Recent Advances in Prediction and Processing of Strong Ground Motions

We present an overview of our recent results on utilizing small earthquakes in the earthquake engineering practice. Site-specific ground motion time-histories of large earthquakes can be successfully simulated using recordings of small earthquakes which are often referred to as 'empirical Green's functions' in seismology. Another important practical problem is whether and how these observations can be used in seismic risk studies which are based on empirical attenuation relations for ground motion parameters. We study a possibility of extrapolating attenuation relations for small earthquakes, to larger magnitudes using the data from the Garner Valley downhole array in Southern California. Finally we introduce efficient ground motion processing techniques in frequency- and time-domains and apply them to site response estimation.     

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.     

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.     

Determination of S-wave velocity structure using microtremors and spac method applied in Thessaloniki (Greece)

Array measurements of microtremors at 16 sites in the city of Thessaloniki were performed to estimate the V_s velocity of soil formations for site effect analysis. The spatial autocorrelation method was used to determine phase velocity dispersion curves in the frequency range from 0.8–1.5 to 6–7 Hz. A Rayleigh wave inversion technique (stochastic method) was subsequently applied to determine the Vs profiles at all the examined sites. The determination of V_s profiles reached a depth of 320 m. Comparisons with V_s values from cross-hole tests at the same sites proved the reliability of the SPAC method. The accuracy of the V_s profiles, the ability to reach large penetration depths in densely populated urban areas and its low cost compared to conventional geophysical prospecting, make Mictrotremor Exploration Method very attractive and useful for microzonation and site effects studies. An example of its application for the site characterization in Thessaloniki is presented herein.     

几种空气质量预报方法的预报效果对比分析

目前应用于我国各个城市空气质量预报业务的预报方法主要有三种 :数值模式预报、统计预报和综合经验预报。这几种预报方法都有其各自的优势 ,同时也存在一些不足。应用以上方法对天津市市区进行空气质量业务预报 ,通过实测资料与预报结果进行对比分析 ,给出这几种方法在天津市区空气质量预报中的预报效果客观评价。     

铝钛柱撑改性膨润土处理两种模拟废水的实验研究

以钠基膨润土为原料制备了铝钛无机柱撑、铝钛有机柱撑改性膨润土，确定了改性膨润土的最佳铝钛比和铝土比，并将其应用于模拟废水、化学实验室废水的处理。与原土进行比较，探讨了用量、pH值、搅拌时间等对COD去除率、色度去除率、浊度去除率的影响，通过正交实验对实验条件进行了优化。结果表明：有机柱撑改性膨润土、无机柱撑改性膨润土对废水的处理效果均明显好于原土，对废水色度、浊度的去除率均大于93％；对废水COD的去除效果，有机柱撑改性膨润土比无机柱撑改性膨润土有较大提高，去除率最高达66．31％，结果令人满意。     

Fitting the Linear Model of Coregionalization by Generalized Least Squares

In geostatistical studies, the fitting of the linear model of coregionalization (LMC) to direct and cross experimental semivariograms is usually performed with a weighted least-squares (WLS) procedure based on the number of pairs of observations at each lag. So far, no study has investigated the efficiency of other least-squares procedures, such as ordinary least squares (OLS), generalized least squares (GLS), and WLS with other weighing functions, in the context of the LMC. In this article, we compare the statistical properties of the sill estimators obtained with eight least-squares procedures for fitting the LMC: OLS, four WLS, and three GLS. The WLS procedures are based on approximations of the variance of semivariogram estimates at each distance lag. The GLS procedures use a variance–covariance matrix of semivariogram estimates that is (i) estimated using the fourth-order moments with sill estimates (GLS₁), (ii) calculated using the fourth-order moments with the theoretical sills (GLS₂), and (iii) based on an approximation using the correlation between semivariogram estimates in the case of spatial independence of the observations (GLS₃). The current algorithm for fitting the LMC by WLS while ensuring the positive semidefiniteness of sill matrix estimates is modified to include any least-squares procedure. A Monte Carlo study is performed for 16 scenarios corresponding to different combinations of the number of variables, number of spatial structures, values of ranges, and scale dependence of the correlations among variables. Simulation results show that the mean square error is accounted for mostly by the variance of the sill estimators instead of their squared bias. Overall, the estimated GLS₁ and theoretical GLS₂ are the most efficient, followed by the WLS procedure that is based on the number of pairs of observations and the average distance at each lag. On that basis, GLS₁ can be recommended for future studies using the LMC.     

Curve-Fitting Schemes for Fragmentation Data

Fragmentation measurements in the form of sieve passing and mass fraction data were used to test the capability of three different distributions to fit the observed data over a wide range in fragment size and mass. These distributions were based on Rosin-Rammler, lognormal and simple sigmoidal (S-shaped) functions, having 2 input parameters for the single-component versions and 5 input parameters for the two-component versions. Provided convergence was achieved in the non-linear curve-fitting technique, the two-component versions always provided superior fits to the observed data. However, these versions were very sensitive to variations in the values chosen for the input parameters. In this particular regard, the two-component sigmoidal function was the most robust. The present results also show that the two-component lognormal function provided the best fit to the fragmentation data in a general sense, and the two-component Rosin-Rammler function provided the worst fit. However, there was not a significant difference between any of the three methods.     

正交法在注浆材料优化设计中的应用

应用正交试验设计法，对粘土固化浆液的配比进行了优化，得到了最佳配比，并将其应用于洛湛铁路益娄段岩溶路基的注浆加固，收到了很好的整治效果。