Inversion of Travel Times in Weakly Anisotropic Rock Samples

Based on the perturbation theory, inversion formulae for travel time of qP and qS waves in arbitrary weak anisotropy media are presented. The inversion formulae are linear expressions of elastic parameters expressed in terms of weak anisotropy (WA) parameters. The formulae of qS₁ and qS₂ waves have the same form and they can be used without identifying which wave is considered. A synthetic experiment similar to the measurement of rock sample in the laboratory is carried out to illustrate the efficiency of the presented inversion formulae. Two data sets for qP wave travel time from rock samples in the laboratory are inverted and 15 WA parameters are obtained.     

A spectroscopic orbit for 26 Comae

Photoelectric radial-velocity measurements show that 26 Comae is a spectroscopic binary with a very eccentric orbit and a period of 972 days. An erratum to this article is available at .     

苏北东部海域辐射沙洲研究的新思路

苏北东部海域辐射沙洲以往仅侧重于外动力方面的研究，这里提出开展内动力与外动力同步研究的新思路，指出两者的结合点是旋扭运动，要在以往外动力研究的基础上，加强地震震中研究、地形变监测、地应力实测等方面内容，以确定该区不同层圈、不同介质条件下是否存在同一的旋扭运动。上述思路的实施，有利于地理学与地质学研究的沟通和溶合，同时提出地震往往伴随旋扭现象的事实，丰富了地震学的研究内容，其研究成果将为多方面的开发辐射沙洲提供基础资料。     

径向基函数网络在云检测中的应用

作者提出一种应用径向基函数网络 (RBF)的云检测方法。此方法要求晴空海域与有云海域均以一定数量的基函数来表征 ,两种基函数可组成一个径向基函数网络。使用欧空局沿轨道扫描辐射计 (ERS- 1/ ATSR)资料对径向基函数网络在云检测中的性能作了验证 ,重点研究网络结构的复杂度对分类结果的影响 ,并与人眼的目视解译作比较 ,结果表明径向基函数网络在云检测中性能良好。     

Microcoring and dendrometer-detected intra-annual wood formation of Populus euphratica in the Ejina Oasis,northwestern China

Seasonal stem radial growth and wood formation of trees have become research hotspots because of their significance for dendroclimatological and dendroecological studies. However, until recently, these studies concentrated on coniferous tree species in high-altitude and high-latitude regions, while detailed information on arid-zone riparian forests is scarce. The main focus of this study is to monitor the intra-annual dynamics of radial growth and tree ring formation in a deciduous species, Populus euphratica. In 2013, we combined the dendrometer and microcoring methods to study this species in the riparian forest of the Ejina Oasis, in arid northwestern China. Vessel enlargement began in early May, and the maximum rate of cell production occurred in early June. The cell division then ceased from early to mid-July. The dendrometer method failed to reliably detect the date of growth initiation and cessation, but succeeded to detect the time of maximum growth rate just like the microcoring method did. We found that weekly stem radial increment data described xylem growth more accurately than daily datasets. Based on correlation analysis among climatic and hydrologic variables, and weekly stem radial increment, weekly ring width increase dataset, the depth to groundwater was the main factor that limited tree ring growth. From a practical perspective, such studies of intra-annual wood formation can provide empirical guidance for seasonal water allocations within a river basin.     

Geographically weighted regression with parameter-specific distance metrics

Geographically weighted regression (GWR) is an important local technique to model spatially varying relationships. A single distance metric (Euclidean or non-Euclidean) is generally used to calibrate a standard GWR model. However, variations in spatial relationships within a GWR model might also vary in intensity with respect to location and direction. This assertion has led to extensions of the standard GWR model to mixed (or semiparametric) GWR and to flexible bandwidth GWR models. In this article, we present a strongly related extension in fitting a GWR model with parameter-specific distance metrics (PSDM GWR). As with mixed and flexible bandwidth GWR models, a back-fitting algorithm is used for the calibration of the PSDM GWR model. The value of this new GWR model is demonstrated using a London house price data set as a case study. The results indicate that the PSDM GWR model can clearly improve the model calibration in terms of both goodness of fit and prediction accuracy, in contrast to the model fits when only one metric is singly used. Moreover, the PSDM GWR model provides added value in understanding how a regression model’s relationships may vary at different spatial scales, according to the bandwidths and distance metrics selected. PSDM GWR deals with spatial heterogeneities in data relationships in a general way, although questions remain on its model diagnostics, distance metric specification, and computational efficiency, providing options for further research.     

Numerical study on stress states and fabric anisotropies in soilbags using the DEM

Wrapping granular soils in geosynthetic containers, such as soilbags, results in a considerable increase in the bearing capacity due to the effective restraint on the dilatancy of the soil. This paper numerically investigates the stress states and fabric anisotropies in the wrapped soil using the discrete element method, providing a novel perspective for new insights into the reinforcement mechanisms and the development of constitutive relations for soilbags. The two most anticipated loading conditions, namely, unconfined compression and simple shear, are considered, and numerical predictions are compared to experimental results. During unconfined compression, both global and local p–q stress paths evolve linearly, having the same slope until the global failure of the wrapping geosynthetic. Under simple shear, the global stress path approaches the critical state line first and then turns to the compression line of the wrapped soil. Some local loading–unloading stress paths are observed, which may account for the high damping of soilbags during cyclic shear. The reduced fabric anisotropies of the normal and tangential force chains suggest greater confinement from the lateral sides of the geosynthetic container in either loading course. The performance and mechanisms of the soilbag earth reinforcement method, i.e., confinement and interlocking, can be better understood based on these new findings on the stress states and fabric anisotropies.     

Quantification of Aperture and Relations Between Aperture,Normal Stress and Fluid Flow for Natural Single Rock Fractures

Accurate quantification of rock fracture aperture is important in investigating hydro-mechanical properties of rock fractures. Liquefied wood’s metal was used successfully to determine the spatial distribution of aperture with normal stress for natural single rock fractures. A modified 3D box counting method is developed and applied to quantify the spatial variation of rock fracture aperture with normal stress. New functional relations are developed for the following list: (a) Aperture fractal dimension versus effective normal stress; (b) Aperture fractal dimension versus mean aperture; (c) Fluid flow rate per unit hydraulic gradient per unit width versus mean aperture; (d) Fluid flow rate per unit hydraulic gradient per unit width versus aperture fractal dimension. The aperture fractal dimension was found to be a better parameter than mean aperture to correlate to fluid flow rate of natural single rock fractures. A highly refined variogram technique is used to investigate possible existence of aperture anisotropy. It was observed that the scale dependent fractal parameter, K _v, plays a more prominent role than the fractal dimension, D _a1d, on determining the anisotropy pattern of aperture data. A combined factor that represents both D _a1d and K _v, D _a1d × K _v, is suggested to capture the aperture anisotropy.     

3D Property Modeling of Void Ratio by Cokriging

Void ratio measures compactness of ground soil in geotechnical engineering. When samples are collected in certain area for mapping void ratios, other relevant types of properties such as water content may be also analyzed. To map the spatial distribution of void ratio in the area based on these types of point, observation data interpolation is often needed. Owing to the variance of sampling density along the horizontal and vertical directions, special consideration is required to handle anisotropy of estimator. 3D property modeling aims at predicting the overall distribution of property values from limited samples, and geostatistical method can he employed naturally here because they help to minimize the mean square error of estimation. To construct 3D property model of void ratio, cokriging was used considering its mutual correlation with water content, which is another important soil parameter. Moreover, K-D tree was adopted to organize the samples to accelerate neighbor query in 3D space during the above modeling process. At last, spatial configuration of void ratio distribution in an engineering body was modeled through 3D visualization, which provides important information for civil engineering purpose.