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American Society for Testing and Materials

Statistics and Data Analysis in Geology

Discrete particle simulation of particulate systems: A review of major applications and findings


 The spectral ratio between horizontal and vertical components (H/V ratio) of microtremors measured at the ground surface has been used to estimate fundamental periods and amplification factors of a site, although this technique lacks theoretical background. The aim of this article is to formulate the H/V technique in terms of the characteristics of Rayleigh and Love waves, and to contribute to improve the technique. The improvement includes use of not only peaks but also troughs in the H/V ratio for reliable estimation of the period and use of a newly proposed smoothing function for better estimation of the amplification factor. The formulation leads to a simple formula for the amplification factor expressed with the H/V ratio. With microtremor data measured at 546 junior high schools in 23 wards of Tokyo, the improved technique is applied to mapping site periods and amplification factors in the area.

Ground Motion Characteristics Estimated from Spectral Ratio between Horizontal and Verticcl Components of Mietremors.

A review of the recent advances on the treatment of industrial wastewaters by Sulfate Radical-based Advanced Oxidation Processes (SR-AOPs)

The wave propagation in jointed rock mass depends on many factors, in particular the wave frequency, existing stress conditions and the induced strain levels. When the wavelength of the propagating wave is much longer than the spacing of the joints, it is referred to as long-wavelength condition. This is a dominant condition in seismological studies due to the presence of closely spaced joints in rocks. A comprehensive study on long-wavelength propagation of shear and compression waves in very weak rocks has been carried out with the help of a resonant column apparatus using a model material (plaster of Paris) at various strain levels. The working principle and suitability of the apparatus for testing stiff samples are discussed. The velocity reductions of shear and compression waves across joints are obtained. The influence of frictional and filled joints in attenuating stress waves under various strain levels is analysed. Wave velocities are found to be reduced with increasing strain levels and ...

Long-wavelength propagation of waves in jointed rocks - study using resonant column experiments and model material

Very often it is difficult to develop mechanistic models for pavement geotechnical engineering problems due to its complex nature and uncertainty in material parameters. The difficulty in mechanistic analysis has forced the engineers to follows certain empirical correlations. The artificial neural network (ANN) is being as an alternate statistical method, mapping in higher-order spaces, such models can go beyond the existing univariate relationships. The applications of ANNs in pavement geotechnical engineering problems is mostly limited to constitutive modeling, with few applications on prediction of soil layer properties using Falling Weight Deflectometer (FWD), prediction of swelling potential and compute the remaining life of flexible pavements. However, ANN is considered as a ‘Black box’ system being unable to explain interrelation between inputs and output. The ANNs also have inherent drawbacks such as slow convergence speed, less generalizing performance, arriving at local minimum and over-fitting problems. Recently support vector machine (SVM) is being used due to its, better generalization as prediction error and model complexity are simultaneously minimized. SVM is based on statistical learning theory unlike ANNs (biological learning theory). The application of SVM in pavement geotechnical engineering is very much limited and to best of the knowledge such methods have not been applied to pavement geotechnical engineering. However, engineering application of numerical methods is a science as well as an art. This juxtaposition is based on the fact that even though the developed algorithms are based on scientific logic and belong to the special branch of applied mathematics, their successful application to new problems is problem oriented and is an art. As no method can be the panacea to solve all problems to the last details, their application to new areas needs critical evaluation. With above in view, an attempt has been made to develop the art of applying the above artificial intelligence techniques (ANN and SVM) to different pavement engineering problems such as prediction of compaction characteristics, permeability, swelling potential, coefficient of subgrade reaction etc. The parameters associated with the model developments are discussed in terms of guide line for its future

Application of Soft Computing Techniques to Expansive Soil Characterization

In metropolitan cities, public transportation service plays a vital role in mobility of people, and it has to introduce new routes more frequently due to the fast development of the city in terms of population growth and city size. Whenever there is introduction of new route or increase in frequency of buses, the nonrevenue kilometers covered by the buses increases as depot and route starting/ending points are at different places. This non-revenue kilometers or dead kilometers depends on the distance between depot and route starting point/ending point. The dead kilometers not only results in revenue loss but also results in an increase in the operating cost because of the extra kilometers covered by buses. Reduction of dead kilometers is necessary for the economic growth of the public transportation system. Therefore, in this study, the attention is focused on minimizing dead kilometers by optimizing allocation of buses to depots depending upon the shortest distance between depot and route starting/ending points. We consider also depot capacity and time period of operation during allocation of buses to ensure parking safety and proper maintenance of buses. Mathematical model is developed considering the aforementioned parameters, which is a mixed integer program, and applied to Bangalore Metropolitan Transport Corporation (BMTC) routes operating presently in order to obtain optimal bus allocation to depots. Database for dead kilometers of depots in BMTC for all the schedules are generated using the Form-4 (trip sheet) of each schedule to analyze depot-wise and division-wise dead kilometers. This study also suggests alternative locations where depots can be located to reduce dead kilometers. Copyright (C) 2015 John Wiley & Sons, Ltd.

Optimization of bus allocation to depots by minimizing dead kilometers

Probabilistic seismic hazard assessment

In this paper, the possibility of using naturally available low-cost areca leaf sheaths as an alternative to the commercially available HDPE geocell has been explored by conducting the laboratory m...

T. G. Sitharam

Papers

Long-wavelength propagation of waves in jointed rocks - study using resonant column experiments and model material

Application of Soft Computing Techniques to Expansive Soil Characterization

Optimization of bus allocation to depots by minimizing dead kilometers

Probabilistic seismic hazard assessment

Model Tests and Analytical Studies on Performance of Areca Leaf Cells as Cellular Confinement in Soil