Stability analysis of an open cut slope in Wardha valley coal field

Open cast mines are the prime source of coal production in India. Due to an increase in coal demand, deeper surface mines are being planned to ensure better productivity with enhanced safety of these mines. The safe working environment and continuous production of the coal calls for the safe and stable design of cut slopes. The stability analysis of this slope requires in depth geotechnical investigation which are aided by result orientated stability assessment using empirical methods and numerical simulation. In the present study, a slope was examined to understand the mechanism and comparisons were made with field observations. The investigation has involved a 32m high cut slope from an open cast mine in Wardha valley coal field which has been analyzed using a two dimensional numerical simulation. The bench slope consisted of a low strength sandstones, shales and clay sequence. Hoek-Brown strength parameters established and used as input parameters in the model. The results indicate that the slope is critically stable and may lead to failure without warning and needs proper attention.     

Salinity Tolerance and Salinity Induced Changes in Ionic and Metabolite Composition in a Penaeid Prawn,Parapenaeopsis sculptilis (Heller)

Summary: Experiments were carried out to study the salinity tolerance and the impact of salinity changes on ions and metabolite in the body of a marine penaeid prawn, Parapenaeopsis sculptilis. Juveniles of this prawn species have a comparatively wide range of salinity tolerance than adults. Juveniles can tolerate 60 … 100 %, but adults only 100 % seawater concentrations. Behavioural observations showed that the juvenile and adult prawns became inactive with decrease in seawater concentrations followed by paralysis and death. Death occurred probably due to failure of the neuromuscular system. A highly significant variation existed in the amount of sodium, potassium and calcium ions in juveniles as well as adults. Exposure to different seawater concentrations probably caused breakdown of the osmoregulatory mechanism in the prawn body. Protein and carbohydrate decreased in both juvenile and adult prawn body, with the decrease in seawater concentrations indicating the utilization of large amounts of protein and carbohydrate from the internal reserve.     

Direct Numerical Simulation of a Turbulent Channel Flow with Forchheimer Drag

Boundary-Layer Meteorology - We characterize the turbulent flow, using direct numerical simulations (DNS), within a closed channel between two parallel walls with a canopy of constant areal density...     

Risk characterization and surface water quality assessment of Manas River,Assam (India) with an emphasis on the TOPSIS method of multi-objective decision making

The present study centers on the investigation of surface water quality with the aid of quality indices and explores the application of a multi-objective decision-making method (TOPSIS) in arranging decisions for policy makers on the basis of overall ranking of the sampling locations. A case study has been performed on the Manas River, Assam (India). Water Quality Index (WQI) involving physico-chemical parameters, and heavy metal pollution index (HPI) and contamination index (CI) involving heavy metal influences were employed for water quality assessment. WQI graded two sampling locations “very poor” and all other locations “poor”. HPIs of all the locations were below the critical value of 100, but the CI depicted that two locations were “moderately contaminated”. Risk assessment to human health was done using hazard quotient and hazard index. Cluster analysis (CA) demonstrated site similarity by grouping the relatively more polluted and less polluted (LP) sites into two major clusters. However, there surfaced difficulty in discerning the overall water quality, as all the three quality indices included different parameters and contradicted each other. A multi-objective decision-making tool, TOPSIS was therefore employed for ranking the locations on the basis of their relative pollution levels. The novelty of the study reflects in the identification of the relatively more or relatively less polluted sites within the same cluster in CA by the application of TOPSIS. The study justifies the effectiveness of TOPSIS method in prioritizing decisions in complex scenarios for policy makers.     

Performance analysis of different predictive models for crop classification across an aridic to ustic area of Indian states

The purpose of this study is to present comparative performance analysis of different machine learning algorithms for large area crop classification. Ten Indian districts with significant rabi crops viz. wheat, mustard, gram, red lentils (masoor) have been selected for the study. Most popular classical ensemble models – bagging/ARCing, random forest (RF), gradient boosting and Importance Sampled Learning Ensemble (ISLE) with traditional single model (decision tree) have been selected for comparative analysis. To incorporate dependency of large area crop in different variables viz. parent material and soil, phenology, texture, topography, soil moisture, vegetation, climate etc., 35 digital layers are prepared using different satellite data (ALOS DEM, Landsat-8, MODIS NDVI, RISAT-1, Sentinental-1A) and climatic data (precipitation, temperature). In rabi season, field survey about crop type is carried out to prepare training data. Performance is evaluated on the basis of marginal rates, F-measure and Jaccard’s coefficient of community, Classification Success Index and Agreement Coefficients. Score is calculated to rank the algorithm. RF is best performer followed by gradient boosting for crop classification. Other ensemble methods ARCing, bagging and ISLE are in decreasing order of performance. Traditional non-ensemble method decision tree scored higher than ISLE.     

A Hybrid CNN + Random Forest Approach to Delineate Debris Covered Glaciers Using Deep Features

The main aim of this study is to propose a novel hybrid deep learning framework approach for accurate mapping of debris covered glaciers. The framework comprises of integration of several CNNs architecture, in which different combinations of Landsat 8 multispectral bands (including thermal band), topographic and texture parameters are passed as input for feature extraction. The output of an ensemble of these CNNs is hybrid with random forest model for classification. The major pillars of the framework include: (1) technique for implementing topographic and atmospheric corrections (preprocessing), (2) the proposed hybrid of ensemble of CNNs and random forest classifier, and (3) procedures to determine whether a pixel predicted as snow is a cloud edge/shadow (post-processing). The proposed approach was implemented on the multispectral Landsat 8 OLI (operational land imager)/TIRS (thermal infrared sensor) data and Shuttle Radar Topography Mission Digital Elevation Model for the part of the region situated in Alaknanda basin, Uttarakhand, Himalaya. The proposed framework was observed to outperform (accuracy 96.79%) the current state-of-art machine learning algorithms such as artificial neural network, support vector machine, and random forest. Accuracy assessment was performed by means of several statistics measures (precision, accuracy, recall, and specificity).     

Moisture rainout fraction over the Indian Ocean during austral summer based on $$^{18}\hbox {O}/{}^{16}\hbox {O}$$ ratios of surface seawater,rainwater at latitude range of 10°N–60°S

Oxygen isotope ratios (\(^{18}\hbox {O}/^{16}\hbox {O}\)) of surface seawater and rainwater samples from the Indian Ocean region (10°N–60°S) during austral summer collected onboard ORV Sagar Nidhi during 2011–2013 have been measured along with salinity, sea surface temperature and relative humidity. The rainwater is isotopically lighter (by \(4.6\pm 2.7\permille )\) compared to the equilibrium condensation of the vapour arising from the seawater at the ambient condition. The isotopic composition of the vapour at high altitude responsible for the rain formation at the sampling location is estimated from a global atmospheric water isotope model (IsoGSM2). The apparent deficit of \(\sim \)5\(\permille \) can be explained by invoking a high degree of rainout (on average, about 70% of the overhead atmospheric moisture) during transport of the source vapour to the sampling location undergoing a Rayleigh fractionation. The required rainout fraction is higher (\(\sim \)80%) in the latitude belt 40°–60°S compared to the equatorial belt (\(\sim \)60%). The pattern of variation in the rainout fraction with latitude is consistent with the well-known evaporation/precipitation processes in the Indian Ocean.     

Geochemistry of the Palaeo–Mesoproterozoic Tadpatri shales,Cuddapah basin,India: implications on provenance,paleoweathering and paleoredox conditions

The Palaeo–Mesoproterozoic Tadapatri formation of the Cuddapah basin is comprised of clastic sedimentary rocks with minor carbonates and mafic–ultramafic sill bodies. Geochemistry of the shale is used to study the provenance, paleoweathering and paleoredox conditions of this Tadpatri formation in order to better understand the development of the Cuddapah basin during Palaeo–Mesoproterozoic time. The higher CIA (average 74.39), PIA (average 85.94) and CIW (average 87.59) values of the Tadpatri shales suggest intensely weathered sources. Higher Al₂O₃/TiO₂ (average 30.78) and LREE/HREE ratio (average 8.80) with negative europium anomaly indicate derivation of the clastic sediments from a felsic source rock. The geochemical parameters like U, U/Th, Cu/Zn, Ni/Co, V/Cr ratios reveal that the Tadpatri shales are mainly deposited in an oxic condition.     

Assessment of Impact on Seafloor Features in INDEX Area

Observations on seafloor features from subbottom profiling and seabed photography data show that the undisturbed and natural conditions before the benthic disturbance undergo a substantial change after operation of the disturber. The effects can be seen in the form of deep trenches and grooves, formed by the action of the sleds and the pumping of the sediment along its path, as well as sediment piles on either side of the track. Biological traces such as fecal coils, casts, tubes, burrows, and trails get obliterated in the areas of disturbance and resedimentation. The smooth, uniform nature of the seafloor observed in predisturbance phase shows microtopographic changes in and around the disturbed area as a result of sediment excavation and resettlement. Vertical mixing as well as lateral transport of sediment alter the geological, biological, physical, and chemical conditions on the seafloor, which need to be monitored over time to assess the process and the time taken for restoration of environmental conditions.