A Hybrid Dung Beetle Optimization Algorithm with Simulated Annealing for the Numerical Modeling of Asymmetric Wave Equations

In the generalized continuum mechanics(GCM)theory framework,asymmetric wave equations encompass the characteristic scale parameters of the medium,accounting for microstructure interactions.This study integrates two theoretical branches of the GCM,the modified couple stress theory(M-CST)and the one-parameter second-strain-gradient theory,to form a novel asymmetric wave equation in a unified framework.Numerical modeling of the asymmetric wave equation in a unified framework accurately describes subsurface structures with vital implications for subsequent seismic wave inversion and imaging endeavors.However,employing finite-difference(FD)methods for numerical modeling may introduce numerical dispersion,adversely affecting the accuracy of numerical modeling.The design of an optimal FD operator is crucial for enhancing the accuracy of numerical modeling and emphasizing the scale effects.Therefore,this study devises a hybrid scheme called the dung beetle optimization(DBO)algorithm with a simulated annealing(SA)algorithm,denoted as the SA-based hybrid DBO(SDBO)algorithm.An FD operator optimization method under the SDBO algorithm was developed and applied to the numerical modeling of asymmetric wave equations in a unified framework.Integrating the DBO and SA algorithms mitigates the risk of convergence to a local extreme.The numerical dispersion outcomes underscore that the proposed SDBO algorithm yields FD operators with precision errors constrained to 0.5‱while encompassing a broader spectrum coverage.This result confirms the efficacy of the SDBO algorithm.Ultimately,the numerical modeling results demonstrate that the new FD method based on the SDBO algorithm effectively suppresses numerical dispersion and enhances the accuracy of elastic wave numerical modeling,thereby accentuating scale effects.This result is significant for extracting wavefield perturbations induced by complex microstructures in the medium and the analysis of scale effects.

Linear numerical calculation method for obtaining critical point,pore fluid,and framework parameters of gas-bearing media

Up to now, the primary method for studying critical porosity and porous media are experimental measurements and data analysis. There are few references on how to numerically calculate porosity at the critical point, pore fluid-related parameters, or framework-related parameters. So in this article, we provide a method for calculating these elastic parameters and use this method to analyze gas-bearing samples. We first derive three linear equations for numerical calculations. They are the equation of density p versus porosity Ф, density times the square of compressional wave velocity p Vp^2 versus porosity, and density times the square of shear wave velocity pVs^2 versus porosity. Here porosity is viewed as an independent variable and the other parameters are dependent variables. We elaborate on the calculation steps and provide some notes. Then we use our method to analyze gas-bearing sandstone samples. In the calculations, density and P- and S-velocities are input data and we calculate eleven relative parameters for porous fluid, framework, and critical point. In the end, by comparing our results with experiment measurements, we prove the viability of the method.

Quantum Chemical Studies on Proteins in the Reaction Center of Rhodobacter sphaeroides

The electronic structure of protein chains L and M in photosynthetic reaction center (PRC) of Rhodobacter sphaeroides (Van Niel) Imhoff, Truper et Pfennig) was studied by using the Overlapping Dimer Approximation method and the Extended Negative Factor Counter method at ab initio level. The result indicated that: (1) Amino acid residues, the molecular orbitals of which composed the main components of frontier orbitals of protein chain L (M), are located at the random coil areas of chain L (alpha helix areas of chain M). Since the random coil is flexible and more easy to change its conformation in the electron transfer process and to reduce the energy of the system, and the structure of the alpha helix is reletively stable, this difference might be one of the causes for the electron transfer in photosynthetic reaction center (PRC) only takes place along the L branch. (2) The His residues which axially coordinated to the 'special pair' P and accessory chlorophyll molecules (ABChls) are essentially important for the E-LUMO levels of P and ABChl. But, the corresponding molecular orbitals of these His residues do not appear in the composition of frontier orbitals of protein chains. It means that the interaction between pigment molecules and protein chains do not influence the contribution to the frontier orbitals of protein chains explicitly, but influences the corresponding E-LUMO levels significantly.

基于逆向思维能力培养的小学数学教学研究

小学数学教学效果与学生思维品质培养成效之间存在着重要的关联性,这就要求教师在教学中加强学生思维能力的培养,以满足新课标理念下教学改革对学生思维品质培养的要求。文章首先就逆向思维能力培养对小学生数学学习的重要意义进行了探讨,进而明确教师需在数学教学中重视学生逆向思维能力的培养,侧重创新教学方法,循序渐进地强化和提升学生的逆向思维能力,从而切实有效地培养学生良好的数学思维品质。

IMPROVED ALGORITHM FOR CFD/CSD COUPLED SYSTEM DESIGN AND CALCULATION

The data information transfer and time marching strategies between computational fluid dynamics （CFD） and computational structural dynamics （CSD） play crucial roles on the aeroelastic analysis in a time domain. An improved CFD/CSD coupled system is designed, including an interpolation method and an improved loosely coupled algorithm. The interpolation method based on boundary element method （BEM） is developed to transfer aerodynamic loads and structural displacements between CFD and CSD grid systems, it can be universally used in fluid structural interaction solution by keeping energy conservation. The improved loosely coupled algo-rithm is designed, thus it improves the computational accuracy and efficiency. The new interface is performed on the two-dimensional （2-D） extrapolation and the aeroelastie response of AGARD445.6 wing. Results show that the improved interface has a superior accuracy.

Recovering implied risk-neutral probability density function using SVR

Using support vector regression （SVR）, a novel non-parametric method for recovering implied risk-neutral probability density function （IRNPDF） is investigated by solving linear operator equations. First, the SVR principle for function approximation is introduced, and an SVR method for solving linear operator equations with knowing some values of the right-hand function and without knowing its form is depicted. Then, the principle for solving the IRNPDF based on SVR and the method for constructing cross-kernel functions are proposed. Finally, an empirical example is given to verify the validity of the method. The results show that the proposed method can overcome the shortcomings of the traditional parametric methods, which have strict restrictions on the option exercise price; meanwhile, it requires less data than other non-parametric methods, and it is a promising method for the recover of IRNPDF.

Finite element solution based on fast numerical technique for large-scale electromagnetic computation

A numerical technique of the target-region locating （TRL） solver in conjunction with the wave-front method is presented for the application of the finite element method （FEM） for 3-D electromagnetic computation. First, the principle of TRL technique is described. Then, the availability of TRL solver for nonlinear application is particularly discussed demonstrating that this solver can be easily used while still remaining great efficiency. The implementation on how to apply this technique in FEM based on magnetic vector potential （MVP） is also introduced. Finally, a numerical example of 3-D magnetostatic modeling using the TRL solver and FEMLAB is given. It shows that a huge computer resource can be saved by employing the new solver.

Numerical Simulation of a Planing Vessel at High Speed

Planing vessels are applied widely in civil and military situations.Due to their high speed,the motion of planning vessels is complex.In order to predict the motion of planning vessels,it is important to analyze the hydrodynamic performance of planning vessels at high speeds.The computational fluid dynamic method（CFD） has been proposed to calculate hydrodynamic performance of planning vessels.However,in most traditional CFD approaches,model tests or empirical formulas are needed to obtain the running attitude of the planing vessels before calculation.This paper presents a new CFD method to calculate hydrodynamic forces of planing vessels.The numerical method was based on Reynolds-Averaged Navier-Stokes（RANS） equations.The volume of fluid（VOF） method and the six-degrees-of-freedom equation were applied.An effective process was introduced to solve the numerical divergence problem in numerical simulation.Compared with experimental results,numerical simulation results indicate that both the running attitude and hydrodynamic performance can be predicted well at high speeds.

Functional Integrals and Excitation Energy in Three-Band Hubbard Model

The normal and anomalous Green＇s functions of antiferromagnetie state in three-band Hubbard model are studied by using functional integrals and temperature Green＇s function method. The equations of energy spectrum are derived. In addition, excitation energy of Fermi fields are calculated under long wave approximation.

Protective Design of a Warship Broadside Liquid Cabin

Based on the traditional Smoothed Particle Hydrodynamics (SPH) algorithm, the linked-list search algorithm combined with the variable smoothing length and square support domain was put forward to improve the calculation efficiency and guarantee the calculation accuracy. The physical process of high velocity fragment impact on a broadside liquid cabin was programmed for simulation. The numerical results agreed well with those of the general software ANSYS AUTODYN, which verifies the effectiveness and feasibility of the numerical method. From the perspective of the outer plate thickness of the liquid cabin, the width of the liquid cabin, and incident angle of the fragment, the influence of these parameters on protective mechanisms was analyzed to provide a basis for protective design of a broadside liquid cabin. Results show that the influence of outer plate thickness is not obvious; therefore, the conventional design can be adopted in the design of the outer plate. The width of the liquid cabin has a great influence on the residual velocity of the fragment and the width of the liquid cabin should be designed to be as wide as possible under the premise of meeting other requirements. There is a certain incident angle in which the velocity attenuation of the fragment is most obvious, and the high-pressure zone near the inner plate is asymmetric. The inner plate of liquid cabin should be strengthened according to the hull form, principal dimensions, and vulnerable points.

Inverse procedure for determining model parameter of soils using real-coded genetic algorithm

The hybrid genetic algorithm is utilized to facilitate model parameter estimation.The tri-dimensional compression tests of soil are performed to supply experimental data for identifying nonlinear constitutive model of soil.In order to save computing time during parameter inversion,a new procedure to compute the calculated strains is presented by multi-linear simplification approach instead of finite element method(FEM).The real-coded hybrid genetic algorithm is developed by combining normal genetic algorithm with gradient-based optimization algorithm.The numerical and experimental results for conditioned soil are compared.The forecast strains based on identified nonlinear constitutive model of soil agree well with observed ones.The effectiveness and accuracy of proposed parameter estimation approach are validated.

ISAR Imaging of Missing Data Based on the Iterative Adaptive Approach

Through the coherent accumulation of target echoes, inverse synthetic aperture radar （ISAR） imaging achieves high azimuth resolution. However, because of the instability of the radar system, the echoes of the 1SAR will be randomly lost. The conventional FFT processing methods can cause image blur and high sidelobes or other issues. A novel algorithm for ISAR missing-data imaging based on the Iterative Adaptive Approach （IAA） is proposed. The algorithm enjoys global convergence properties and does not need to set the parameters in advance. The missing-data ISAR imaging results for simulated and measured data illustrate the effectiveness of the algorithm.

Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes

Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.

New Exact Solutions of Zakharov-Kuznetsov Equation

The Zakharov-Kuznetsov equation is proved to be nonintegrable by standard Painleve approach and three new types of soliton solutions are obtained by means of the nonstandard truncation of the extended Painleve analysis approach.

A Novel Robust Nonlinear Dynamic Data Reconciliation

Outlier in one variable will smear the estimation of other measurements in data reconciliation （DR）. In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influence of outliers on the result of DR. This method introduces a penalty function matrix in a conventional least-square objective function, to assign small weights for outliers and large weights for normal measurements. To avoid the loss of data information, element-wise Mahalanobis distance is proposed, as an improvement on vector-wise distance, to construct a penalty function matrix. The correlation of measurement error is also considered in this article. The method introduces the robust statistical theory into conventional least square estimator by constructing the penalty weight matrix and gets not only good robustness but also simple calculation. Simulation of a continuous stirred tank reactor, verifies the effectiveness of the proposed algorithm.

New empirical model to evaluate groundwater flow into circular tunnel using multiple regression analysis

There are various analytical, empirical and numerical methods to calculate groundwater inflow into tun- nels excavated in rocky media. Analytical methods have been widely applied in prediction of groundwa- ter inflow to tunnels due to their simplicity and practical base theory. Investigations show that the real amount of water infiltrating into jointed tunnels is much less than calculated amount using analytical methods and obtained results are very dependent on tunnel＇s geometry and environmental situations. In this study, using multiple regression analysis, a new empirical model for estimation of groundwater seepage into circular tunnels was introduced. Our data was acquired from field surveys and laboratory analysis of core samples. New regression variables were defined after perusing single and two variables relationship between groundwater seepage and other variables. Finally, an appropriate model for estima- tion of leakage was obtained using the stepwise algorithm. Statistics like R, R2, R2e and the histogram of residual values in the model represent a good reputation and fitness for this model to estimate the groundwater seepage into tunnels. The new experimental model was used for the test data and results were satisfactory. Therefore, multiple regression analysis is an effective and efficient way to estimate the groundwater seeoage into tunnels.

Numerical method and model for calculating thermal storage time for an annular tube with phase change material

For calculating the thermal storage time for an annular tube with phase change material （PCM）, a novel method is proposed. The method is suitable for either low-temperature PCM or high-temperature PCM whose initial temperature is near the melting point. The deviation fit is smaller than 8% when the time is below 2x104 s. Comparison between the predictions and the reported experimental data of thermal storage time at same conditions is investigated and good agreements have been got. Based on this method, the performance of the thermal storage unit and the role of natural convection are also investigated. Results show a linear relation between the maximum amount of stored heat and thermal storage time, and their ratio increases with the height of the thermal storage unit. As the thickness of the cavity increases, natural convection plays an increasingly important role in promoting the melting behavior of paraffin. When the thickness of the cavity is small, natural convection restrains the melting behavior of paraffin.

A flexible lag definition for experimental variogram calculation

Inferring the experimental variogram used in geostatistics commonly relies on the method-of-moments approach.Ideally,the available data-set used for calculating the experimental variogram should be drawn from a regular pattern.However,in practice the available data-set is typically sampled over a sparse pattern at irregularly spaced locations.Hence,some binning of the variogram cloud is required to obtain fair estimates of the experimental variogram.Grouping of the variogram data pairs as a result of conventional binning depends on parameters such as the main anisotropic directions and a regular definition of the lag vectors.These parameters are not based on the configuration of the variogram data pairs in the variogram cloud but on a segment of it that is arbitrarily predefined.Therefore,the conventional experimental variogram estimation approach is biased because of the strict configuration of the bins over the variogram cloud.In this paper,a new method of estimating experimental variograms is proposed.Lag vectors and their tolerances are decided in the proposed method from information in the variogram cloud：they are not influenced by any predefined directions.The proposed methodology is a well-founded,practicable and easy-to-automate approach for experimental variogram calculation using an irregularly sampled data-set.Comparison of results from the new method to those from the traditional approach is very encouraging.

New self-calibration approach to space robots based on hand-eye vision

To overcome the influence of on-orbit extreme temperature environment on the tool pose(position and orientation) accuracy of a space robot,a new self-calibration method based on a measurement camera(hand-eye vision) attached to its end-effector was presented.Using the relative pose errors between the two adjacent calibration positions of the space robot,the cost function of the calibration was built,which was different from the conventional calibration method.The particle swarm optimization algorithm(PSO) was used to optimize the function to realize the geometrical parameter identification of the space robot.The above calibration method was carried out through self-calibration simulation of a six-DOF space robot whose end-effector was equipped with hand-eye vision.The results showed that after calibration there was a significant improvement of tool pose accuracy in a set of independent reference positions,which verified the feasibility of the method.At the same time,because it was unnecessary for this method to know the transformation matrix from the robot base to the calibration plate,it reduced the complexity of calibration model and shortened the error propagation chain,which benefited to improve the calibration accuracy.

Estimation of Design Sea Ice Thickness with Maximum Entropy Distribution by Particle Swarm Optimization Method

The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.