UNIVERSALITY OF THE LAGRANGIAN VELOCITY STRUCTURE FUNCTION CONSTANT (C0) ACROSS DIFFERENT KINDS OF TURBULENCE

In this paper, we evaluate the Lagrangian velocity structure function constant, C0, in the inertial subrange by comparing experimental diffusion data and simulation results obtained with applicable Lagrangian stochastic models. We find in several different flows (grid turbulence, laboratory boundary-layer flow and the atmospheric surface layer under neutral stratification) the value for C0 is 3.0 ± 0.5. We also identify the reasons responsible for earlier studies having not reached the present result.     

用非线性遗传反演方法进行自动静校正

静校正处理是消除近地层影响的一个重要地震资料数字处理方法，在近地表层纵，横向变化复杂，静校正量变化较大的地区，常规静校正方法和线性反演方法均不能解决问题，遗传算法是近年发展起来的一种模拟生物生化过程的较先进的非线性反演方法，对用遗传算法进行静校正的若干问题进行了讨论，说明它是可以解决表层情况复杂地区静校正问题的一个有效方法。     

Dynamic stochastic estimation of physical variables

A fundamental problem facing the physical sciences today is analysis of natural variations and mapping of spatiotemporal processes. Detailed maps describing the space/time distribution of groundwater contaminants, atmospheric pollutant deposition processes, rainfall intensity variables, external intermittency functions, etc. are tools whose importance in practical applications cannot be overestimated. Such maps are valuable inputs for numerous applications including, for example, solute transport, storm modeling, turbulent-nonturbulent flow characterization, weather prediction, and human exposure to hazardous substances. The approach considered here uses the spatiotemporal random field theory to study natural space/time variations and derive dynamic stochastic estimates of physical variables. The random field model is constructed in a space/time continuum that explicitly involves both spatial and temporal aspects and provides a rigorous representation of spatiotemporal variabilities and uncertainties. This has considerable advantages as regards analytical investigations of natural processes. The model is used to study natural space/time variations of springwater calcium ion data from the Dyle River catchment area, Belgium. This dataset is characterized by a spatially nonhomogeneous and temporally nonstationary variability that is quantified by random field parameters, such as orders of space/time continuity and random field increments. A rich class of covariance models is determined from the properties of the random field increments. The analysis leads to maps of continuity orders and covariances reflecting space/time calcium ion correlations and trends. Calcium ion estimates and the associated statistical errors are calculated at unmeasured locations/instants over the Dyle region using a space/time kriging algorithm. In practice, the interpretation of the results of the dynamic stochastic analysis should take into consideration the scale effects.     

隧道支护结构荷载作用的随机反演

提出荷载－结构模式进行随机反分析方法，从隧道支护结构变形反算对应的荷载作用，可反推围岩抗力系数和覆土荷载的分布情况，以及作用于支护结构上各部位的外荷载。提出了以实测位移为基础的样条函数插值．以插值位移补充大量的实测值，满足了反分析所需众多的已知位移数。通过一施工实例对该方法的可行性进行了检验。     

论广义逆矩阵阶数增大的递推算法

本文针对加拿大地球物理学家ＥｄｏＮｇｌａｎｄ教授提出的问题，对Ｍ—Ｐ广义逆矩阵的递推算法进行了探分论述探讨的初步结果和对Ｇｒｅｖｉｌｌｅ递推算法的扩充。文中对算法的扩充给出严格的证明。     

层析成像中的波形反演

在波动方程有限差分数值模拟基础上，用波形记录残差平方并建立目标函数。对目标函数进行梯度优化，我们得出了介质速度的迭代公式。通过计算目标函数梯度我们可以对介质进行速度校正，从而获得反演解。经数值试验证明这是一种很有效的反演方法。     

地球物理反问题中的随机反演理论

本文从最大后验概率密度观点出发，在数据噪音向量和待求模型向量为具有零均值的独立高斯随机过程的假设前提下，建立起了随机反演的非线性系统方程；给出了模型方差估计的函数表达式，并在文章最后，证明了反演解的稀疏性，即解释了随机反演的输出解的高分辨率特征。文章在最小二乘反演方法的基础上，发展并完善了随机反演方法的理论基础；揭示了随机反演方法与最小二乘反演方法之间的本质区别；阐述了随机反演方法的优越性，并指出了其广阔的应用前景。     

Simulation of normal distributed smooth fields by Karhunen-Loéve expansion in combination with kriging

Simulation of multigaussian stochastic fields can be made after a Karhunen-Loéve expansion of a given covariance function. This method is also called simulation by Empirical Orthogonal Functions. The simulations are made by drawing stochastic coefficients from a random generator. These numbers are multiplied with eigenfunctions and eigenvalues derived from the predefined covariance model. The number of eigenfunctions necessary to reproduce the stochastic process within a predefined variance error, turns out to be a cardinal question. Some ordinary analytical covariance functions are used to evaluate how quickly the series of eigenfunctions can be truncated. This analysis demonstrates extremely quick convergence to 99.5% of total variance for the 2nd order exponential (‘gaussian’) covariance function, while the opposite is true for the 1st order exponential covariance function. Due to these convergence characteristics, the Karhunen-Loéve method is most suitable for simulating smooth fields with ‘gaussian’ shaped covariance functions. Practical applications of Karhunen-Loéve simulations can be improved by spatial interpolation of the eigenfunctions. In this paper, we suggest interpolation by kriging and limits for reproduction of the predefined covariance functions are evaluated.     

GPS Ambiguity Resolution: Impact of Time Correlation,Cross-Correlation and Satellite Elevation Dependence

In this contribution we discuss the geometry-free GPS single baseline model and show how the least-squares ambiguities are affected by changes in the stochastic model. We particularly pay attention to the effect of time correlation, cross-correlation and satellite elevation dependence. We also differentiate between the impact on the location of the ambiguity search space and the impact on the size and shape of the search space. The analysis is carried out for both the model in which the ionospheric delays are assumed absent, and for the model in which they are assumed present. The former model is applicable to short baselines only.