PLS法与隧道围岩稳定性分类

围岩稳定性是隧道工程支护设计的基本参数,采用偏最小二乘回归法,综合考虑多因变量影响因素,对隧道围岩稳定性分类进行回归建模,并取得较好效果.     

海洋天然气水合物的地球物理研究(III):似海底反射

对天然气水合物研究中与似海底反射有关的一些观点进行讨论 ,以推动天然气水合物地震研究的认识 .30年的似海底反射研究表明 ,似海底反射仍然是指示天然气水合物沉积存在的最好手段之一 .有似海底反射 ,是可以认为存在天然气水合物的 .虽然存在“游离气带速度模型”与“水合物楔速度模型” ,但似海底反射主要由天然气水合物稳定带底界下方的游离气引起 .BSR上方的天然气水合物、下方的游离气与天然气再循环和含甲烷的流体流有关 .由于天然气水合物稳定带计算控制因素难以准确确定等因素 ,似海底反射与天然气水合物稳定带底界只是近似的对应关系 .需从动态的观点考虑天然气水合物 天然气体系及其与似海底反射的关系 .     

Decoupled seismic analysis of an earth dam

The seismic stability of an earth dam is evaluated via the decoupled displacement analysis using the accelerograms obtained by ground response analysis to compute the earthquake-induced displacements. The response analysis of the dam is carried out under both 1D and 2D conditions, incorporating the non-linear soil behaviour through the equivalent linear method. Ten artificial and five real accelerograms were used as input motions and four different depths were assumed for the bedrock.1D and 2D response analyses were in a fair agreement with the exception of the top third of the dam where only a 2D modelling of the problem could ensure that the acceleration field is properly described. The acceleration amplification ratio obtained in the 2D analyses was equal to about 2 in all the cases considered, consistently with data from real case histories.The maximum permanent displacements computed by the sliding block analysis were small, being less than 10% of the service freeboard; a satisfactory performance of the dam can then be envisaged for any of the seismic scenarios considered in the analyses.     

Bio-dependent bed parameters as a proxy tool for sediment stability in mixed habitat intertidal areas

The stability of cohesive and non-cohesive sediments in a mixed intertidal habitat within the Ria Formosa tidal lagoon, Portugal, was examined during two field campaigns as part of the EU F-ECTS project. The cohesive strength meter Mk III was used to determine critical erosion shear stress (τ_c) within a variety of different intertidal habitats and substrata, including Spartina maritima fields and Zostera noltii beds. The best predictor(s) for τ_c were derived from a range of properties measured for the surface sediments (chlorophyll a, colloidal carbohydrate, water, organic content, % fraction <63 μm, and seabed elevation). Pigment biomarkers were used to identify the dominant algal groups within the surface phytobenthic assemblage.Strong, seasonally dependent relationships were found between τ_c and habitat type, chl a, colloidal carbohydrate and bed elevation. Typically, critical erosion thresholds decreased seawards, reflecting a change from biostabilisation by cyanobacteria in the upper intertidal areas, to biostabilisation by diatoms on the bare substrata of the channel edges. In the late summer/early autumn, cyanobacteria were the main sediment stabilisers, and colloidal carbohydrate was the best bio-dependent predictor of τ_c across the entire field area. In the late winter/early spring, cyanobacterial activity was lower, and sediment stabilisation by Enteromorpha clathrata was important; the best predictor of τ_c was bed elevation. The implications and use of proxies for sediment stability are discussed in terms of feedback and sedimentation processes operating across the intertidal area.     

Testing a model for predicting the timing and location of shallow landslide initiation in soil‐mantled landscapes

The growing availability of digital topographic data and the increased reliability of precipitation forecasts invite modelling efforts to predict the timing and location of shallow landslides in hilly and mountainous areas in order to reduce risk to an ever‐expanding human population. Here, we exploit a rare data set to develop and test such a model. In a 1·7 km² catchment a near‐annual aerial photographic coverage records just three single storm events over a 45 year period that produced multiple landslides. Such data enable us to test model performance by running the entire rainfall time series and determine whether just those three storms are correctly detected. To do this, we link a dynamic and spatially distributed shallow subsurface runoff model (similar to TOPMODEL) to an in?nite slope model to predict the spatial distribution of shallow landsliding. The spatial distribution of soil depth, a strong control on local landsliding, is predicted from a process‐based model. Because of its common availability, daily rainfall data were used to drive the model. Topographic data were derived from digitized 1 : 24 000 US Geological Survey contour maps. Analysis of the landslides shows that 97 occurred in 1955, 37 in 1982 and ?ve in 1998, although the heaviest rainfall was in 1982. Furthermore, intensity–duration analysis of available daily and hourly rainfall from the closest raingauges does not discriminate those three storms from others that did not generate failures. We explore the question of whether a mechanistic modelling approach is better able to identify landslide‐producing storms. Landslide and soil production parameters were ?xed from studies elsewhere. Four hydrologic parameters characterizing the saturated hydraulic conductivity of the soil and underlying bedrock and its decline with depth were ?rst calibrated on the 1955 landslide record. Success was characterized as the most number of actual landslides predicted with the least amount of total area predicted to be unstable. Because landslide area was consistently overpredicted, a threshold catchment area of predicted slope instability was used to de?ne whether a rainstorm was a signi?cant landslide producer. Many combinations of the four hydrological parameters performed equally well for the 1955 event, but only one combination successfully identi?ed the 1982 storm as the only landslide‐producing storm during the period 1980–86. Application of this parameter combination to the entire 45 year record successfully identi?ed the three events, but also predicted that two other landslide‐producing events should have occurred. This performance is signi?cantly better than the empirical intensity–duration threshold approach, but requires considerable calibration effort. Overprediction of instability, both for storms that produced landslides and for non‐producing storms, appears to arise from at least four causes: (1) coarse rainfall data time scale and inability to document short rainfall bursts and predict pressure wave response; (2) absence of local rainfall data; (3) legacy effect of previous landslides; and (4) inaccurate topographic and soil property data. Greater resolution of spatial and rainfall data, as well as topographic data, coupled with systematic documentation of landslides to create time series to test models, should lead to signi?cant improvements in shallow landslides forecasting. Copyright © 2003 John Wiley & Sons, Ltd.     

Mechanisms of riverbank failure along the Arno River,central Italy

Riverbanks along the Arno River have been investigated with the aims of de?ning the main mechanisms of failure and retreat, their spatial distribution, and their causes. Geomorphological aspects were investigated by a reconnaissance of riverbank processes, for a number (26) of representative sites. Laboratory and in situ tests were then performed on a selected number of riverbanks (15). Based on the material characteristics, six main typologies of riverbanks have been de?ned, with homogeneous ?ne‐grained and composite banks representing the most frequent types. Slab‐type failures are the most frequent mechanism observed on ?ne‐grained banks, while cantilever failures prevail on composite banks. The role of river stage and related pore water pressure distributions in triggering the main observed mechanisms of failure has been investigated using two different types of stability analysis. The ?rst was conducted for 15 riverbanks, using the limit equilibrium method and considering simpli?ed hypotheses for pore water pressure distribution (annulment of negative pore pressures in the portion of the bank between low water stage and peak stage). Stability conditions and predicted mechanisms of failure are shown to be in reasonably good agreement with ?eld observations. Three riverbanks, representative of the main alluvial reaches of the river, were then selected for a more detailed bank stability analysis, consisting of: (a) de?nition of characteristic hydrographs of the reach with different return periods; (b) modelling of saturated and unsaturated ?ow using ?nite element seepage analysis; and (c) stability analysis with the limit equilibrium method, by adopting pore water pressure values derived from the seepage analysis. The results are compared to those obtained from the previous simpli?ed analysis, and are used to investigate the different responses, in terms of stability, to different hydrological and riverbank conditions. Copyright © 2003 John Wiley & Sons, Ltd.     

京沈高速公路迁-滦连线龙山滑坡成因机理分析及治理

对龙山滑坡层状滑体的破坏模式进行了分析，采用Sarma法和直线滑面型边坡分析法对各个滑块进行了稳定性分析计算，结果准确。根据不同的工程地质条件，采用不同的工程措施进行治理，效果良好。     

Risk analysis of landslides – A case study

The effects of uncertainty due to the variability of soil parameters on the risk of landsliding in the Himalayan region are investigated using a random field model combined with slope stability analyses. Effects of spatial variability both in horizontal and vertical directions, number of test samples, variations in piezometric level and the influence of earthquake on the reliability of a typical slope in a slide area are investigated. The results show that the reliability of slopes in the slide area is significantly affected by the coefficients of variation of soil parameters, spatial variations of soil parameters, number of test samples and piezometric variations. The results also show that the assumption of isotropic variations to assess slope reliability isconservative. The results of the study are useful in providing guidelines and pointing to remedial measures in the form of sub-surface drainage to improve slope reliability in the area.     

Stability analysis of the Vallcebre translational slide,Eastern Pyrenees (Spain) by means of a GIS

The stability of the landslide of Vallcebre has been evaluated by means of a GIS. The landslide mechanism is a translational failure which has been analysed as an infinite slope. Soil strength parameters and groundwater conditions are obtained from laboratory tests and monitoring devices. Geometric parameters necessary to compute the factor of safety at each individual cell are generated by interpolation from the boreholes present in the landslide. The results have been checked with the actual behaviour of the landslide and are consistent. The comparison between a conventional slope stability analysis and the GIS-based approach gives similar results, showing the feasibility of the latter.