Stress intensity factors calculation in anti-plane fracture problem by orthogonal integral extraction method based on femol

For an anti-plane problem, the differential operator is self-adjoint and the corresponding eigenfunctions belong to the Hilbert space. The orthogonal property between eigenfunctions (or between the derivatives of eigenfunctions) of anti-plane problem is exploited. We developed for the first time two sets of radius-independent orthogonal integrals for extraction of stress intensity factors (SIFs), so any order SIF can be extracted based on a certain known solution of displacement (an analytic result or a numerical result). Many numerical examples based on the finite element method of lines (FEMOL) show that the present method is very powerful and efficient.

平面上旋转充液腔体稳定性问题的谱分析及状态空间算子的势理论

本文对充满均匀粘性液体的旋转对称腔体在光滑水平面上的平衡旋转态附近的振动模,导出本征方程?φ=0,对算子?进行谱分析,给出各模及总体的稳定性结论。本文还将Hilbert空间的算子势论推广到充液腔的复空间,给出与?相关的势泛函,从而获得二条泛函微分定理。本文方法比伴随变分更具普遍性。

FORTRAN语言的非数值应用

<正> 1.系统设计 利用高速计算机,进行微分方程公式的推导是数学研究工作的一个新的尝试,它将影响今后微分方程研究工作的现代化。 微分方程程序系统(Differential Equation Program System,简称DEPS)的主要用途是

Stress-distribution around a rigid line in dissimilar media

The elastic plane problem of a rigid line inclusion between two dissimilar media was considered. By solving the Riemann-Hilbert problem, the closed-form solution was obtained and the stress distribution around the rigid line was investigated. It was found that the modulus of the singular behavior of the stress remains proportional to the inverse square root of the distance from the rigid line end, but the stresses possess a pronounced oscillatory character as in the case of an interfacial crack tip.

Digits speech recognition based on geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems.We observe that this may be true for a recognition tasks based on geometrical learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions via the Hilbert transform. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy, Experiments show method based on ICA and geometrical learning outperforms HMM in different number of train samples.

Optimized logarithmic phase masks used to generate defocus invariant modulation transfer function for wavefront coding system

In a previous Letter [Opt. Lett. 33, 1171 (2008)], we proposed an improved logarithmic phase mask by making modifications to the original one designed by Sherif. However, further studies in another paper [Appl. Opt. 49, 229 (2010)] show that even when the Sherif mask and the improved one are optimized, their corresponding defocused modulation transfer functions (MTFs) are still not stable with respect to focus errors. So, by further modifying their phase profiles, we design another two logarithmic phase masks that exhibit more stable defocused MTF. However, with the defocus-induced phase effect considered, we find that the performance of the two masks proposed in this Letter is better than the Sherif mask, but worse than our previously proposed phase mask, according to the Hilbert space angle. (C) 2010 Optical Society of America

Crossing the phantom divide in brane cosmology with curvature corrections and brane-bulk energy transfer

We consider the Randall-Sundrum brane-world model with bulk-brane energy transfer where the Einstein-Hilbert action is modified by curvature correction terms: a four-dimensional scalar curvature from induced gravity on the brane, and a five-dimensional Gauss-Bonnet curvature term. It is remarkable that these curvature terms will not change the dynamics of the brane universe at low energy. Parameterizing the energy transfer and taking the dark radiation term into account, we find that the phantom divide of the equation of state of effective dark energy could be crossed, without the need of any new dark energy components. Fitting the two most reliable and robust SNIa datasets, the 182 Gold dataset and the Supernova Legacy Survey (SNLS), our model indeed has a small tendency of phantom divide crossing for the Gold dataset, but not for the SNLS dataset. Furthermore, combining the recent detection of the SDSS baryon acoustic oscillations peak (BAO) with lower matter density parameter prior, we find that the SNLS dataset also mildly favors phantom divide crossing.

多尺度分解与相位反褶积提高海上地震资料分辨率和信噪比

Offshore seismic exploration is full of high investment and risk. And there are many problems, such as multiple. The technology of high resolution and high S/N ratio on marine seismic data processing is becoming an important project. In this paper, the technology of multi-scale decomposition on both prestack and poststack seismic data based on wavelet and Hilbert-Huang transform and the theory of phase deconvolution is proposed by analysis of marine seismic exploration, investigation and study of literatures, and integration of current mainstream and emerging technology. Related algorithms are studied. The Pyramid algorithm of decomposition and reconstruction had been given by the Mallat algorithm of discrete wavelet transform In this paper, it is introduced into seismic data processing, the validity is shown by test with field data. The main idea of Hilbert-Huang transform is the empirical mode decomposition with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions that admit well-behaved Hilbert transform. After the decomposition, a analytical signal is constructed by Hilbert transform, from which the instantaneous frequency and amplitude can be obtained. And then, Hilbert spectrum. This decomposition method is adaptive and highly efficient. Since the decomposition is based on the local characteristics of the time scale of data, it is applicable to nonlinear and non-stationary processes. The phenomenons of fitting overshoot and undershoot and end swings are analyzed in Hilbert-Huang transform. And these phenomenons are eliminated by effective method which is studied in the paper. The technology of multi-scale decomposition on both prestack and poststack seismic data can realize the amplitude preserved processing, enhance the seismic data resolution greatly, and overcome the problem that different frequency components can not restore amplitude properly uniformly in the conventional method. The method of phase deconvolution, which has overcome the minimum phase limitation in traditional deconvolution, approached the base fact well that the seismic wavelet is phase mixed in practical application. And a more reliable result will be given by this method. In the applied research, the high resolution relative amplitude preserved processing result has been obtained by careful analysis and research with the application of the methods mentioned above in seismic data processing in four different target areas of China Sea. Finally, a set of processing flow and method system was formed in the paper, which has been carried on in the application in the actual production process and has made the good progress and the huge economic benefit.

反假频重建理论及其在储层预测中的应用

To extend the cross-hole seismic 2D data to outside 3D seismic data, reconstructing the low frequency data to high frequency data is necessary. Blind deconvolution method is a key technology. In this paper, an implementation of Blind deconvolution is introduced. And optimized precondition conjugate gradient method is used to improve the stability of the algorithm and reduce the computation. Then high-frequency retrieved Seismic data and the cross-hole seismic data is combined for constraint inversion. Real data processing proved the method is effective. To solve the problem that the seismic data resolution can’t meet the request of reservoir prediction in the river face thin-layers in Chinese eastern oil fields, a high frequency data reconstruction method is proposed. The extrema of the seismic data are used to get the modulation function which operated with the original seismic data to get the high frequency part of the reconstruction data to rebuild the wide band data. This method greatly saves the computation, and easy to adjust the parameters. In the output profile, the original features of the seismic events are kept, the common feint that breaking the events and adding new zeros to produce alias is avoided. And the interbeded details are enhanced compared to the original profiles. The effective band of seismic data is expended and the method is approved by the processing of the field data. Aim to the problem in the exploration and development of Chinese eastern oil field that the high frequency log data and the relative low frequency seismic data can’t be merged, a workflow of log data extrapolation constrained by time-phase model based on local wave decomposition is raised. The seismic instantaneous phase is resolved by local wave decomposition to build time-phase model, the layers beside the well is matched to build the relation of log and seismic data, multiple log info is extrapolated constrained by seismic equiphase map, high precision attributes inverse sections are produced. In the course of resolve the instantaneous phase, a new method of local wave decomposition --Hilbert transform mean mode decomposition(HMMD) is raised to improve the computation speed and noise immunity. The method is applied in the high resolution reservoir prediction in Mao2 survey of Daqing oil field, Multiple attributes profiles of wave impedance, gamma-ray, electrical resistivity, sand membership degree are produced, of which the resolution is high and the horizontal continuous is good. It’s proved to be a effective method for reservoir prediction and estimation.

数据驱动型多次波衰减方法的研究

In the practical seismic profile multiple reflections tend to impede the task of even the experienced interpreter in deducing information from the reflection data. Surface multiples are usually much stronger, more broadband, and more of a problem than internal multiples because the reflection coefficient at the water surface is much larger than the reflection coefficients found in the subsurface. For this reason most attempts to remove multiples from marine data focus on surface multiples, as will I. A surface-related multiple attenuation method can be formulated as an iterative procedure. In this essay a fully data-driven approach which is called MPI —multiple prediction through inversion (Wang, 2003) is applied to a real marine seismic data example. This is a pretty promising scheme for predicting a relative accurate multiple model by updating the multiple model iteratively, as we usually do in a linearized inverse problem. The prominent characteristic of MPI method lie in that it eliminate the need for an explicit surface operator which means it can model the multiple wavefield without any knowledge of surface and subsurface structures even a source signature. Another key feature of this scheme is that it can predict multiples not only in time but also in phase and in amplitude domain. According to the real data experiments it is shown that this scheme for multiple prediction can be made very efficient if a good initial estimate of the multiple-free data set can be provided in the first iteration. In the other core step which is multiple subtraction we use an expanded multi-channel matching filter to fulfil this aim. Compared to a normal multichannel matching filter where an original seismic trace is matched by a group of multiple-model traces, in EMCM filter a seismic trace is matched by not only a group of the ordinary multiple-model traces but also their adjoints generated mathematically. The adjoints of a multiple-model trace include its first derivative, its Hilbert transform and the derivative of the Hilbert transform. The third chapter of the thesis is the application for the real data using the previous methods we put forward from which we can obviously find the effectivity and prospect of the value in use. For this specific case I have done three group experiments to test the effectiveness of MPI method, compare different subtraction results with fixed filter length but different window length, invest the influence of the initial subtraction result for MPI method. In terms of the real data application, we do fine that the initial demultiple estimate take on a great deal of influence for the MPI method. Then two approaches are introduced to refine the intial demultiple estimate which are first arrival and masking filter respectively. In the last part some conclusions are drawn in terms of the previous results I have got.

中高层大气对低层大气声重波响应的分析

Acoustic Gravity waves (AGW) play an important role in balancing the atmospheric energy and momentum budget. Propagation of gravity wave in the atmosphere is one of the important factors of changing middle and upper atmosphere and ionosphere. The purpose of this dissertation is to study the propagation of gravity wave in a compression atmosphere whit means of numerical simulation and to analyze the response of middle and upper atmosphere to pulse disturbance from lower atmosphere. This work begins with the establishment of 2-D fully nonlinear compressible atmospheric dynamic model in polar coordinate, which is used ton numerically study gravity wave propagation. Then the propagation characteristics of acoustic gravity wave packets are investigated and discussed. We also simulate the response of middle and upper atmosphere to pulse disturbance of lower atmosphere in background winds or without background winds by using this model and analyze the data we obtained by using Fourier Transform (FT), Short-time Fourier Transform (STFT) and Empirical Mode Decomposition (EMD) method which is an important part of Hilbert-Huang Transform (HHT). The research content is summarized in the following: 1. By using a two-dimensional full-implicit-continuous-Eulerian (FICE) scheme and taking the atmospheric basic motion equations as the governing equations, a numerical model for nonlinear propagation of acoustic gravity wave disturbance in two-dimensional polar coordinates is solved. 2. Then the propagation characteristics of acoustic gravity wave packets are investigated and discussed. Results of numerical simulation show that the acoustic gravity wave packets propagate steadily upward and keep its shape well after several periods. 3. We simulate the response of middle and upper atmosphere to pulse disturbance of lower atmosphere in background winds or without background winds by using this model, and obtain the distribution of a certain physical quantity in time and space from earth’s surface to 300km above. The results reveal that the response of ionosphere occurs at a large horizontal distance from the source and the disturbance becomes greater with increasing of height. The situation when the direction of the background wind is opposite to or the same as the direction of disturbed velocity of gravity-wave is studied. The results show that gravity wave propagating against winds is easier than those propagating along winds and the background wind can accelerate gravity wave propagation. Just upon the source, an acoustic wave component with period of 6 min can be found. These images of simulation are similar to observations of the total electron content (TEC) disturbances caused by the great Sumatra-Andaman earthquake on December 26 in 2004. 4. Using the EMD method the disturbed velocity data of a certain physical quantity in time and space can be decomposed into a series of intrinsic mode function (IMF) and a trend mode respectively. The results of EMD reveal impact of the gravity wave frequency under the background winds.

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.

小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.