188 resultados para Inherent Soil Variability


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By using the lower bound limit analysis in conjunction with finite elements and linear programming, the bearing capacity factors due to cohesion, surcharge and unit weight, respectively, have been computed for a circular footing with different values of phi. The recent axisymmetric formulation proposed by the authors under phi = 0 condition, which is based on the concept that the magnitude of the hoop stress (sigma(theta)) remains closer to the least compressive normal stress (sigma(3)), is extended for a general c-phi soil. The computational results are found to compare quite well with the available numerical results from literature. It is expected that the study will be useful for solving various axisymmetric geotechnical stability problems. Copyright (C) 2010 John Wiley & Sons, Ltd.

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Recycling plastic waste from water bottles has become one of the major challenges worldwide. The present study provides an approach for the use plastic waste as reinforcement material in soil. The experimental results in the form of stress-strain-pore water pressure response are presented. Based on experimental test results, it is observed that the strength of soil is improved and compressibility reduced significantly with addition of a small percentage of plastic waste to the soil. The use of the improvement in strength and compressibility response due to inclusion of plastic waste can be advantageously used in bearing capacity improvement and settlement reduction in the design of shallow foundations. (C) 2010 Elsevier Ltd. All rights reserved.

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An energy landscape view of phase separation and nonideality in binary mixtures is developed by exploring their potential energy landscape (PEL) as functions of temperature and composition. We employ molecular dynamics simulations to study a model that promotes structure breaking in the solute-solvent parent binary liquid, at low temperatures. The PEL of the system captures the potential energy distribution of the inherent structures (IS) of the system and is obtained by removing the kinetic energy (including that of intermolecular vibrations). The broader distribution of the inherent structure energy for structure breaking liquid than that of the structure making liquid demonstrates the larger role of entropy in stabilizing the parent liquid of the structure breaking type of binary mixtures. At high temperature, although the parent structure of the structure breaking binary mixture is homogenous, the corresponding inherent structure is found to be always phase separated, with a density pattern that exhibits marked correlation with the energy of its inherent structure. Over a broad range of intermediate inherent structure energy, bicontinuous phase separation prevails with interpenetrating stripes as signatures of spinodal decomposition. At low inherent structure energy, the structure is largely phase separated with one interface where as at high inherent structure energy we find nucleation type growth. Interestingly, at low temperature, the average inherent structure energy (< EIS >) exhibits a drop with temperature which signals the onset of crystallization in one of the phases while the other remains in the liquid state. The nonideal composition dependence of viscosity is anticorrelated with average inherent structure energy.

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An interaction analysis of an axially loaded single pile and pile group with and without a pile cap in a layered soil medium has been investigated using the two-dimensional photoelastic method. A study of the pile or pile group behaviour has been made, varying the pile cap thickness as well as the embedded length of the pile in the hard stratum. The shear stress distribution along the pile-soil interface, non-dimensionalized settlement values of the single pile and the interaction factor for the pile group have been presented. Wherever possible, the results of the present analysis have been compared with available numerical solutions.

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This study describes two machine learning techniques applied to predict liquefaction susceptibility of soil based on the standard penetration test (SPT) data from the 1999 Chi-Chi, Taiwan earthquake. The first machine learning technique which uses Artificial Neural Network (ANN) based on multi-layer perceptions (MLP) that are trained with Levenberg-Marquardt backpropagation algorithm. The second machine learning technique uses the Support Vector machine (SVM) that is firmly based on the theory of statistical learning theory, uses classification technique. ANN and SVM have been developed to predict liquefaction susceptibility using corrected SPT (N-1)(60)] and cyclic stress ratio (CSR). Further, an attempt has been made to simplify the models, requiring only the two parameters (N-1)(60) and peck ground acceleration (a(max)/g)], for the prediction of liquefaction susceptibility. The developed ANN and SVM models have also been applied to different case histories available globally. The paper also highlights the capability of the SVM over the ANN models.

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A sample of 96 compact flat-spectrum extragalactic sources, spread evenly over all galactic latitudes, has been studied at 327 MHz for variability over a time interval of about 15 yr. The variability shows a dependence on galactic latitude being less both at low and high latitudes and peaking around absolute value of b approximately 15-degrees. The latitude dependence is surprisingly similar in both the galactic centre and anticentre directions. Assuming various single and multi-component distributions for the ionized, irregular interstellar plasma, we have tried to generate the observed dependence using a semi-qualitative treatment of refractive interstellar scintillations. We find that it is difficult to fit our data with any single or double component cylindrical distribution. Our data suggests that the observed variability could be influenced by the spiral structure of our Galaxy.

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As a seepage barrier slurry trench material should have a relatively low coefficient of permeability, in the range of 10(-7) cm/s, and at the same time should be compatible with surrounding material with regard to compressibility. Although bentonite-sand/soil mixes are used widely, there is no specific engineering approach to proportion these mixes that satisfies the above practical requirements. In this paper, a generalized approach is presented for predicting the permeability and compressibility characteristics of mixes with minimum input parameters. This approach will be helpful in proportioning mixes and predicting corresponding changes in engineering behavior. It is possible to proportion a mix to arrive at the required compressibility without affecting the permeability. This is explained using an illustrative example.

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Stochastic structural systems having a stochastic distribution of material properties and stochastic external loadings in space are analysed when a crack of deterministic size is present. The material properties and external loadings are considered to constitute independent, two-dimensional, univariate, real, homogeneous stochastic fields. The stochastic fields are characterized by their means, variances, autocorrelation functions or the equivalent power spectral density functions, and scale fluctuations. The Young's modulus and Poisson's ratio are treated to be stochastic quantities. The external loading is treated to be a stochastic field in space. The energy release rate is derived using the method of virtual crack extension. The deterministic relationship is derived to represent the sensitivities of energy release rate with respect to both virtual crack extension and real system parameter fluctuations. Taylor series expansion is used and truncation is made to the first order. This leads to the determination of second-order properties of the output quantities to the first order. Using the linear perturbations about the mean values of the output quantities, the statistical information about the energy release rates, SIF and crack opening displacements are obtained. Both plane stress and plane strain cases are considered. The general expressions for the SIF in all the three fracture modes are derived and a more detailed analysis is conducted for a mode I situation. A numerical example is given.

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This paper critically appraises the limitations of the liquid-limit water content of clayey soils determined conventionally either by percussion cup or by the cone penetration method. It is shown that the conventional liquid limit and plastic limit are arbitrary, strength-based water contents and that they cannot represent the plasticity limits, and that the state of the soil-water system at the conventional liquid limit does not correspond to a stress-free reference state. The present investigation identifies three characteristic limiting water contents for a soil-water system which have well-defined, unique mechanisms controlling them, namely the free swell limit, settling limit and shrinkage limit. Simple procedures for the determination of the free swell limit and settling limit of natural soils are presented. The settling limit is shown to be the 'real liquid limit' of any clayey soil. With a number of experimental illustrations, it is clearly shown that the settling limit represents the maximum water-holding capacity of clayey soils and that it corresponds to the stress-free reference state.

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The potential predictability of the Indian summer monsoon due to slowly varying sea surface temperature (SST) forcing is examined. Factors responsible for limiting the predictability are also investigated. Three multiyear simulations with the R30 version of the Geophysical Fluid Dynamics Laboratory's climate model are carried out for this purpose, The mean monsoon simulated by this model is realistic including the mean summer precipitation over the Indian continent. The interannual variability of the large-scale component of the monsoon such as the "monsoon shear index" and its teleconnection with Pacific SST is well simulated by the model in a 15-yr integration with observed SST as boundary condition. On regional scales, the skill in simulating the interannual variability of precipitation over the Indian continent by the model is rather modest and its simultaneous correlation with eastern Pacific SST is negative but poor as observed. The poor predictability of precipitation over the Indian region in the model is related to the fact that contribution to the interannual variability over this region due to slow SST variations [El Nino-Southern Oscillation (ENSO) related] is comparable to those due to regional-scale fluctuations unrelated to ENSO SST. The physical mechanism through which ENSO SST tend to produce reduction in precipitation over the Indian continent is also elucidated. A measure of internal variability of the model summer monsoon is obtained from a 20-yr integration of the same model with fixed annual cycle SST as boundary conditions but with predicted soil moisture and snow cover. A comparison of summer monsoon indexes between this run and the observed SST run shows that the internal oscillations can account for a large fraction of the simulated monsoon variability. The regional-scale oscillations in the observed SST run seems to arise from these internal oscillations. It is discovered that most of the interannual internal variability is due to an internal quasi-biennial oscillation (QBO) of the model atmosphere. Such a QBO is also found in the author's third 18-yr simulation in which fixed annual cycle of SST as well as soil moisture and snow cover are prescribed. This shows that the model QBO is not due to land-surface-atmosphere interaction. It is proposed that the model QBO arises due to an interaction between nonlinear intraseasonal oscillations and the annual cycle. Spatial structure of the QBO and its role in limiting the predictability of the Indian summer monsoon is discussed.

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The soil moisture characteristic (SMC) forms an important input to mathematical models of water and solute transport in the unsaturated-soil zone. Owing to their simplicity and ease of use, texture-based regression models are commonly used to estimate the SMC from basic soil properties. In this study, the performances of six such regression models were evaluated on three soils. Moisture characteristics generated by the regression models were statistically compared with the characteristics developed independently from laboratory and in-situ retention data of the soil profiles. Results of the statistical performance evaluation, while providing useful information on the errors involved in estimating the SMC, also highlighted the importance of the nature of the data set underlying the regression models. Among the models evaluated, the one possessing an underlying data set of in-situ measurements was found to be the best estimator of the in-situ SMC for all the soils. Considerable errors arose when a textural model based on laboratory data was used to estimate the field retention characteristics of unsaturated soils.

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Geophysical methods are becoming more popular nowadays in the field of hydrology due to their time and space efficiency. So an attempt has been made here to relate electrical resistivity with soil moisture content in the field. The experiments were carried out in an experimental watershed `Mulehole' in southern India, which is a forested watershed with approximately 80% red soil. Five auger holes were drilled to perform the soil moisture and electrical resistivity measurements in a toposequence having red and black soils, with sandy weathered soil at the bottom. Soil moisture was measured using neutron probe and electrical resistivity was measured using electrical logging tool. The results indicate that electrical resistivity measurements can be used to measure soil moisture content for red soils only.