受冲击的饱和砂土产生裂缝和通道的实验研究

本文首先对饱和砂土在动载荷下的液化、密实和结构破坏等方面做了文献综述，同时也叙述了化工冶金中的液固流态化的有关情况。本文探讨了饱和砂土中产生水平裂缝和纵向通道等现象的机理。为此，进行了扁平砂柱的落锤冲击实验和模拟圆柱落锤冲击实验中产生水平裂缝和纵向通道等现象的底部加压实验。扁平砂柱落锤冲击实验的目的是为了更清楚地观察饱和砂土结构破坏和孔隙水流动的情况，观察纵向通道和水平裂缝的产生和发展，以及水平裂缝和纵向通道之间的联系。为了探讨水平裂缝和纵向通道产生的条件和机理，设计和进行了底部加压实验，用来模拟落锤冲击实验的后期变形和渗流效应，测量出现水平裂缝和纵向通道时的超孔隙水压力和平均水流速度，统计分析采用什么样的参数可以表征水平裂缝和纵向通道的出现及其特性，发现液化指数等于1是出现水平裂缝的必要条件。此外，针对含有细砂层的饱和砂土在该层出现水平裂缝的现象，提出了一个简化模型，推导出砂柱的液化指数一维分布，根据液化指数等于1才能出现水平裂缝，能够说明水平裂缝出现的条件和位置。

Liquefaction Hazard Mapping of Bangalore, South India

his paper presents identification and mapping of vulnerable and safe zones for liquefaction hazard. About 850 bore logs data collected from geotechnical investigation reports have been used to estimate the liquefaction factor of safety for Bangalore Mahanagara palike (BMP) area of about 220 km(2). Liquefaction factor of safety is arrived based on surface level peak ground acceleration presented by Anbazhagan and Sitharam(5) and liquefaction resistance, using corrected standard penetration test (SPT) N values. The estimated factor of safety against liquefaction is used to estimate liquefaction potential index and liquefaction severity index. These values are mapped using Geographical information system (GIS) to identify the vulnerable and safe zones in Bangalore. This study shows that more than 95% of the BMP area is safe against liquefaction potential. However the western part of the BMP is not safe against liquefaction, as it may be subjected to liquefaction with probability of 35 to 65%. Three approaches used in this study show that 1) mapping least factor of safety irrespective of depth may be used to find liquefiable area for worst case. 2) mapping liquefaction potential index can be used to assess the liquefaction severity of the area by considering layer thickness and factor of safety and 3) mapping of liquefaction severity index can be used to access the probability of liquefaction of area.

Support vector machine for evaluating seismic-liquefaction potential using shear wave velocity

The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.

Understanding Micro- and Macro-Mechanics of Soil Liquefaction: A Necessary Step for Field-Scale Assessment

Liquefaction is a devastating instability associated with saturated, loose, and cohesionless soils. It poses a significant risk to distributed infrastructure systems that are vital for the security, economy, safety, health, and welfare of societies. In order to make our cities resilient to the effects of liquefaction, it is important to be able to identify areas that are most susceptible. Some of the prevalent methodologies employed to identify susceptible areas include conventional slope stability analysis and the use of so-called liquefaction charts. However, these methodologies have some limitations, which motivate our research objectives. In this dissertation, we investigate the mechanics of origin of liquefaction in a laboratory test using grain-scale simulations, which helps (i) understand why certain soils liquefy under certain conditions, and (ii) identify a necessary precursor for onset of flow liquefaction. Furthermore, we investigate the mechanics of liquefaction charts using a continuum plasticity model; this can help in modeling the surface hazards of liquefaction following an earthquake. Finally, we also investigate the microscopic definition of soil shear wave velocity, a soil property that is used as an index to quantify liquefaction resistance of soil. We show that anisotropy in fabric, or grain arrangement can be correlated with anisotropy in shear wave velocity. This has the potential to quantify the effects of sample disturbance when a soil specimen is extracted from the field. In conclusion, by developing a more fundamental understanding of soil liquefaction, this dissertation takes necessary steps for a more physical assessment of liquefaction susceptibility at the field-scale.

High body mass index is not a barrier to physical activity: Analysis of international rugby players' anthropometric data

Recent data indicate that levels of overweight and obesity are increasing at an alarming rate throughout the world. At a population level (and commonly to assess individual health risk), the prevalence of overweight and obesity is calculated using cut-offs of the Body Mass Index (BMI) derived from height and weight. Similarly, the BMI is also used to classify individuals and to provide a notional indication of potential health risk. It is likely that epidemiologic surveys that are reliant on BMI as a measure of adiposity will overestimate the number of individuals in the overweight (and slightly obese) categories. This tendency to misclassify individuals may be more pronounced in athletic populations or groups in which the proportion of more active individuals is higher. This differential is most pronounced in sports where it is advantageous to have a high BMI (but not necessarily high fatness). To illustrate this point we calculated the BMIs of international professional rugby players from the four teams involved in the semi-finals of the 2003 Rugby Union World Cup. According to the World Health Organisation (WHO) cut-offs for BMI, approximately 65% of the players were classified as overweight and approximately 25% as obese. These findings demonstrate that a high BMI is commonplace (and a potentially desirable attribute for sport performance) in professional rugby players. An unanswered question is what proportion of the wider population, classified as overweight (or obese) according to the BMI, is misclassified according to both fatness and health risk? It is evident that being overweight should not be an obstacle to a physically active lifestyle. Similarly, a reliance on BMI alone may misclassify a number of individuals who might otherwise have been automatically considered fat and/or unfit.