A Comparative Study of the Atmospheric Layers below First Lifting Condensation Level for Instantaneous Pre-Monsoon Thunderstorm Occurrence at Agartala (23o30’N, 91o15’E) and Ranchi (23o14’N, 85o14’E) of India

An attempt has been made to investigate the role of vertical wind shear, corrective instability and the thermodynamic parameter (θes - θe) below the first lifting condensation level (FLCL) in the occurrence of instanta-neous premonsoon thunderstorm over Agartala (AGT) and Ranchi (RNC) at 12 GMT Radiosonde data of 1988 have been utilized here. The study has however been confined to 1000 hPa-500 hPa range at most Here the convectively unstable layers with positive vertical wind shear upto 500 hPa have been termed as ‘Fa?vourable Layers’ (FL) and the level at which an initially stable layer turns out to be convectively unstable for the first time has been termed as ‘Transition Level’ (TL). It is observed that the changes in vertical wind shear are positive at TL at the time of occurrence of thunderstorm (TS) and the corresponding change is negative on fair-weather situa?tion Moreover, the 90% confidence interval for (θes - θe) reveals that for AGT the upper layer thermodynamic characteristic is important at the time of occurrence of TS whereas for RNC, the value of (θes - θe) at the surface is much more effective     

Development of CityGML Application Domain Extension for Indoor Routing and Positioning

CityGML is an open data model for storage and exchange of 3D city models. It is categorised into thirteen thematic classes, i.e., buildings, tunnels, bridges, etc., lacking the other themes such as indoor routing and positioning. With the amplified use of indoor routing and positioning, the need for prerequisite notion of detailed semantic, as well as geometric information of the 3D building data has grown. We intend to extend the CityGML schema to add attributes of indoor features using the facility of Application Domain Extension (ADE) provided by the OGC CityGML 2.0. In this study, we aim to showcase the formation of Indoor Routing and Positioning ADE along with the process concerning its development, such as the 3D model design, network dataset creation, routing, positioning and Unified Modeling Language based ADE application schema generation. This research would help the users to easily store and exchange 3D city data on which they can perform routing and positioning inside the buildings with enhanced semantic and geometric properties.     

Observations of enhanced sub-iron (Sc-Cr) to iron abundance ratios in the low energy galactic cosmic rays in Spacelab-3 and their implications

The Anuradha cosmic ray experiment in Spacelab-3, flown in the orbit at 350 km with an inclination of 57° for about six days, was used to measure the low energy galactic cosmic ray (GCR) heavy ions using a specially designed CR-39 detector module incorporating the arrival time information of the particles. The abundances of sub-iron (Sc-Cr) and iron particles in the low energy interval of 30–300 MeV/N were determined from the measurements made in four different depths of the CR-39 detector module of 150 layers. From these studies we obtained sub-iron (Sc-Cr) to iron abundance ratios of 0.8 to 1.2 in 30–300 MeV/N energy range. It is found that these ratios are enhanced by a factor of two as compared to interplanetary ratios of about 0.5. It is shown that the enhancement of the ratio inside the earth’s magnetosphere is probably due to the degree of ionization of low energy Sc to Cr and Fe ions in the galactic cosmic rays and to the rigidity filtering effects of the geomagnetic field. Further studies are needed to understand fully the phenomena and their implications.     

Design and Optimization of a Ground Water Monitoring System Using GIS and Multicriteria Decision Analysis

A GIS-based methodology has been developed to design a ground water monitoring system and implemented for a selected area in Mae-Klong River Basin, Thailand. A multicriteria decision-making analysis has been performed to optimize the network system based on major criteria which govern the monitoring network design such as minimization of cost of construction, reduction of kriging standard deviations, etc. The methodology developed in this study is a new approach to designing monitoring networks which can be used for any site considering site-specific aspects. It makes it possible to choose the best monitoring network from various alternatives based on the prioritization of decision factors.     

Determination of run-off factor of the Tons Catchment using aerial photographs

Run-off is an important element of the hydrologic studies of any given basin. As such the estimation of the run-off factor of a catchment becomes imperative for determination of the total quantity of its surface run-off. The traditional ground survey methods of hydrologic studies of river basins are gradually getting replaced by more economical and reasonably accurate methods mostly based on aerial photographs. This paper deals with an experiment carried out on the Tons Catchment for determination of its run-off factor with the help of aerial photographs using the photo-interpretation and analysis techniques. The resultant values of the surface runoff have compared very well with the observed flow at Kisau gauging station. This indicates that a suitable methodology can be developed to estimate the discharge of the catchment of Indian rivers, where the run-off data is not available, with reasonable accuracy using the aerial photographs.     

Motion in a non-homogeneous elastic medium by a twisting impulsive force on the surface of a spherical cavity

Summary In this paper, the propagation of disturbance due to a twisting impulsive force on the surface of a spherical cavity, in a non-homogeneous isotropic medium, in which the rigidity and density vary inversely as the distance from the centre is investigated. Numerical solution is done by the method suggested byKromm.     

Influence of Shear Strain on the Poisson’s Ratio of Clean Sands

In the present study, a series of resonant column tests was performed to determine the influence of confining pressure, shear strain and relative density on the dynamic properties and Poisson's ratio of poorly graded clean sand. The tests were performed on the sand specimens of size 50 × 100 mm compacted at relative densities 30, 50 and 75 %. To achieve the corresponding relative density, sand was compacted in 5 equal layers with a specific number of blows. A fixed-free type resonant column apparatus was used to determine the dynamic soil properties at various confining pressures. It has been inferred from the data that the shear modulus (\(G\)) increases with an increase in confining pressure and relative density; and decreases with an increase in shear strain. In addition, damping ratio (\(D\)) decreases with an increase in confining pressure and relative density; and increases with an increase in shear strain. In addition, Poisson’s ratio (\(\nu\)) decreases with an increase in confining pressure and relative density and increases with an increase in the shear strain. The variation of shear modulus with Poisson’s ratio is also discussed. It has been found that there has been a decrease in shear modulus with an increase in Poisson’s ratio of the soil. It is noticed that the small strain shear modulus determined from the present study closely matches with the value determined using the correlations from the literature.     

Sparse Data Division Using Data Segmentation and Kohonen Network for Neural Network and Geostatistical Ore Grade Modeling in Nome Offshore Placer Deposit

In this paper, sparse data problem in neural network and geostatistical modeling for ore-grade estimation was addressed in the Nome offshore placer gold deposit. The problem of sparse data arises because of the random data division into training, validation, and test subsets during ore-grade modeling. In this regard, the possibility of generating statistically dissimilar data subsets by random data division was also explored through a simulation exercise. A combined approach of data segmentation and application of a Kohonen network then was used to solve the data division problem. Two neural networks and five kriging models were applied for grade modeling. The neural network was trained using an early stopping method. Performance evaluation of the models was carried out on the test data set. The study results indicated that all the models that were investigated in this study performed almost equally. It was also revealed that by using the secondary variable watertable depth the neural network and the kriging models slightly improved their prediction precision. Further, the overall R ² of the models was poor as a result of high nugget (noisy) component in ore-grade variation.