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1.
A Shear Model Accounting Scale Effect in Rock Joints Behavior   总被引：1，自引：0，他引：1  
Understanding the scale effect on the mechanical behavior of a single rock joint is still very important in rock engineering. Rock joints can be classified into three different categories depending on their scale: the “micro scale” which is the scale of the asperities; the “meso scale” is the scale of the specimens tested in laboratory; and the “macro scale” which is the scale of the rock mass. The purpose of this paper is to propose an effective way to model rock joints at both the meso and macro scale. An original constitutive mechanical model, in which parameters are deduced from experimental results, has been developed. This model is then extended to simulate the discontinuities occurring at a larger size. At the macro scale, the constitutive modeling was carried out for both small and large relative displacements. Large displacements lead to substantial changes in dilation. For both cases, the peak shear stress vanishes for joints longer than 2 m.  相似文献   

2.
A new formulation of garnet-biotite Fe–Mg exchange thermometer has been developed through statistical regression of the reversed experimental data of Ferry and Spear. Input parameters include available thermo-chemical data for quaternary Fe–Mg–Ca–Mn garnet solid solution and for excess free energy terms, associated with mixing of Al and Ti, in octahedral sites, in biotite solid solution. The regression indicates that Fe–Mg mixing in biotite approximates a symmetrical regular solution model showing positive deviation from ideality withW FeMg bi =1073±490 cal/mol. H r and S r for the garnet-biotite exchange equilibrium were derived to be 4301 cal and 1.85 cal respectively. The resultant thermometer gives consistent results for rocks with a much wider compositional range than can be accommodated by earlier formulations.  相似文献   

3.
This paper presents an innovative fuzzy regression approach for the assessment of the potential vulnerability of bridge to earthquakes. Taking the Mao-Luo-Hsi Bridge in Nantou County of Taiwan as an example, structural models representing vulnerable sections of the bridge are established and updated by ambient vibration tests. Because of uncertainties in the structural models and ambient vibration data preprocessed by wavelet filtering, the fuzzy regression approach is adopted to synthesize the maximum displacements of the bridge sections so as to develop a bridge alert?Caction principle. The fuzzy regression model can be achieved by the fuzzy blending of each individual input?Coutput realization for the critical sections D, E, and F of the bridge subjected to various earthquake intensity scales ranging from one to seven. Verification of the resulting fuzzy regression models along the longitudinal and transverse directions of the bridge reflects on the high R 2 values of the models being 0.7317 and 0.8401, respectively. The developed decision systems suggest that the action value can be determined for the location of the bridge site when the earthquake intensity reaches scale 6 corresponding to the maximum slopes of the resulting fuzzy regression curves, and the next one lower scale 5 refers the alert value.  相似文献   

4.
弥散度是刻画孔隙介质中溶质运移和扩散的重要参数,对于污染物的预测和修复至关重要,但野外示踪试验往往会选择忽略真实存在的井内混合效应。通过室内砂槽实验方法,模拟具有水平分层结构的含水层,该含水层主要由3种介质充填而成。采用埋藏传感器和井中布设传感器2种监测方式,对比在有/无混合效应情况下,穿透曲线的形态差异,进而探究井内混合效应对弥散尺度依赖性的影响情况。实验结果表明,井内混合效应会使穿透曲线呈现阶梯式增长,并伴有显著的拖尾现象;当使用对流弥散方程进行计算时,混合效应会导致弥散度被高估;观测到的弥散度与真实弥散度的差异会随着注入井和观测井间距离的增加而增大;此外,2种观测方式（埋藏/井内）均能发现弥散的尺度依赖性,且井内混合效应显著增强了弥散尺度效应,该实验结果可为污染物运移的评价和预测提供参考。   相似文献   

5.
The inter-annual variation and linear trends of the surface air temperature in the regions in and around the Bay of Bengal have been studied using the time series data of monthly and annual mean temperature for 20–40 years period within 1951–1990. The study area extends from Pusma Camp of Nepal in the north and Kuala Lumpur of Malaysia in the south and between 80--100 ° E. The annual variation of temperature has also been studied using the mean monthly temperature for the variable time frames 1961–1975, 1976–1990 and 1961–1990. The trend of temperature has been analyzed using linear regression technique with the data from 1961–1990, which showed that the warming trend is dominant over the study areas except for a few stations. It has been found that Nepal shows predominant warming trends. Bangladesh and the adjacent areas of India and the northern part of Bay of Bengal adjacent to the Bangladesh coast have shown strong warming trends of the annual temperature with maximum at Dhaka (0.037 °C/year). The near equatorial zone, i.e., southern India, Sri Lanka and part of Thailand and Malaysia (Kuala Lumpur) shows warming trends in the annual mean temperature with strong warming at Pamban and Anuradhapura (around 0.04 °C/year). The cooling trends have been observed at a few stations including Port Blair, Yangoon and Cuttack. Further analysis shows the presence of prominent ENSO scale of variations with time period 4–7 years and 2–3 years for almost all the stations. The decadal mode with T >7 years is present in some data series. The results of the variations of temperature with respect to the Southern Oscillation Index (SOI) show that SOI has some negative correlation with temperature for most of the stations except those in the extreme northeast. It has been found that positive anomaly of temperature has been observed for El Niño events and negative anomaly for the La Nina events.  相似文献   

6.
General circulation models (GCMs) fitted with stable isotope schemes are widely used to interpret the isotope–climate relationship. However, previous studies have found that the spatiotemporal isotope/precipitation correlation simulated by GCMs is stronger and more widespread than the observed value. To understand the reason for this failure, we investigated the factors influencing the empirically well-known isotope/precipitation relationship, or precipitation amount effect, in the tropics using newly obtained daily precipitation isotope monitoring data over Asia. As in previous studies, we found an apparent correlation between the long-term monthly mean isotopic content and the corresponding precipitation amount (local precipitation) observed at sub-tropical island stations. Furthermore, on a monthly timescale, the isotopic variability of precipitation for these stations was more clearly related to the regional precipitation amount than to local precipitation. This correlation of isotopic content with the regional precipitation amount was observed at the equatorial (Maritime Continent) stations. For these stations, isotope/local precipitation relationships only appeared over longer timescales, with different regression line slopes at each station. However, at the coastal stations, there was a strong linear relationship between the monthly mean isotopic content and corresponding regional precipitation, and regression line slopes were spatially uniform. For the two sub-tropical terrestrial (Indochina Peninsula) stations, the isotopic minimum appeared without any relationship to rainfall amount but usually occurred at the leeward station during the rainy season. These results suggest that the isotopic variations of precipitation did not depend on the ’local’ rain-out history but on the rain-out process in the surrounding region. However, local rainfall events were associated not only with large-scale disturbances but also with regional circulation. Thus, the scale difference of controlling factors between local rainfall amount and isotopic value results in the weakening of the rainfall amount effect at the observation site and in the discrepancy between GCM simulations and observations. This finding suggests that regional precipitation–isotope relationships should be compared with GCM results. Additionally, because the isotope signal reflects the rain-out history at a regional scale, evaluation of the isotopic field using isotopic GCMs will be useful not only to reconstruct paleoclimate conditions but also to examine how GCMs can reproduce real atmospheric circulation over the tropics.  相似文献   

7.
Summary. Uniaxial Compressive Strength (UCS), considered to be one of the most useful rock properties for mining and civil engineering applications, has been estimated from some index test results by fuzzy and multiple regression modelling. Laboratory investigations including Uniaxial Compressive Strength (UCS), Point Load Index test (PL), Schmidt Hammer Hardness test (SHR) and Sonic velocity (Vp) test have been carried out on nine different rock types yielding to 305 tested specimens in total. Average values along with the standard deviations (Stdev) as well as Coefficients of variation (CoV) have been calculated for each rock type. Having constructed the Mamdani Fuzzy algorithm, UCS of intact rock samples was then predicted using a data driven fuzzy model. The predicted values derived from fuzzy model were compared with multi-linear statistical model. Comparison proved that the best model predictions have been achieved by fuzzy modelling in contrast to multi-linear statistical modelling. As a result, the developed fuzzy model based on point load, Schmidt hammer and sonic velocity can be used as a tool to predict UCS of intact rocks.  相似文献   

8.
Rock mass classification systems are one of the most common ways of determining rock mass excavatability and related equipment assessment. However, the strength and weak points of such rating-based classifications have always been questionable. Such classification systems assign quantifiable values to predefined classified geotechnical parameters of rock mass. This causes particular ambiguities, leading to the misuse of such classifications in practical applications. Recently, intelligence system approaches such as artificial neural networks (ANNs) and neuro-fuzzy methods, along with multiple regression models, have been used successfully to overcome such uncertainties. The purpose of the present study is the construction of several models by using an adaptive neuro-fuzzy inference system (ANFIS) method with two data clustering approaches, including fuzzy c-means (FCM) clustering and subtractive clustering, an ANN and non-linear multiple regression to estimate the basic rock mass diggability index. A set of data from several case studies was used to obtain the real rock mass diggability index and compared to the predicted values by the constructed models. In conclusion, it was observed that ANFIS based on the FCM model shows higher accuracy and correlation with actual data compared to that of the ANN and multiple regression. As a result, one can use the assimilation of ANNs with fuzzy clustering-based models to construct such rigorous predictor tools.  相似文献   

9.
Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km2. In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.  相似文献   

10.
To better understand the recent motion of the Pacific plate relative to the Rivera plate and to better define the limitations of the existing Rivera–Pacific plate motion models for accurately predicting this motion, total-field magnetic data, multibeam bathymetric data and sidescan sonar images were collected during the BART and FAMEX campaigns of the N/O L'Atalante conducted in April and May 2002 in the area surrounding the Moctezuma Spreading Segment of the East Pacific Rise, located offshore of Manzanillo, Mexico, at 106°16′W, between 17.8°N and 18.5°N. Among the main results are: (1) the principle transform displacement zone of the Rivera Transform is narrow and well defined east of 107o15′W and these azimuths should be used preferentially when deriving new plate motion models, and (2) spreading rates along the Moctezuma Spreading Segment should not be used in plate motion studies as either seafloor spreading has been accommodated at more than one location since the initiation of seafloor spreading in the area of the Moctezuma Spreading Segment, or this spreading center is not a Rivera–Pacific plate boundary as has been previously assumed. Comparison of observed transform azimuths with those predicted by the best-fit poles of six previous models of Rivera–Pacific relative motion indicate that, in the study area, a significant systematic bias is present in the predictions of Rivera–Pacific motion. Although the exact source of this bias remains unclear, this bias indicates the need to derive a new Rivera–Pacific relative plate motion model.  相似文献   

11.
Barbolini  M.  Natale  L.  Savi  F. 《Natural Hazards》2002,25(3):225-244
Dynamical models for calculating snow avalanche motion have gained growingimportance in recent years for avalanche hazard assessment. Nevertheless, inherentuncertainties in their input-data specification, although well acknowledged, areusually not explicitly incorporated into the analysis and considered in the mappingresults. In particular, the estimate of avalanche release conditions is affected bystrong uncertainties when associated to a return period. These sources of error arenormally addressed through sensitivity analysis or conservative parameters estimate.However, each of these approaches has limitations in assessing the statistical implications of uncertainties.In the present paper the problem of release scenarios randomness is looked at following a Monte Carlo procedure. This statistical sampling-analysis method allows the evaluation of the probability distributions of relevant variables for avalanche hazard assessment – such as runout distance and impact pressure – once the release variables – essentially releasedepth and release length – are expressed in terms of probability distributions, accounting explicitly for inherent uncertainties in their definition. Both the theoretical framework of this procedure and its application to a real study case are presented. As initial step of this research in the present work the attention is mainly focused on flowing avalanches descending on open slopes. Therefore, the one-dimensional version of VARA dynamic models is usedfor avalanche simulations.  相似文献   

12.
This article presents a multidisciplinary approach to landslide susceptibility mapping by means of logistic regression, artificial neural network, and geographic information system (GIS) techniques. The methodology applied in ranking slope instability developed through statistical models (conditional analysis and logistic regression), and neural network application, in order to better understand the relationship between the geological/geomorphological landforms and processes and landslide occurrence, and to increase the performance of landslide susceptibility models. The proposed experimental study concerns with a wide research project, promoted by the Tuscany Region Administration and APAT-Italian Geological Survey, aimed at defining the landslide hazard in the area of the Sheet 250 “Castelnuovo di Garfagnana” (1:50,000 scale). The study area is located in the middle part of the Serchio River basin and is characterized by high landslide susceptibility due to its geological, geomorphological, and climatic features, among the most severe in Italy. Terrain susceptibility to slope failure has been approached by means of indirect-quantitative statistical methods and neural network software application. Experimental results from different methods and the potentials and pitfalls of this methodological approach have been presented and discussed. Applying multivariate statistical analyses made it possible a better understanding of the phenomena and quantification of the relationship between the instability factors and landslide occurrence. In particular, the application of a multilayer neural network, equipped for supervised learning and error control, has improved the performance of the model. Finally, a first attempt to evaluate the classification efficiency of the multivariate models has been performed by means of the receiver operating characteristic (ROC) curves analysis approach.  相似文献   

13.
Plots of sedimentation rates vs. time span of observation are routinely used to demonstrate that sedimentation rates decrease if one averages over longer time spans. However, these plots are suspect because they plot a variable, time, against its inverse. It has been shown that even random numbers may yield correlation coefficients of 0.7 or higher under these circumstances. We have circumvented this problem by splitting observed sedimentation rates into time classes and performing regression on the primary variables, thickness and time, separately in each class. An alternative is weighted regression that corrects for the effect of spurious correlation. Regression on the primary variables has been performed on real data from siliciclastic and carbonate rocks. Data were sorted into time classes of 10 –1–10 2 yr, 10 2–10 5 yr, and 10 5–10 8 yr. Sedimentation rates decrease systematically as the time windows increase. The experiment indicates that the decrease of sedimentation rates with increase of time is not simply an effect of the mathematical transformation. It is a physical phenomenon, probably related to the fact that sedimentation is an episodic process and that the sediment record is riddled with hiatuses on all scales.  相似文献   

14.
Assessment of uncertainties related to seismic hazard using fuzzy analysis   总被引：1，自引：1，他引：0  
Seismic hazard analysis in the last few decades has become a very important issue. Recently, new technologies and available data have been improved that have helped many scientists to understand where and why earthquakes happen, the physics of earthquakes, etc. Scientists have begun to understand the role of uncertainty in seismic hazard analysis. However, how to handle existing uncertainty is still a significant problem. The same lack of information causes difficulties in quantifying uncertainty accurately. Usually, attenuation curves are obtained in a statistical manner: regression analysis. Statistical and probabilistic analyses show overlapping results for the site coefficients. This overlapping takes place not only at the border between two neighboring classes but also among more than three classes. Although the analysis starts from classifying sites using geological terms, these site coefficients are not classified at all. In the present study, this problem is solved using fuzzy set theory. Using membership functions, the ambiguities at the border between neighboring classes can be avoided. Fuzzy set theory is performed for southern California in the conventional way. In this study, standard deviations that show variations between each site class obtained by fuzzy set theory and the classical manner are compared. Results of this analysis show that when we have insufficient data for hazard assessment, site classification based on fuzzy set theory shows values of standard deviations less than those obtained using the classical way, which is direct proof of less uncertainty.  相似文献   

15.
Weights of evidence and logistic regression are two of the most popular methods for mapping mineral prospectivity. The logistic regression model always produces unbiased estimates, whether or not the evidence variables are conditionally independent with respect to the target variable, while the weights of evidence model features an easy to explain and implement modeling process. It has been shown that there exists a model combining weights of evidence and logistic regression that has both of these advantages. In this study, three models consisting of modified fuzzy weights of evidence, fuzzy weights of evidence, and logistic regression are compared with each other for mapping mineral prospectivity. The modified fuzzy weights of the evidence model retains the advantages of both the fuzzy weights of the evidence model and the logistic regression model; the advantages being (1) the predicted number of deposits estimated by the modified fuzzy weights of evidence model is nearly equal to that of the logistic regression model, and (2) it can deal with missing data. This method is shown to be an effective tool for mapping iron prospectivity in Fujian Province, China.  相似文献   

16.
张嘉  王明玉 《地学前缘》2010,17(6):152-158
在地下水污染模拟预报中,弥散参数是很难确定的一个模型参数。因实验室小尺度弥散规律一般不能用于大尺度弥散过程,而野外示踪试验却耗资大、周期长,限制了其实用性。文中利用随机数值模拟手段、基于随机理论的蒙特卡罗方法及序贯高斯模拟技术来生成渗透系数随机场,并研究渗透系数对数场的方差、相关长度以及变异函数类型在不同尺度上对纵向弥散度的影响,进而建立纵向弥散度与随机分布渗透系数场的方差和相关长度的统计定量关系,并与Gelhar理论计算结果进行比较。数值模拟结果表明,经过一定迁移距离后纵向弥散度与随机分布渗透系数对数场的方差和相关长度具有良好的线性统计关系,与Gelhar理论公式表达的关系类型类似。但对于较大的方差,纵向弥散度模拟结果明显大于Gelhar理论计算值,而对于较大相关长度在迁移距离不很大时,纵向弥散度模拟结果明显小于Gelhar理论计算值。本研究可为野外大尺度地下水污染预报模型中水动力弥散参数的确定提供方法借鉴。  相似文献   

17.
区域蒸散发遥感估算方法及验证综述   总被引：7，自引：0，他引：7  
张荣华  杜君平  孙睿 《地球科学进展》2012,27(12):1295-1307
蒸散发是地表水热平衡的重要参量,也是农作物生长状况和产量的重要指标。与传统的蒸散发计算方法相比,遥感技术经济、适用、有效,在非均匀下垫面的区域蒸散发监测上具有明显的优越性。系统回顾了5种常用的区域蒸散发遥感估算方法,包括经验统计模型、与传统方法相结合的遥感模型、地表能量平衡模型、温度—植被指数特征空间模型以及陆面过程与数据同化等,分析了这些模型的最新研究进展及各自的优缺点,并对地表蒸散发的地面验证方法进行了概述。最后简要分析了区域蒸散发遥感估算存在的问题,并展望了其未来发展趋势。多源遥感数据协同反演与非遥感参数遥感化、蒸散发模型改进与多模型集成、陆面过程与遥感数据同化、遥感蒸散发估算及地面验证中的尺度问题与空间代表性问题研究等将会是未来区域蒸散发研究中的重点发展方向。  相似文献   

18.
Correct block size assessment is the most important stage for rock quarry management. Although volumetric joint count (Jv) and weighted joint density (wJd) were proposed for this purpose, simple prediction method for these indices is not encountered in literature. Due to the fact that some rock masses such as marbles contain less discontinuity, collection of representative amount of data from in situ line surveys for statistical assessments is highly difficult. For this reason, the main targets of the present paper are to apply photoanalysis approach for collecting additional discontinuity data and to obtain some simple statistical and fuzzy models for predicting weighted joint density to evaluate block size in engineering practice for marbles around Supren (Eskisehir, Turkey). In addition, a new and simple approach to predict volumetric decrease caused by chemical weathering is introduced. For these purposes, extensive field and photoanalysis studies were performed and the data obtained from both field and photoanalysis studies were assessed by regression and fuzzy approaches. The results revealed that the prediction performance of the fuzzy inference system is higher than that of the regression equation.  相似文献   

19.
This paper investigates the prediction of future earthquakes that would occur with magnitude 5.5 or greater using adaptive neuro-fuzzy inference system (ANFIS). For this purpose, the earthquake data between 1950 and 2013 that had been recorded in the region with 2°E longitude and 4°N latitude in Iran has been used. Thereupon, three algorithms including grid partition (GP), subtractive clustering (SC) and fuzzy C-means (FCM) were used to develop models with the structure of ANFIS. Since the earthquake data for the specified region had been reported on different magnitude scales, suitable relationships were determined to convert the magnitude scales into moment magnitude and all records uniformed based on the relationships. The uniform data were used to calculate seismicity indicators, and ANFIS was developed based on considered algorithms. The results showed that ANFIS-FCM with a high accuracy was able to predict earthquake magnitude.  相似文献   

20.
About 400 km of new seismic reflection data has been acquired in the study region offshore of Alaçatı, Doğanbey, and Kuşadası, which enables investigation of the active crustal deformation in this region. The deformation onshore in western Turkey is dominated by crustal extension, and clear evidence of this process is also now available from this offshore area. However, in the onshore area adjacent to this study region evidence of active right-lateral strike-slip faulting has also previously been observed. This strike-slip faulting has previously been thought only to accommodate variations in extension between adjacent normal faults. However, in the offshore area there is considerable evidence of zones of deformation, some of which may link to the strike-slip faulting onshore, suggesting that strike-slip faulting may be of greater importance in this region than previously thought.  相似文献   

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