Liquefaction Studies on Silty Clays Using Cyclic Triaxial Tests

Liquefaction of saturated soils during earthquake often had been a major cause of damage to structures. Since beginning the liquefaction studies were concentrated on sandy soils, as the sandy soils are known to be more susceptible to liquefaction. However, observations from some sites in China and Loma-Prieta earthquakes show that soils with high plastic fines are also susceptible to liquefaction. Isotropically consolidated undrained cyclic triaxial tests were conducted on undisturbed samples of silty clay soil and results of these tests are used to verify the methods based on SPT data. Slow cyclic tests were performed to investigate the development of pore pressure and cyclic strength, as reliable pore pressure measurement is only possible in slow cyclic triaxial test for clayey soils. The site was than characterized for liquefaction by a computer program developed. The N-value was obtained for the same site by conducting Standard Penetration Test. Test results were verified using methods reported by Tokimatsu & Yoshimi (1983) and Ishihara (1993). The simplicity of the methods and application of the methods to the fine-grained soils are the main criteria for selection of the field methods. The computer program also provides characterization of site using these methods

Nadaraya-Watson estimator for sensor fusion problems

The classical Nadaraya-Watson estimator is shown to solve a generic sensor fusion problem where the underlying sensor error densities are not known but a sample is available. By employing Haar kernels this estimator is shown to yield finite sample guarantees and also to be efficiently computable. Two simulation examples, and a robotics example involving the detection of a door using arrays of ultrasonic and infrared sensors, are presented to illustrate the performance

Distributed decision fusion using empirical estimation

The problem of optimal data fusion in multiple detection systems is studied in the case where training examples are available, but no a priori information is available about the probability distributions of errors committed by the individual detectors. Earlier solutions to this problem require some knowledge of the error distributions of the detectors, for example, either in a parametric form or in a closed analytical form. Here the authors show that, given a sufficiently large training sample, an optimal fusion rule can be implemented with an arbitrary level of confidence. They first consider the classical cases of Bayesian rule and Neyman-Pearson test for a system of independent detectors. Then they show a general result that any test function with a suitable Lipschitz property can be implemented with arbitrary precision, based on a training sample whose size is a function of the Lipschitz constant, number of parameters, and empirical measures. The general case subsumes the cases of non-independent and correlated detectors

Fusion rule estimation using vector space methods

In a system of N sensors, the sensor S{sub j}, j = 1, 2 .... N, outputs Y{sup (j)} {element_of} {Re}, according to an unknown probability distribution P{sub (Y(j) /X)}, corresponding to input X {element_of} [0, 1]. A training n-sample (X{sub 1}, Y{sub 1}), (X{sub 2}, Y{sub 2}), ..., (X{sub n}, Y{sub n}) is given where Y{sub i} = (Y{sub i}{sup (1)}, Y{sub i}{sup (2)}, . . . , Y{sub i}{sup N}) such that Y{sub i}{sup (j)} is the output of S{sub j} in response to input X{sub i}. The problem is to estimate a fusion rule f : {Re}{sup N} {r_arrow} [0, 1], based on the sample, such that the expected square error is minimized over a family of functions Y that constitute a vector space. The function f* that minimizes the expected error cannot be computed since the underlying densities are unknown, and only an approximation f to f* is feasible. We estimate the sample size sufficient to ensure that f provides a close approximation to f* with a high probability. The advantages of vector space methods are two-fold: (a) the sample size estimate is a simple function of the dimensionality of F, and (b) the estimate f can be easily computed by well-known least square methods in polynomial time. The results are applicable to the classical potential function methods and also (to a recently proposed) special class of sigmoidal feedforward neural networks

Compressibility Behaviour of Borneo Tropical Peat Stabilized with Lime-Sand Column

Construction on peat soils can have two alternatives, either to excavate and replace the weak soil or to improve the soil strength using soil stabilizers such as lime and other ground improvement method such as soil column. This paper studies the properties of Borneo tropical peat soil and the effect of lime-sand-column to the value of the void ratio, the coefficient of consolidation, volume compressibility, and compressibility of the stabilized soil. After the engineering properties of the peat were determined, consolidation test was performed to observe the effect of the lime-sand column for 1 and 3 curing days with lime percentages of 3 and 6% lime. Tests were then repeated using a different number of lime-sand column. It was observed that the compressibility of the peat soil was reduced using a longer period of curing, a higher percentage of lime, and a higher number of sand columns

2D Fem Analysis of Earth and Rockfill Dams under Seismic Condition

The paper pertains to the seismic analysis of earth and rockfill dams with the aid of MSC_ Nastran (Windows) package. After validation, the package has been used to investigate the dynamic response of Tehri Dam, located in the seismically active region of Himalayas. A 2D FEM analysis is adopted wherein the dam has been modeled as a linear, elastic, non-homogeneous material. The base acceleration data of the Bhuj Earthquake has been used as an input motion. Effect of Poisson’s ratio and the ratio of the canyon length to the height of the dam has been investigated and is reported. Acceleration-time histories reveal that the maximum acceleration occurs at the crest of the dam, and decreases towards the bottom of the dam. Displacement-time histories reveal that the vertical displacement at any locations of the dam is negligibly small compared to the horizontal displacement. The shear stresses evaluated displays a maximum and minimum magnitude at the shell and core of the dam respectively. Velocity-time history shows a maximum velocity in the forward direction at the crest of the dam, while in the reverse direction, the same is experienced by the shell and the core of the dam supplemented by a noticeable phase difference

Determination of pavement thickness based on threshold stress of the subgrade soil

This paper presents the threshold stress determination to determine the pavement thickness. This design method is based on maintaining the maximum deviator stress induced from traffic loadings on top of the sub-grade below the threshold stress of the subgrade by providing a suitable pavement layer thickness. The design method is intended to achieve a stable deformation behavior of the subgrade soil under repeated loadings, thus limiting plastic deformation. This method has significant advantages over existing ones. It is applicable to the various soil types, different surfaces, base and subbase qualities. The effects of surface and base qualities are isolated from the formation quality, and can be readily presumed and determined. A simple laboratory test procedure for quick evaluation of the threshold stress of the subgrade soil is suggested. A flow chart is given for the systematic formation design along with a suitable example. The importance of drainage conditions for the success of this approach is emphasized. The design method is evaluated by observing the performance of an actual formation under repeated load applications

A rational approach for the design of highway formations

No abstrac

A generic sensor fusion problem: Classification and function estimation

Abstract. A generic fusion problem is studied for multiple sensors whose outputs are probabilistically related to their inputs according to unknown distributions. Sensor measurements are provided as iid input-output samples, and an empirical risk minimization method is described for designing fusers with distribution-free performance bounds. The special cases of isolation and projective fusers for classifiers and function estimators, respectively, are described in terms of performance bounds. The isolation fusers for classifiers are probabilistically guaranteed to perform at least as good as the best classifier. The projective fusers for function estimators are probabilistically guaranteed to perform at least as good as the best subset of estimators.