基于分离迭代和耦合时变的列车—轨道—桥梁耦合系统高效动力分析混合算法

为提高列车—轨道—桥梁耦合系统动力分析的计算效率,基于耦合时变法及分离迭代法,提出了1种混合算法。该算法将列车—轨道—桥梁耦合系统分解为车辆—轨道子系统和桥梁子系统。其中,车辆—轨道子系统在每一时间步需根据车辆位置对系统刚度系数矩阵进行更新,具有时变的特性;桥梁子系统的系统动力系数矩阵在整个动力分析过程中保持不变;车辆—轨道子系统与桥梁子系统通过钢轨与桥梁间作用力的平衡迭代实现耦合。利用朔黄重载铁路32m简支梁桥现场试验数据与由混合算法计算得到的分析结果进行对比,验证了混合算法的可行性。采用耦合时变法和混合算法分别计算列车通过蒙华重载铁路黄河龙门大桥的动力响应,结果表明:采用相同的时间积分步长时,2种方法拥有相同的计算精度,但混合算法比耦合时变法具有更高的计算效率,求解耗时降低了75%。

高耸结构调谐质量阻尼器附加有效阻尼比的计算方法研究

为研究高耸结构TMD附加有效阻尼比计算方法的适用性,建立了设置TMD和不设置TMD的某高耸结构ETABS模型,采用规范法、时变法、自由衰减法分别计算了TMD的附加有效阻尼比,并开展了振动台试验,根据试验结果得到了TMD的附加有效阻尼比。研究结果表明:评估高耸结构TMD的附加有效阻尼比时,计算方法可以采用时变法、自由衰减法;振动台试验法得到的附加有效阻尼比较为可靠,建议开展振动台试验进行验证。

磁场强度对日冕定态结构的影响

以二维ＭＨＤ模型及时变方法为基础，内外边界采用完整的投影特征线边界条件，考察了太阳日冕大气的定态结构随偶极场强度的变化情况．模拟结果表明：随着偶极场强度的增加，磁场对太阳风的约束增强，低纬闭磁场打开程度减小，高纬与低纬区速度差增加，并且在阿尔文马赫数为１的点附近达到最大，速度过度区变陡；随着日心距离增加，低纬区宽度减小，速度过渡区变陡，可定性解释Ｕｌｙｓｓｅｓ飞船的新观测事实．

COMPENSATION CONTROL OF REAL-TIME UNBALANCE FORCE FOR ACTIVE MAGNETIC BEARING SYSTEM

Aiming at the stability and others properties of active magnetic bearing （AMB） system influenced by the periodic unbalance stimulation synchronous with rotor rotational speed, a new real-time adaptive feed-forward unbalance force compensation scheme is proposed based on variable step-size least mean square（LMS） algorithm as the feed-forward compensation controller. The controller can provide some suitable sinusoidal signals to com- pensate the feedback unbalance response signals synchronous with the rotary frequency, then reduce the fluctua- tion of the control currents and weaken the active control of AMB system. The variable step-size proportional to the rotational frequency is deduced by analyzing the principle of normal LMS algorithm and its deficiency in the application of real-time filtering of AMB system. Experimental results show that the new method can implement real-time unbalance force compensation in a wide frequency band, reduce the effect of unbalance stimulant force on the housing of AMB system, and provide convenience to improve rotational speed.

A novel particle swarm optimizer without velocity:Simplex-PSO

A simplex particle swarm optimization(simplex-PSO) derived from the Nelder-Mead simplex method was proposed to optimize the high dimensionality functions.In simplex-PSO,the velocity term was abandoned and its reference objectives were the best particle and the centroid of all particles except the best particle.The convergence theorems of linear time-varying discrete system proved that simplex-PSO is of consistent asymptotic convergence.In order to reduce the probability of trapping into a local optimal value,an extremum mutation was introduced into simplex-PSO and simplex-PSO-t(simplex-PSO with turbulence) was devised.Several experiments were carried out to verify the validity of simplex-PSO and simplex-PSO-t,and the experimental results confirmed the conclusions:(1) simplex-PSO-t can optimize high-dimension functions with 200-dimensionality;(2) compared PSO with chaos PSO(CPSO),the best optimum index increases by a factor of 1×102-1×104.

Time-variant reliability analysis of three-dimensional slopes based on Support Vector Machine method

In the reliability analysis of slope, the performance functions derived from the most available stability analysis procedures of slopes are usually implicit and cannot be solved by first-order second-moment approach. A new reliability analysis approach was presented based on three-dimensional Morgenstem-Price method to investigate three-dimensional effect of landslide in stability analyses. To obtain the reliability index, Support Vector Machine （SVM） was applied to approximate the performance function. The time-consuming of this approach is only 0.028% of that using Monte-Carlo method at the same computation accuracy. Also, the influence of time effect of shearing strength parameters of slope soils on the long-term reliability of three-dimensional slopes was investigated by this new approach. It is found that the reliability index of the slope would decrease by 52.54% and the failure probability would increase from 0.000 705% to 1.966%. In the end, the impact of variation coefficients of c andfon reliability index of slopes was taken into discussion and the changing trend was observed.

An Explicit-Implicit Predictor-Corrector Domain Decomposition Method for Time Dependent Multi-Dimensional Convection Diffusion Equations

The numerical solution of large scale multi-dimensional convection diffusion equations often requires efficient parallel algorithms.In this work,we consider the extension of a recently proposed non-overlapping domain decomposition method for two dimensional time dependent convection diffusion equations with variable coefficients. By combining predictor-corrector technique,modified upwind differences with explicitimplicit coupling,the method under consideration provides intrinsic parallelism while maintaining good stability and accuracy.Moreover,for multi-dimensional problems, the method can be readily implemented on a multi-processor system and does not have the limitation on the choice of subdomains required by some other similar predictor-corrector or stabilized schemes.These properties of the method are demonstrated in this work through both rigorous mathematical analysis and numerical experiments.

A Real-time Modeling of Photovoltaic Array

This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.

A novel method to predict static transmission error for spur gear pair based on accuracy grade

This paper proposes a novel method to predict the spur gear pair’s static transmission error based on the accuracy grade,in which manufacturing errors(MEs),assembly errors(AEs),tooth deflections(TDs)and profile modifications(PMs)are considered.For the prediction,a discrete gear model for generating the error tooth profile based on the ISO accuracy grade is presented.Then,the gear model and a tooth deflection model for calculating the tooth compliance on gear meshing are coupled with the transmission error model to make the prediction by checking the interference status between gear and pinion.The prediction method is validated by comparison with the experimental results from the literature,and a set of cases are simulated to study the effects of MEs,AEs,TDs and PMs on the static transmission error.In addition,the time-varying backlash caused by both MEs and AEs,and the contact ratio under load conditions are also investigated.The results show that the novel method can effectively predict the range of the static transmission error under different accuracy grades.The prediction results can provide references for the selection of gear design parameters and the optimization of transmission performance in the design stage of gear systems.

Optimizing bus services with variable directional and temporal demand using genetic algorithm

As a major mode choice of commuters for daily travel, bus transit plays an important role in many urban and metropolitan areas. This work proposes a mathematical model to optimize bus service by minimizing total cost and considering a temporally and directionally variable demand. An integrated bus service, consisting of all-stop and stop-skipping services is proposed and optimized subject to directional frequency conservation, capacity and operable fleet size constraints. Since the research problem is a combinatorial optimization problem, a genetic algorithm is developed to search for the optimal result in a large solution space. The model was successfully implemented on a bus transit route in the City of Chengdu, China, and the optimal solution was proved to be better than the original operation in terms of total cost. The sensitivity of model parameters to some key attributes/variables is analyzed and discussed to explore further the potential of accruing additional benefits or avoiding some of the drawbacks of stop-skipping services.

Effect of a novel three-step aging on strength, stress corrosion cracking and microstructure of AA7085

The influence of a novel three-step aging on strength, stress corrosion cracking(SCC) and microstructure of AA7085 was investigated by tensile testing and slow strain rate testing combined with transmission electron microscopy(TEM). The results indicate that with the increase of second-step aging time of two-step aging, the mechanical properties increase first and then decrease, while the SCC resistance increases. Compared with two-step aging, three-step aging treatment improves SCC resistance and the strength increases by about 5%. The effects of novel three-step aging on strength and SCC resistance are explained by the role of matrix precipitates and grain boundary precipitates, respectively.

SUBSPACE METHOD FOR BLIND IDENTIFICATION OF CDMA TIME-VARYING CHANNELS

A new blind method is proposed for identification of CDMA Time-Varying (TV)channels in this paper. By representing the TV channel's impulse responses in the delay-Doppler spread domain, the discrete-time canonical model of CDMA-TV systems is developed and a subspace method to identify blindly the Time-Invariant (TI) coordinates is proposed. Unlike existing basis expansion methods, this new algorithm does not require .estimation of the base frequencies, neither need the assumption of linearly varying delays across symbols. The algorithm offers definite explanation of the expansion coordinates. Simulation demonstrates the effectiveness of the algorithm.

Calculation and application of full-wave airborne transient electromagnetic data in electromagnetic detection

Airborne electromagnetic transient method enjoys the advantages of high-efficiency and the high resolution of electromagnetic anomalies,especially suitable for mining detection around goaf areas and deep exploration of minerals.In this paper,we calculated the full-wave airborne transient electromagnetic data,according to the result of numerical research,the advantage of switch-off time response in electromagnetic detection was proofed via experiments.Firstly,based on the full-wave airborne transient electromagnetic system developed by Jilin University(JLU-ATEMI),we proposed a method to compute the full-waveform electromagnetic(EM)data of 3D model using the FDTD approach and convolution algorithm,and verify the calculation by the response of homogenous half-space.Then,through comparison of switch-off-time response and off-time response,we studied the effect of ramp time on anomaly detection.Finally,we arranged two experimental electromagnetic detection,the results indicated that the switch-off-time response can reveal the shallow target more effectively,and the full-waveform airborne electromagnetic system is an effective technique for shallow target detection.

Algorithm study of transient response of vertical magnetic bipolar source in whole space plane layered medium

For some time, whole space feature as a theoretical problem has been a puzzle in mining transient electromagnetic method （TEM）. We have introduced a detailed method of calculating the transient response of a vertical magnetic bipolar source in a whole space plane layered medium in order to obtain whole space features. After designing a whole space plane layered medium model, equations were established based on boundary conditions in terms of electromagnetic vector potential. Expressions of electromagnetic fields were obtained by solving these equations. The expressions were computed by the Hankel transform after dispersion. The results in a frequency domain were changed into a time domain by using a multinomial cosine transform method. The expressions were correctly validated by comparing them with the analytical solution in half space. The half space and whole space results show that the whole space features are dear, suggesting that the theory of half space is not suitable for the whole space. Our algorithm supplied the technical instrument for studying the distributed features of whole space transient electromagnetic fields.

Separation of Variable Treatment for Solving Time—Dependent Potentials

We use the separation of variable treatment to treat some time-dependent systems, and point out that the condition of separability is the same as the condition of existence of invariant, and the separation of variable treatment is interrelated with the quantum-invariant method and the propagator method. We directly use the separation of variable treatment to obtain the wavefunctions of the time-dependent Coulomb potential and the time-dependent Hulthén potential.

Spectrum Allocation for Cognitive Radio Networks with Non-Deterministic Bandwidth of Spectrum Hole

The spectrum allocation for cognitive radio networks(CRNs) has received considerable studies under the assumption that the bandwidth of spectrum holes is static. However, in practice, the bandwidth of spectrum holes is time-varied due to primary user/secondary user(PU/SU) activity and mobility, which result in non-determinacy. This paper studies the spectrum allocation for CRNs with non-deterministic bandwidth of spectrum holes. We present a novel probability density function(PDF) through order statistics as well as its simplified form to describe the statistical properties of spectrum holes, with which a statistical spectrum allocation model based on stochastic multiple knapsack problem(MKP) is formulated for spectrum allocation with non-deterministic bandwidth of spectrum holes. To reduce the computational complexity, we transform this stochastic programming problem into a constant MKP through exploiting the properties of cumulative distribution function(CDF), which can be solved via MTHG algorithm by using auxiliary variables. Simulation results illustrate that the proposed statistical spectrum allocation algorithm can achieve better performance compared with the existing algorithms when the bandwidth of spectrum holes is time-varied.

Robust SLAM localization method based on improved variational Bayesian filtering

Aimed at the problem that the state estimation in the measurement update of the simultaneous localization and mapping(SLAM)method is incorrect or even not convergent because of the non-Gaussian measurement noise,outliers,or unknown and time-varying noise statistical characteristics,a robust SLAM method based on the improved variational Bayesian adaptive Kalman filtering(IVBAKF)is proposed.First,the measurement noise covariance is estimated using the variable Bayesian adaptive filtering algorithm.Then,the estimated covariance matrix is robustly processed through the weight function constructed in the form of a reweighted average.Finally,the system updates are iterated multiple times to further gradually correct the state estimation error.Furthermore,to observe features at different depths,a feature measurement model containing depth parameters is constructed.Experimental results show that when the measurement noise does not obey the Gaussian distribution and there are outliers in the measurement information,compared with the variational Bayesian adaptive SLAM method,the positioning accuracy of the proposed method is improved by 17.23%,20.46%,and 17.76%,which has better applicability and robustness to environmental disturbance.

Influence of Auxiliary Equation on Wave Functions for Time-Dependent Pauli Equation in Presence of Aharonov-Bohm Effect

Invariant operator method for discrete or continuous spectrum eigenvalue and unitary transformation approach are employed to study the two-dimensional time-dependent Pauli equation in presence of the Aharonov-Bohm effect （AB） and external scalar potential. For the spin particles the problem with the magnetic field is that it introduces a singularity into wave equation at the origin. A physical motivation is to replace the zero radius flux tube by one of radius R, with the additional condition that the magnetic field be confined to the surface of the tube, and then taking the limit R → 0 at the end of the computations. We point that the invariant operator must contain the step function θ（r - R）. Consequently, the problem becomes more complicated. In order to avoid this dimculty, we replace the radius R by ρ（t）R, where ρ（t） is a positive time-dependent function. Then at the end of calculations we take the limit R →0. The qualitative properties for the invariant operator spectrum are described separately for the different values of the parameter C appearing in the nonlinear auxiliary equation satisfied by p（t）, i.e., C 〉 0, C = 0, and C 〈0. Following the C＇s values the spectrum of quantum states is discrete （C 〉 0） or continuous （C ≤ 0）.

Calculation of all-time apparent resistivity of large loop transient electromagnetic method with very fast simulated annealing

In large loop transient electromagnetic method(TEM),the late time apparent resistivity formula cannot truly reflect the geoelectric model,thus it needs to define the all-time apparent resistivity with the position information of measuring point.Utilizing very fast simulated annealing(VFSA) to fit the theoretical electromagnetic force(EMF) and measured EMF could obtain the all-time apparent resistivity of the measuring points in rectangular transmitting loop.The selective cope of initial model of VFSA could be confirmed by taking the late time apparent resistivity of transient electromagnetic method as the prior information.For verifying the correctness,the all-time apparent resistivities of the geoelectric models were calculated by VFSA and dichotomy,respectively.The results indicate that the relative differences of apparent resistivities calculated by these two methods are within 3%.The change of measuring point position has little influence on the tracing pattern of all-time apparent resistivity.The first branch of the curve of all-time apparent resistivity is close to the resistivity of the first layer medium and the last branch is close to the resistivity of the last layer medium,which proves the correctness of the arithmetics proposed.

Assimilating Amounts of Precipitation Using a New Four-Dimensional Variational Method

Observations of accumulated precipitation are extremely valuable for effectively improving rainfall analysis and forecast. It is, however, difficult to use such observations directly through sequential assimilation methods, such as three-dimensional variational data assimilation or an Ensemble Kalman Filter. In this study, the authors illustrate a new approach that makes effective use of precipitation data to improve rainfall forecast. The new method directly obtains an optimal solution in a reduced space by fitting observations with historical time series generated by the model; it also avoids the implementation of tangent linear model and its adjoint. A lot of historical samples are produced as the ensemble of precipitation observations with the fully nonlinear forecast model. The results show that the new approach is capable of extracting information from precipitation observations to improve the analysis and forecast. This method provides comparable performance with the standard fourdimensional variational data assimilation at a much lower computational cost.