IR@CIMFR - Central Institute of Mining and Fuel Research (CSIR)
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CHANNEL MIGRATION AND CONSEQUENTIAL LAND USE LAND COVER CHANGES OF SUBANSIRI RIVER, ASSAM, NORTH-EASTERN INDIA
No full textSubansiri River is the largest tributary of the Brahmaputra River running through the Indian states of Assam and Arunachal Pradesh, and Tibet, the Autonomous Region of China. The Subansiri River is 442 km long with a drainage basin of 32,640 km2 and it contributes approximately 7.92% of the Brahmaputra's total flow. Sequential Channel shifting has been witnessed as the most important characteristic of the Subansiri River of Assam. The detailed study on channel migration of the present course of the Subansiri River through the upper floodplain of Brahmaputra valley indicates that the area is under active erosion for a long time. Therefore, an attempt has been made to understand the relationship between the rate of channel migration and successive land use/land cover changes in its surrounding floodplain area. The Support Vector Machine (SVM) and the Artificial Neural Network (ANN) algorithms are applied on Landsat images of the years 1973, 1988, 2001, and 2017 for generating land use/land cover maps through supervised classification technique. The overall accuracy of the land use/land cover classification ranges between 81% (for the year 1988) and 84% (for the year 2017). The land use/land cover maps show an increase in the built-up area and a decrease in the agricultural area. The change has been observed vis-a-vis channel migration indicating that the migration directly affects the floodplain habitats which in turn affects the land use, Findings of this study highlight geomorphological instabilities of the study area and the vulnerability of the habitations residing near the Subansiri river
The integration of flexible dye-sensitized solar cells and storage devices towards wearable self-charging power systems: A review
No full textDue to the outstanding high power conversion efficiency and mechanical robustness, photovoltaic systems have become a perfect alternative to traditional sources of energy. This helps in fulfilling the human demand for renewable, inexpensive and compact electricity sources. The production of highly efficient flexible dye-sensitized solar cells (FDSSCs) has sparked a lot of attention in recent years. These FDSSCs are promising energy sources for battery-free and self-powered electronics, which have application in different sectors, including the Internet of Things. Due to the intermittent and unpredictable nature of solar radiation, photoelectric conversion devices fail to satisfy the criteria of constant power output. Owing to the emergence of rechargeable electric energy storage devices, the integration of FDSSCs and rechargeable electric energy storage systems has become a promising approach in solving this problem. This review focused on the recent developments in terms of the materials used to fabricate FDSSCs along with the working principle, challenges in FDSSCs and improvements made in photoanode, sensitizer, electrolytes and counter electrode materials. In addition, some of the general characterization methods for newly prepared flexible/rigid dye-sensitized solar cell materials and the device are summarized. The evolution of many forms of mainstream flexible integrated photorechargeable energy storage systems, prospects for the development of highly effective, reliable FDSSCs and their integrated devices have also been demonstrated
Heavy metal pollution in groundwater of urban Delhi environs: Pollution indices and health risk assessment
No full textThe excess presence of heavy metals in water resources deteriorates the quality and has a high potential for bioaccumulation and environmental contamination. The study of heavy metals in water is essential because of their integration in the food chain and the potential for sublethal effects on aquatic and human life. To understand the extent of heavy metal pollution, a total of 64 groundwater samples (32 in each pre-and post-monsoon season) were collected around the Yamuna River's flood plains in the Delhi region. In this study, pollution indices and health risk assessment methodologies were used to estimate the significant threat to humans. In examined seasons, the sequence of heavy metal content in groundwater is Fe > Mn > Zn > B > As>Ni > Pb. The heavy metal pollution index (HPI) revealed that in the pre-and post-monsoon seasons, 53% and 44% (HPI >100), of groundwater samples are at high-risk zone respectively. 53% of pre-monsoon and 56% of post-monsoon samples were found highly polluted, according to the degree of contamination (Cd). Moreover, health risk assessment shows that hazard index (HI) values for heavy metals were found significantly high (HI >1) in groundwater samples inferring increased non-cancerous risk to the local community. The results imply that continuous exposure can lead to chronic diseases in the population residing in the study region. In both carcinogenic and non-carcinogenic assessments, children's hazard index and carcinogenic risk assessment (CR) scores were found higher. As a result, compared to adults in the study region, children are more vulnerable to potential health threats. The principal component analysis (PCA) method was used to figure out the origin of heavy metals, and it was found that As, Fe, Mn, and Zn come from non-anthropogenic sources, whereas mixed sources (natural and anthropogenic) may be responsible for B, Ni, and Pb presence. The results of the study will help to develop an effective strategy for environmental assessment and monitoring to control groundwater pollution of the Delhi urban environs
Effect of Char Temperature on CO2 Gasification of High Ash Coal and Biomass
No full textInformation on comparative gasification reactivity of high temperature chars in CO2 with high ash coal (C), sawdust (SD) and rice husk (RH) under identical condition is important for clean energy development drive particularly in countries like India, where energy matrix is dominated by coal and introduction of larger quantity of biomass in energy-mix is attracting global interests. Therefore, TGA-studies on char-gasification reactivity using CO2 as a gasifying agent were performed at temperatures 850–1000 °C. In case of coal and RH-chars, CO2 reactivity found to increase with increasing the BET surface area and reverse trend was observed with SD-chars. Both the biomass-chars showed increased specific micro pore surface area with increasing char preparation temperature through t-plot analysis, still keeping unusual behavior of CO2 reactivity of SD-char unexplained. The estimations indicating the presence of catalytically active alkali and alkaline earth metals in substantial quantity is only important criteria found to explain the decreasing trend of gasification reactivity of SD-char prepared at various temperatures despite the increase in surface area. Catalytic activity of the components decreases with the rise in char preparation temperature. Kinetic analysis reveal that activation energy values of SD-chars varied in the range123–182 kJ mole−1, whereas those for coal- and RH-chars remained in the range 204–214 kJ mole−1
Neural network based uncertainty and sensitivity evaluation of electrical resistivity tomography for improved subsurface imaging
No full textAssessment of subsurface status by resistivity technique, being an indirect approach, is pretended to be a strategic factor. Projection of full proof confirmation in this domain is always a challenge and hence outcomes are expressed in possibilities. Intervene of mathematical interpretation on resistivity data generated in the field by different arrays would offer a better choice in building-up the possibility of projecting the actual status. Thus, a study of Wenner-Schlumberger (WS), dipole–dipole (DD) and combined inversion (CI) data of three parallel profiles have been conducted, as a whole, for old and abandoned shallow depth coal mine workings in Jharia coalfield. The study recapitulates influence of sensitivity and uncertainty with depth, apart from resistivity. Statistical significance of the data has been evaluated inclusive of their inter-relationship. PCA presented an encouraging relation of sensitivity with depth. The comprehensible approach of mathematical interpretation helps in cracking a problem of uncertain prediction. Sensitivity and the extent of uncertainty are the parameters to build a strong foundation for evaluating the degree of confidence in prediction accuracy. Artificial Neural Network (ANN) tool has been used to understand the relative importance of sensitivity and uncertainty with depth. The weightage of sensitivity has been observed to be on upper side with respect to uncertainty. The importance of configuration of resistivity survey array has been emphasized based on sensitivity
Review of preventive and constructive measures for coal mine explosions: An Indian perspective
No full textFiredamp and coal dust explosion constitute a lion’s share in mine accidents in a global mining scenario. This paper reports a list of mine explosion disasters since last two decades, a critical review of the different prevention and constructive measures, and its recent development to avoid firedamp and coal dust explosion. Preventive legislation in core coal-producing countries, viz. China, USA, Australia, South Africa, and India related to firedamp and coal dust explosion are critically analysed. Accidents occurred due to explosion after Nationalisation of Coal Mines (1973) in India are listed. Prevention and constructive measures adopted in India are critically analysed with respect to the global mining scenario. Measures like methane credit concept, classification of mines/seams with respect to explosion risk zone, deflagration index; installation of automatic fire warning devices, canopy air curtain technology, explosion-prevention measures, such as fire-retardant materials, inhibitors, extinguishing agent, dust suppressor, and active explosion barrier are discussed in detail to avoid explosion and thereby adhering to zero accident policy due to coal mine explosion
A Review on Conversion of Biomass to Liquid Fuels and Methanol through Indirect Liquefaction Route
No full textGlobal urbanization and industrialization are energy-intensive processes. Among different energy resources, fossil fuels meet more than 80 % of the energy demand. The factors such as the depletion of fossil fuel reserves, the unstable price of fossil fuels, and the emission of greenhouse gases (GHGs) due to the burning of fuels draw researchers’ attention towards the development of renewable and sustainable fuels. In this context, biomass may fill the gap between energy demand and petroleum availability in the foreseeable future. Moreover, half of this bioenergy comes from conventional uses of biomass, primarily in cooking and heating, as well as within small-scale industries (such as charcoal kilns and brick kilns). The Biomass-to-Liquid (BTL) technology using Fischer-Tropsch synthesis (FTS) and the Methanol process offers advantages over the traditional use of biomass. The FT/Methanol process is a propitious route to produce carbon-neutral, ultra-clean fuels that generate regulated emissions, including NOx, SOx, and PM. In this article, we have reviewed the processes of biomass gasification, syngas cleaning and conditioning, FTS and methanol synthesis
Prediction of Blast-Induced Ground Vibration Using Principal Component Analysis-Based Classification and Logarithmic Regression Technique
No full textGround vibration is one of the major hazards produced by rock-blasting operation. The accurate prediction of vibration is necessary for designing controlled blasting parameters. The existing vibration predictors consider maximum explosive charge weight per delay and distance as the parameters responsible for ground vibration. These predictors are based on the assumption that the geometrical parameters of the blast will be constant for a site. However, the mining sites with bigger production targets have varying geometrical parameters to suit the excavator utility. Accordingly, the other blast design parameters will also have an impact on ground vibration intensity. A principal component analysis is a dimension reduction technique. This technique along with multivariate logarithmic regression has been used in this paper to predict the ground vibration. The technique has classified the blast design parameters into four principal components. The regression with the scores from these principal components has been carried out. The evaluation of the model performance of predictors along with the existing empirical predictors has been carried out using R2 and RMSE values. The evaluation suggests that the predictor with logarithmic regression followed by principal component analysis gives better performance with respect to the existing empirical predictors
MEUF for removal and recovery of valuable organic components present in effluents: A process intensified technology
No full textIn recent years, the domain of the research space in novel separation process
has been led by membrane systems as a panacea providing multifarious bene�fits of high separation efficiency, elimination of extreme process conditions,
sustainability, and environment friendliness coupled with high operational
flexibility. In this niche area, often, ultrafiltration is touted as a robust separa�tion technique due to its high separation efficiency, membrane stability, and
lower operating costs. The only drawback of relatively large pore size can be
overcome by combining surfactant addition, leading to development of inte�grated processes termed as Micellar Enhanced Ultrafiltration. MEUF processes
isolate and selectively separate valuable organics present in effluent streams.
The process characteristics fit the bill as a typified example for process intensi�fication Technology interventions for recycling of surfactants can enhance the
cost-competitiveness of the process. This has the potential to develop into a
broad-spectrum effluent treatment option with a change of surfactants for tar�get contaminants. Here, in this review, we attempt to critically examine the
unique features of this technology, development of spin-offs with wide-ranging
applications. Specifically applications in removal of hazardous, and persistent
components like dissolved organics have been critically studied. The focus was
to highlight the crux of the novel technologies highlighting the efficacy and
the underlying concept of process intensificatio
Artificial intelligent based smart system for safe mining during foggy weather
No full textOpencast mining operations at hilly areas are usually affected during foggy weather due to the inability of drivers to operate heavy earth-moving machinery in low visibility conditions. This article deals with an intelligent vision enhancement system for continuing opencast mining operations during foggy weather. The system integrates hardware and software to provide multistage safety features that make it unique from existing systems. The system includes hardware like thermal cameras, high definition cameras, proximity radar, wireless devices, GNSS module, graphical processing unit, display unit, and so forth, and image processing software, namely real-time image stitching, image enhancement, and object detection using convolutional neural networks. The integrated system and algorithms display a 180° panorama field view of the vehicle's front using real-time video stitching. The front view after image processing, rear camera view, object detection through proximity radar, and real-time location of the vehicles on a 3D geo-tagged mine map by GNSS modules are displayed in four splitter windows on a touch screen fitted on the dashboard in front of the driver's seat. The driver can drive the vehicle by seeing the display screen during foggy weather. The output image of the developed image-processing algorithm has less distortion, better quality, and better depth perception than existing methods. Overall, there are significant improvements in the persistence of the color elements by 39.65%, contrast by 4.62%, and the corresponding entropy by 7.11% concerning the similar existing methods. The final system has been successfully tested in an opencast mine