship is approximated by an exponential function. A power law relationship between the terrain height spectra and wavelength is fitted by the least-squares method, and the fitting slope is associated with grid-size selection for mesoscale models. The monotonicity of grid size is investigated, and it is strictly proved that grid size increases with increasing fitting exponent, indicating that the universal grid size is determined by the minimum fitting exponent. An example of landslide-prone areas in western Sichuan is given, and the universal grid spacing of 4.1 km is shown to be a requirement to resolve 90% of terrain height variance for mesoscale models, without resorting to the parameterization of subgrid-scale terrain variance. Comparison among results of different simulations shows that the simulations estimate the observed precipitation well when using a resolution of 4.1 km or finer. Although the main flow patterns are similar, finer grids produce more complex patterns that show divergence zones, convergence zones and vortices. Horizontal grid size significantly affects the vertical structure of the convective boundary layer. Stronger vertical wind components are simulated for finer grid resolutions. In particular, noticeable sinking airflows over mountains are captured for those model configurations.

A New Mean Reversion Model of Close-End Fund

On the basis of fractal theory, one of the nonlinear theories, this paper studies the validity of Chinese fund market fractal time sequence through Hurst exponent, calculates the H value and proposes a new close-end fund mean reversion model. Meanwhile, this paper validates the mean reversion time sequence for consecutive 54 week data of fund market. The result indicates that this model can effectively prove that Chinese close-end fund market follows the biased random walk. The research also proves that the fund discount does have mean reversion tendency and averagely the fund with high discount has a higher excess yield than that of the fund with low discount. The mean excess yield and the ratio between discount rate deviation and standard deviation demonstrate a descending relationship. The optimum investment period based on ＂mean reversion＂ is one month. Consequently this model provides a new arbitrage method through the discount of close-end fund.

Short-Time Dynamics of the Random n-Vector Model

Short-time critical behavior of the random n-vector model is studied by the theoretic renormalization-group approach.Asymptotic scaling laws are studied in a frame of the expansion in e = 4 - d for n ≠ 1 and for n = 1respectively.In d ＜ 4,the initial slip exponents θ′ for the order parameter and θ for the response function are calculated up to the second order in e ＝ 4 - d for n ≠ 1 and for n ＝ 1 at the random fixed point respectively.Our results show that the random impurities exert a strong influence on the short-time dynamics for d ＜ 4 and n ＜ nc.