SHORT COMMUNICATIONS FLEXURAL CAPACITY OF EDGE LOADED ANNULAR FOUNDATIONS

Edge loaded annular foundations have been analysed assuming the soil pressure at the contact to be non-uniform using the lower bound approach of Limit Analysis. Variable fixity at the edges has been allowed and the foundation slab is made to follow the Square yield criterion. Results presented in the form of curves can be readily used to obtain the locations of the yield hinge circles for the given slab and the corresponding collapse load. © 1997 John Wiley & Sons, Ltd.     

Effects of linear and exponential heterogeneity on the dynamic response of a moving load in an irregular isotropic half-space: a comparative study

Heterogeneity, being a trivial feature inside the earth or in a geostructure, makes a strong basis for its consideration in the study of geomechanics. Inclusion of the concept of heterogeneity along with irregularity in the medium brings a novelty to the existing literature related to the study of the moving load. The present study investigates the effects of linear and exponential heterogeneity on the dynamic response due to a normal load moving with constant velocity on a rough irregular heterogeneous isotropic half-space in a comparative approach. Expressions for both normal and shear stresses for either case of heterogeneity have been established in closed form. Substantial effects of the affecting parameters such as depth, irregularity factor, maximum depth of irregularity, frictional coefficient, linear heterogeneity parameter and exponential heterogeneity parameter on normal and shear stresses for both the cases of heterogeneity have been observed. Numerical computation has been carried out and the effects of said parameters have been meticulously examined by means of graphs. Moreover, different cases of heterogeneity and homogeneity along with various types of irregularity namely rectangular, parabolic and no irregularity are compared which serve as a focal theme of the study.     

Impact of 3D Var GSI-ENKF hybrid data assimilation system

The hybrid two-way coupled 3DEnsVar assimilation system was tested with the NCMRWF global data assimilation forecasting system. At present, this system consists of T574L64 deterministic model and the grid-point statistical interpolation analysis scheme. In this experiment, the analysis system is modified with a two-way coupling with an 80 member Ensemble Kalman Filter of T254L64 resolution and runs are carried out in parallel to the operational system for the Indian summer monsoon season (June–September) for the year 2015 to study its impact. Both the assimilation systems are based on NCEP GFS system. It is found that hybrid assimilation marginally improved the quality of the forecasts of all variables over the deterministic 3D Var system, in terms of statistical skill scores and also in terms of circulation features. The impact of the hybrid system in prediction of extreme rainfall and cyclone track is discussed.     

Prediction of fog/visibility over India using NWP Model

Frequent occurrence of fog in different parts of northern India is common during the winter months of December and January. Low visibility conditions due to fog disrupt normal public life. Visibility conditions heavily affect both surface and air transport. A number of flights are either diverted or cancelled every year during the winter season due to low visibility conditions, experienced at different airports of north India. Thus, fog and visibility forecasts over plains of north India become very important during winter months. This study aims to understand the ability of a NWP model (NCMRWF, Unified Model, NCUM) with a diagnostic visibility scheme to forecast visibility over plains of north India. The present study verifies visibility forecasts obtained from NCUM against the INSAT-3D fog images and visibility observations from the METAR reports of different stations in the plains of north India. The study shows that the visibility forecast obtained from NCUM can provide reasonably good indication of the spatial extent of fog in advance of one day. The fog intensity is also predicted fairly well. The study also verifies the simple diagnostic model for fog which is driven by NWP model forecast of surface relative humidity and wind speed. The performance of NWP model forecast of visibility is found comparable to that from simple fog model driven by NWP forecast of relative humidity and wind speed.     

Regional character of induced magnetic variations in India

Variations recorded simultaneously at eight Indian stations during a magnetic storm are analysed to obtain the power spectra for each component using the fast Fourier transform. For two selected peaks, observed for H at all stations, at 49.5- and 70-min periods, a complex demodulation is performed for each component. From the variations thus obtained, horizontal polarization ellipses are drawn for four events of 49.5-min period. The variation of the demodulates and polarization ellipses at the stations shows a regional character which coincides with the physiographic grouping of the stations. Anomalously large Z variations are observed at the equatorial stations, which are near the sea. A distinct feature is the suppression of H at Trivandrum where the polarization ellipses confirm the E-W trend of the induced currents in this region. The overall similarity of the horizontal variations is demonstrated by these ellipses. Horizontal disturbance vectors at Annamalainagar, Trivandrum and Sabhawala confirm channelled currents located previously. At Shillong, the induced effects are evident and the currents are deduced to flow eastward, directly beneath the station.The overall regional similarities in variations are clearly manifested.     

Mechanical response of a piezoelectric composite transducer subjected to a thermal field

Summary The present paper studies the mechanical response of a piezoelectric composite transducer—with an elastic compliance partly constant and partly variable with time—acted upon by suitable thermal field besides the electrical voltage. The Laplace transform has been applied to solve the problem.     

Some theoretical aspects of electric field and precipitation growth in a finite thundercloud

A time-dependent numerical model allowing a simulation of the electric field and precipitation growth in a thundercloud of finite dimensions is described. It is found that slower growth rate (compared to an infinite thundercloud) of the electric field in a finite thundercloud permits larger size growth and higher terminal velocities of hydrometeors owing to an enhancement in precipitation intensity. Calculations also show that a higher maximum of the electric field is needed to slow down the larger particles produced in a thundercloud of finite dimensions. In particular, these solutions also include contribution of screening charge transport in thundercloud electrification.     

Prediction of creep characteristic of rock under varying environment

The strain developed due to creep is mainly proportional to the logarithm of the time under load, and is mostly proportional to the stress and temperature. At higher temperature the creep rate falls slowly with respect to time, and the creep strain is proportional to a fractional power of time, with the exponent increasing as the temperature increases and reaching a value approximately one-third at temperatures of about 0.5°C. At these temperatures, the creep increases with stress according to a power greater than unity and possibly exponentially. It increases with temperature as (−U/kT), where U is an activation energy and k is Boltzman’s constant. There are different methods to determine the creep strain and the energy of Jog (B) including experimental methods, multivariate regression analysis, and by numerical simulation. These methods are less cumbersome and time consuming. In the present investigation, artificial neural network technique has been used for prediction of the creep strain and energy of Jog (B). Two different networks have been tested and validated. Both the networks have four input neurons and one hidden layer with five neurons, and one output neuron. The data for different rocks at temperatures up to 750°C under conditions of compressive or tortional stress are taken from the literatures. The training and testing data sets used were 163 and 14, respectively. To deal with the problem of overfitting of data, Bayesian regulation has been used and network is trained with suitable training epochs. The coefficients of correlation among the predicted and observed values are found high and they improve the confidence of the users. The mean absolute percentage error obtained are also very low.