Cuttability assessment of hard coal seams

Summary A number of field and laboratory tests have been carried out on more than 15 coal seams of compressive strengths ranging from 19 MPa to 44 MPa to evolve methods which would help in the selection of suitable coaling machines for hard coal seams. The effect of physico-mechanical properties on cuttability were studied in the laboratory for all these coal seams to identify the relevant parameters affecting the specific energy of coal cuttability. These data were subjected to regression analysis to find the best fit for estimation of laboratory specific energy of coal samples on the basis of simple laboratory and field tests for the strength parameters. Field studies were also conducted over a large number of active mechanized coal faces to study in situ cuttability along with the geo-mining conditions of the site. The field and the laboratory data so generated were correlated and an attempt is made to establish a relationship for estimating the field specific energy for a particular capacity of coaling machines by considering the geo-mining domain of the field in totality.     

Empirical Orthogonal Function (EOF) analysis of monsoon rainfall and satellite-observed outgoing long-wave radiation for Indian monsoon: a comparative study

Summary The present study involves the use of Empirical Orthogonal Function (EOF) analysis/Principal Component Analysis (PCA) to compare the dominant rainfall patterns from normal rainfall records over India, coupled with the major modes of the Outgoing Long-wave Radiation (OLR) data for the period (1979–1988) during the monsoon period (June–September). To understand the intraseasonal and interannual variability of the monsoon rainfall, daily and seasonal anomalies have been obtained by using the (EOF) analysis. Importantly, pattern characteristics of seasonal monsoon rainfall covering 68 stations in India are highlighted.The purpose is to ascertain the nature of rainfall distribution over the Indian continent. Based on this, the percentage of variance for both the rainfall and OLR data is examined. OLR has a higher spatial coherence than rainfall. The first principal component of rainfall data shows high positive values, which are concentrated over northeast as well as southeast, whereas for the OLR, the area of large positive values is concentrated over northwest and lower value over south India apart from the Indian ocean. The first five principal components explain 92.20% of the total variance for the rainfall and 99.50% of the total variance for the outgoing long-wave radiation. The relationship between monsoon rainfall and Southern Oscillations has also been examined and for the Southern Oscillations, it is 0.69 for the monsoon season. The El-Niño events mostly occurred during Southern Oscillations, i.e. Walker circulation. It has been found that the average number of low pressure system/low pressure system days play an important role during active (flood) or inactive (drought) monsoon year, but low pressure system days play more important role in comparison to low pressure systems and their ratio are (16:51) and (13:25) respectively. Significantly, the analysis identifies the spatial and temporal pattern characteristics of possible physical significance.     

Automatic Road Extraction from High Resolution Satellite Image using Adaptive Global Thresholding and Morphological Operations

Road network extraction from high resolution satellite images is one of the most important aspects. In the present paper, research experimentation is carried out in order to extract the roads from the high resolution satellite image using image segmentation methods. The segmentation technique is implemented using adaptive global thresholding and morphological operations. Global thresholding segments the image to fix the boundaries. To compute the appropriate threshold values several problems are also analyzed, for instance, the illumination conditions, the different type of pavement material, the presence of objects such as vegetation, vehicles, buildings etc. Image segmentation is performed using morphological approach implemented through dilation of similar boundaries and erosion of dissimilar and irrelevant boundaries decided on the basis of pixel characteristics. The roads are clearly identifiable in the final processed image, which is obtained by superimposing the segmented image over the original enhanced image. The experimental results proved that proposed approach can be used in reliable way for automatic detection of roads from high resolution satellite image. The results can be used in automated map preparation, detection of network in trajectory planning for unmanned aerial vehicles. It also has wide applications in navigation, computer vision as a predictor-corrector algorithm for estimating the road position to simulate dynamic process of road extraction. Although an expert can label road pixels from a given satellite image but this operation is prone to errors. Therefore, an automated system is required to detect the road network in a high resolution satellite image in a robust manner.     

Study of seasonal variation of PM2.5 concentration associated with meteorological parameters at residential sites in Delhi,India

The seasonal variation of particulate matter and its relationship with meteorological parameters were measured at five different residential sites in Delhi. Sampling was carried out for one year including all three seasons (summer, monsoon, and winter). The yearly average concentration of particulate matter (PM_2.5) was 135.16 ± 41.34 µg/m³. The highest average values were observed in winter (208.44 ± 43.67 µg/m³) and the lowest during monsoon season (80.29 ± 39.47 µg/m³). The annual average concentration of PM_2.5 was found to be the highest at the Mukherjee Nagar site (242.16 µg/m³ ) during the winter and lowest at (Jawaharlal Nehru University) JNU (35.65 µg/m³) during the monsoon season. The strongest correlation between PM mass and a meteorological parameter was a strong negative correlation with temperature (R2=0.55). All other parameters were weakly correlated (R2<0.2) with PM mass.

     

Analysis of earth dams affected by the 2001 Bhuj Earthquake

An earthquake of magnitude of 7.6 (M_w 7.6) occurred in Bhuj, India on January 26, 2001. This event inflicted damages of varying extents to a large number of small to moderate size multi-zone earth dams in the vicinity of the epicenter. Some of the distress was due to the liquefaction of saturated alluvium in foundation. Liquefaction was relatively localized for the majority of these dams because the earthquake struck in the middle of a prolonged dry season when the reservoirs behind these dams were nearly empty and shallow alluvium soils underneath the downstream portions of the dams were partly dry. Otherwise, liquefaction of foundation soils would have been more extensive and damage to these dams more significant. Six such dams have been examined in this paper. Four of these facilities, Chang, Shivlakha, Suvi, and Tapar were within the 50 km of epicenter region. These dams underwent free-field ground motion with peak ground accelerations between 0.28g to 0.52g. Of these Chang Dam underwent severe slumping, whereas Shivlakha, Suvi, and Tapar Dams were affected severely especially over the upstream sections. Fatehgadh Dam and Kaswati Dam were affected relatively less severely. Foundation conditions underneath these dams were first examined for assessing liquefaction potential. A limited amount of subsurface information available from investigations undertaken prior to the earthquake indicates that, although the foundation soils within the top 2.0 to 2.5 m underneath these dams were susceptible to liquefaction, Bhuj Earthquake did not trigger liquefaction because of lack of saturation of these layers underneath the downstream portions of these dams. These dams were then analyzed using a simple sliding block procedure using appropriate estimates of undrained soil strength parameters. The results of this analysis for these structures were found to be in general agreement with the observed deformation patterns.     

Characteristics of spectral aerosol optical depths over India during ICARB

Spectral aerosol optical depth (AOD) measurements, carried out regularly from a network of observatories spread over the Indian mainland and adjoining islands in the Bay of Bengal and Arabian Sea, are used to examine the spatio-temporal and spectral variations during the period of ICARB (March to May 2006). The AODs and the derived Ångström parameters showed considerable variations across India during the above period. While at the southern peninsular stations the AODs decreased towards May after a peak in April, in the north Indian regions they increased continuously from March to May. The Ångström coefficients suggested enhanced coarse mode loading in the north Indian regions, compared to southern India. Nevertheless, as months progressed from March to May, the dominance of coarse mode aerosols increased in the columnar aerosol size spectrum over the entire Indian mainland, maintaining the regional distinctiveness. Compared to the above, the island stations showed considerably low AODs, so too the northeastern station Dibrugarh, indicating the prevalence of cleaner environment. Long-range transport of aerosols from tshe adjoining regions leads to remarkable changes in the magnitude of the AODs and their wavelength dependencies during March to May. HYSPLIT back-trajectory analysis shows that enhanced long-range transport of aerosols, particularly from the west Asia and northwest coastal India, contributed significantly to the enhancement of AOD and in the flattening of the spectra over entire regions; if it is the peninsular regions and the island Minicoy are more impacted in April, the north Indian regions including the Indo Gangetic Plain get affected the most during May, with the AODs soaring as high as 1.0 at 500 nm. Over the islands, the Ångström exponent (α) remained significantly lower (～1) over the Arabian Sea compared to Bay of Bengal (BoB) (～1.4) as revealed by the data respectively from Minicoy and Port Blair. Occurrences of higher values of α, showing dominance of accumulation mode aerosols, over BoB are associated well with the advection, above the boundary layer, of fine particles from the east Asian region during March and April. The change in the airmass to marine in May results in a rapid decrease in α over the BoB.     

Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India

This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network (ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality of the ANN technique in mapping the liquefaction susceptibility of the area.     

Dynamic Subsidence Characteristics in Jharia Coalfield,India

Surface ground movements are usually described by a number of characteristic indices such as vertical displacement, horizontal strain and slope, which are an inevitable consequence of underground mining. Every point at the surface over a panel is subjected to strain and slope during mining and its investigation is essential to assess the safety of surface structures. Therefore, the behaviour of dynamic active and residual subsidence was studied for a few panels of Jharia coalfield. The subsidence and slope were linearly related to time. Compressive and tensile strains showed typical fluctuating characteristic behaviour. The rate of mining being a key and controlling parameter for rate of subsidence their inter-relationship was developed, which showed a rational trend. Compressive and tensile strains and slope showed poor correlation with rate of face advance.     

Quantification of stability improvement of a dump through biological reclamation

An integrated study on biological stabilisation of a dump slope has indicated that biological reclamation with grass and tree species should be considered for long term stability of this coal mine dump in India. The grasses have greater soil binding capacity and help to control soil erosion and improve dump stability. Native grasses such as Bamboo (Dendrocalmus strictus) and Kashi (Saccharum spontaneum) are the important constituents of grass species which can stabilise the dump slopes. Field observation of growth performance of grasses have indicated that mean grass height, root depth and below-ground root biomass are 185 cm (±68), 45 cm (±5) and 467 g m^–2 (±170), respectively after three years of grass growth on Mudidih overburden dump slope in India. The growth performance of tree species, namely Sisum (Dalbergia sisoo) and Subabool (Leucena lecocephala), in terms of height, diameter increment, below-ground biomass and root depth have shown mean values of 219 cm (±94), 48 mm (±6), 4.0 kg m^–2 (±1.5) and 1 m (±0.1), respectively. This acts as biological fertility which helps in root proliferation and enhancement of dump stability. From the numerical modelling it is suggested that roots of these grass and tree species have significantly enhanced the factor of safety of dump from 1.4 to 1.8 and therefore have a positive role in maintaining long term stability.