G. L. Sivakumar Babu

Bio: G. L. Sivakumar Babu is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Bearing capacity & Geotechnical engineering. The author has an hindex of 29, co-authored 206 publications receiving 2865 citations. Previous affiliations of G. L. Sivakumar Babu include Indian Institute of Technology Bhubaneswar.

Strength and Stiffness Response of Coir Fiber-Reinforced Tropical Soil

Abstract: Use of natural fibers in civil engineering construction practice is often advantageous as they are cheap, locally available, biodegradable, and ecofriendly. Among the available natural fibers, coir is produced in large quantities in South Asian countries, such as India, Ceylon, Indonesia, Philippines, etc. and has better mechanical properties, such as tensile strength. In this paper, results on the strength and stiffness behavior of soil reinforced with coir fibers are presented. Soil samples reinforced with coir fibers of different sizes, and made into cylindrical soil specimens were tested in triaxial shear apparatus to determine the strength and stiffness of soil response due to fiber inclusion and the results were compared with that of unreinforced soils. The results show that addition of coir (1-2%) as random reinforcing material increases both strength and stiffness of clay soil considered in the study. In addition, available theoretical models for prediction of strength of fiber-reinforced soil are examined in relation to the results of the present investigation. Analysis shows that the available models are not adequate to capture the strength and stiffness response of coir fiber-reinforced soil. A nonlinear regression model for strength and stiffness response is proposed in the present study.

Influence of spatial variability of permeability property on steady state seepage flow and slope stability analysis

Abstract: In recent years, spatial variability modeling of soil parameters using random field theory has gained distinct importance in geotechnical analysis. In the present Study, commercially available finite difference numerical code FLAC 5.0 is used for modeling the permeability parameter as spatially correlated log-normally distributed random variable and its influence on the steady state seepage flow and on the slope stability analysis are studied. Considering the case of a 5.0 m high cohesive-frictional soil slope of 30 degrees, a range of coefficients of variation (CoV%) from 60 to 90% in the permeability Values, and taking different values of correlation distance in the range of 0.5-15 m, parametric studies, using Monte Carlo simulations, are performed to study the following three aspects, i.e., (i) effect ostochastic soil permeability on the statistics of seepage flow in comparison to the analytic (Dupuit's) solution available for the uniformly constant permeability property; (ii) strain and deformation pattern, and (iii) stability of the given slope assessed in terms of factor of safety (FS). The results obtained in this study are useful to understand the role of permeability variations in slope stability analysis under different slope conditions and material properties. (C) 2009 Elsevier B.V. All rights reserved.

Numerical simulation of fiber-reinforced sand behavior

Abstract: This paper reports the results of triaxial compression tests on sand reinforced with coir fibers and demonstrates that fibers are useful in increasing the shear strength of sand. An approach for considering the effect of random-oriented fibers in numerical analysis is proposed and the results of numerical simulations are reported. Numerical simulation results are compared with those obtained from laboratory triaxial compression tests. The mechanisms by which random fibers reinforce sand are explained in terms of microstructure that prevents the formation of distinct localized strain bands and increases pull-out resistance.

Effect of soil spatial variability on the response of laterally loaded pile in undrained clay

Abstract: A comprehensive study is performed on the allowable capacity of laterally loaded pile embedded in undrained clay having spatial variation of strength properties. Undrained shear strength is considered as a random variable and the analysis is conducted using random field theory. The soil medium is modeled as two-dimensional non-Gaussian homogeneous random field using Cholesky decomposition technique. Monte Carlo simulation approach is combined with finite difference analysis. Statistics of lateral load capacity and maximum bending moment developed in the pile for a specified allowable lateral displacement as influenced by variance and spatial correlation length of soil’s undrained shear strength are investigated. The observations made from this study help to explain the requirement of allowable lateral capacity calculations in probabilistic framework.

Use of Coir Fibers for Improving the Engineering Properties of Expansive Soils

Abstract: A large part of Central India and a portion of South India are covered with black cotton soils. These soils have high swelling and shrinkage characteristics and shear strength is extremely low; hence, there is need for improvement of these properties. Coir is a natural biodegradable material abundantly available in some parts of South and coastal regions of India. The paper reports the results of comprehensive experimental investigations using tri-axial shear tests, swelling, and consolidation tests to quantify the improvement of strength, swelling and compressibility characteristics of black cotton soil reinforced with coir fibers in a random manner. This paper discusses the mechanisms of improvement in strength, shrinkage, swelling and compressibility behavior of black cotton soils due to the inclusion of coir fibers. This facilitates the use of combination of black cotton soil and coir fibers for sustainable development purposes.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

A simple review of soil reinforcement by using natural and synthetic fibers

Abstract: Soil reinforcement is defined as a technique to improve the engineering characteristics of soil. In this way, using natural fibers to reinforce soil is an old and ancient idea. Consequently, randomly distributed fiber-reinforced soils have recently attracted increasing attention in geotechnical engineering for the second time. The main aim of this paper, therefore, is to review the history, benefits, applications; and possible executive problems of using different types of natural and/or synthetic fibers in soil reinforcement through reference to published scientific data. As well, predictive models used for short fiber soil composite will be discussed. On other words, this paper is going to investigate why, how, when; and which fibers have been used in soil reinforcement projects.

Influence of spatial variability on slope reliability using 2-D random fields.

Abstract: The paper investigates the probability of failure of slopes using both traditional and more advanced probabilistic analysis tools. The advanced method, called the random finite-element method, uses elastoplasticity in a finite-element model combined with random field theory in a Monte-Carlo framework. The traditional method, called the first-order reliability method, computes a reliability index which is the shortest distance (in units of directional equivalent standard deviations) from the equivalent mean-value point to the limit state surface and estimates the probability of failure from the reliability index. Numerical results show that simplified probabilistic analyses in which spatial variability of soil properties is not properly accounted for, can lead to unconservative estimates of the probability of failure if the coefficient of variation of the shear strength parameters exceeds a critical value. The influences of slope inclination, factor of safety (based on mean strength values), and cross correlation between strength parameters on this critical value have been investigated by parametric studies in this paper. The results indicate when probabilistic approaches, which do not model spatial variation, may lead to unconservative estimates of slope failure probability and when more advanced probabilistic methods are warranted.

A multiple response-surface method for slope reliability analysis considering spatial variability of soil properties

Abstract: This paper proposes a multiple response-surface method for slope reliability analysis considering spatially variable soil properties. The scales of fluctuation of soil shear strength parameters are summarized. The effect of theoretical autocorrelation functions (ACFs) on slope reliability is highlighted since the theoretical ACFs are often used to characterize the spatial variability of soil properties due to a limited number of site observation data available. The differences in five theoretical ACFs, namely single exponential, squared exponential, second-order Markov, cosine exponential and binary noise ACFs, are examined. A homogeneous c–ϕ slope and a heterogeneous slope consisting of three soil layers (including a weak layer) are studied to demonstrate the validity of the proposed method and explore the effect of ACFs on the slope reliability. The results indicate that the proposed method provides a practical tool for evaluating the reliability of slopes in spatially variable soils. It can greatly improve the computational efficiency in relatively low-probability analysis and parametric sensitivity analysis. The extended Cholesky decomposition technique can effectively discretize the cross-correlated non-Gaussian random fields of spatially variable soil properties. Among the five selected ACFs, the squared exponential and second-order Markov ACFs might characterize the spatial correlation of soil properties more realistically. The probability of failure associated with the commonly-used single exponential ACF may be underestimated. In general, the difference in the probabilities of failure associated with the five ACFs is minimal.