Microtextural analysis of a glacially ‘deformed’ bedrock: implications for inheritance of preferred clast orientations in diamictons

Although analysis of clast macrofabrics has been used to differentiate between different types of glacial diamictons and to determine palaeo‐ice flow directions, no account appears to have been made of preferred clast orientations inherited from the parental source material. Clast macrofabrics in tills are typically interpreted as having developed in response to an imposed subglacial deformation and as such provide a link between the sedimentary record and glacier dynamics. They rely on the assumption that any preferred clast orientation is a result of deformation/flow. The results of the micromorphological study of the Langholm Till exposed at North Corbelly near Dumfries (southwestern Scotland) clearly demonstrate that bedrock structure can influence clast orientation (macrofabric) within diamictons. In the lower part of the till, the orientation of elongate clasts preserves the geometry of the tectonic cleavage present within the underlying bedrock. The intensity of this steeply inclined, ‘inherited’ clast fabric decreases upward through the till, to be replaced by a more complex pattern of successive generations of clast microfabrics developed in response to deformation/flow. These results indicate potential limitations of applying clast macrofabric or microfabric analysis in isolation to establish till genesis or palaeo ice‐flow directions. Consequently, due account should be made of other glacial palaeo‐environmental and ice flow indicators, as well as rockhead depth and morphology in relation to the selection of fabric measurements sites. © British Geological Survey/Natural Environment Research Council copyright 2007. Reproduced with the permission of BGS/NERC. Published by John Wiley & Sons, Ltd.     

Temperature evolution between 50 K and 320 K of the thermal expansion tensor of gypsum derived from neutron powder diffraction data

The unit cell parameters, extracted from Rietveld analysis of neutron powder diffraction data collected between 4.2 K and 320 K, have been used to calculate the temperature evolution of the thermal expansion tensor for gypsum for 50 ≤ T ≤ 320 K. At 300 K the magnitudes of the principal axes are α ₁₁  = 1.2(6) × 10⁻⁶ K⁻¹, α ₂₂  = 36.82(1) × 10⁻⁶ K⁻¹ and α ₃₃  = 25.1(5) × 10⁻⁶ K⁻¹. The maximum axis, α ₂₂ , is parallel to b, and using Institution of Radio Engineers (IRE) convention for the tensor orthonormal basis, the axes α ₁₁ and α ₃₃ have directions equal to (−0.979, 0, 0.201) and (0.201, 0, 0.979) respectively. The orientation and temperature dependent behaviour of the thermal expansion tensor is related to the crystal structure in the I2/a setting. Received 12 February 1998 / Revised, accepted 19 October 1998     

基于GPD分布的黑河流域极端降水频率特征分析

采用广义帕雷托分布(GPD)对黑河流域极端降水的频率特征进行了分析。采用百分位数法、Hill图法、年交叉率法选取了极端降水阈值,借助L矩法对GPD分布的参数进行了估计;采用Mann-Kendall和Pettitt方法对超阈值日极端降水序列的平稳性进行了检验。结果表明：① 采用百分位数法和Hill图法得到的日极端降水阈值差别很大,在综合考虑以上两种方法的基础上,结合年交叉率法,最终确定了流域各站点日极端降水的阈值;② 根据Mann-Kendall和Pettitt方法,超阈值日极端降水序列基本满足平稳性假定;通过Kolmogorov-Smirnov检验以及理论频率曲线和经验频率曲线的拟合程度可以看出,GPD分布能够很好地拟合研究区极端降水的分布特征;③ 通过分析理论累积频率达到90%以上的极端降水可以发现,黑河流域20世纪60年代发生极端降水的次数最多,其次是90年代以后,70年代、80年代发生极端降水次数较少;在过去51年间,下游发生极端降水的次数最多,其次是中游和上游。     

模糊层次综合评价在深埋隧道围岩质量分级中的应用

针对现行隧道围岩分类中存在的模糊性问题,引进模糊层次分析模型,实现了围岩定性分类向定量分类的转变,经过工程实践取得了良好的效果.首先确定了影响隧道围岩质量的主要因素,如岩块坚硬程度、结构面发育程度、岩石质量指标以及地下水出水特征,然后建立了模糊评价模型,并采用层次分析法确定了各因素的权重,最后针对堡镇铁路隧道围岩采用模糊层次综合评价决策的数学模型所得到的结果对隧道各段岩体质量的级别进行了划分.     

High-resolution cyclostratigraphy of geochemical records from Permo-Triassic boundary section of Dongpan, southwestern Guangxi, South China

Spectral analysis is applied to geochemical data from a deep-water Permian-Triassic Boundary (PTB) section across PTB in Dongpan, Guangxi for high-resolution cyclostratigraphic research. The characteristics of the Milankovitch Cycles have been well recorded in the strata of the Dongpan section. Spectrum on Ce/La records shows especially that the ratios among its three preponderant cycles in the section are 5:2:1, which well displays the phenomenon of the sedimentary cycles driven by orbital force. The Milankovitch theory is further confirmed by the Paleozoic records.     

欧亚地震带地震活动和中国大陆地震

欧亚地震带及其与中国大陆相邻地域的地震活动和中国大陆地震之间存在有多种相关关系，这些相关关系对预测中国大陆地震活动趋势有一定的作用     

傅里叶变换在深州井资料处理中的应用

深州井水位日常观测中,经常会因为仪器供电不稳、雷击等原因出现一些幅度很大的脉冲、突跳及数据缺测,严重影响了观测资料的内在质量。本文采用数字信号处理技术[1]对深州井水位资料进行分析处理,首先使用分段线性插值法对缺测数据进行插值处理,然后用快速傅里叶变换对水位数据进行频谱分析,绘制振幅谱,分析水位数据中的不同周期成分,选取恰当的截止频率进行滤波处理,去除了干扰,获得了井水位的变化动态,提高了资料质量。最后应用滤波后的水位数据做一些震例分析。     

Automatic classification of dome instabilities based on Doppler radar measurements at Merapi volcano, Indonesia: Part I

Monitoring lava dome instabilities is crucial to efficiently monitor active dome building volcanoes. The Doppler radar technique provides a unique opportunity to gather information about the number of instability events occurring at the growing dome and about the dynamic processes that take place during different types of instabilities. So far, three different kinds of processes have been identified: sliding material, gravitational break-offs and explosive outbursts. In addition, Doppler radars provide rain measurements, which can be used to investigate possible correlations between rainfall and dome activity. Two radar systems have been installed at Merapi volcano in October 2001 and January 2005 to continuously monitor dome instabilities. Due to the large number of instability events that occur during times of high activity, manual processing and analysis of instability events is not practical for monitoring purposes. Therefore, an automatic classification system has been developed, which is capable of identifying different kinds of instabilities as well as rainfall. Two different kinds of classifier models have been applied: (1) neural network and (2) K-nearest-neighbour classifier model. Both classify Doppler spectra according to the underlying dynamic process, that is, rain, sliding material, gravitational break-off or explosive outburst. The classifiers are able to identify disturbances, which have no physical source, but are merely artefacts from the radar device itself. Because radar events are sequences of Doppler spectra, a rule set has been defined, which finally determines the event class. All classifiers have been trained and tested on independent data sets to estimate the classification performance. The overall classification rate is about 90 per cent. Discrimination of instabilities and non-volcanic events reaches about 98 per cent accuracy.