IR@CIMFR - Central Institute of Mining and Fuel Research (CSIR)
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Development of Empirical and Artificial Neural Network Model for the Prediction of Sorption Time to Assess the Potential of CO2 Sequestration in Coal
No full textGeological sequestration of CO2 in a coal seam is considered an attractive option to reduce the carbon footprint. It has an additional advantage of enhancing the recovery of coalbed methane, which has less sorption affinity toward coal in comparison to CO2. Desorption of gases from coal is controlled by various parameters, including reservoir depth and coal rank. A representative factor for desorption and diffusion in coal is the sorption time. It is an indicator which helps in estimation and evaluation of gas movement in the coal seam. Coals exhibiting high sorption time allow greater quantities of CO2 injection and hold potential for CO2 sequestration. Therefore, reliable and cost-effective estimation of sorption time is very important prior to investment in projects related to CO2 sequestration. Generally, proximate and gas content analyses are part of the preliminary analysis of coal for the assessment of its potential as a coal-bed methane reservoir. In this study, data generated using these analyses were found very useful for estimating the sorption time and CO2 sequestration potential of coal. The coal samples were collected from different depths of the Mand Raigarh coalfield for testing, and an empirical equation and artificial neural network (ANN)-based model have been developed to predict the sorption time of coal. The developed empirical equation predicts the sorption time with a coefficient of determination value of 0.88 and a root mean squared error value of ±1.07 days. Furthermore, the developed ANN model has been found to be very efficient in prediction with a correlation coefficient value of 0.97
Biosorption study of basic dye using aerial part of widely growing weed Chenopodium album
No full textIn the present study, the fine powder of the aerial part of the invasive weed Chenopodium album has
been explored to effectively eliminate the organic dye Crystal violet from its water solution. The fine
powder of the aerial part of the weed has been characterized by scanning electron microscopy,
X-ray diffraction and Fourier-transform infrared spectroscopy techniques. Its impact on various
parameters of dye elimination has been investigated. It is found that the magnitude of adsorption
is greater at pH 8 and increases with temperature. Different adsorption isotherms and kinetic mod�els were employed to match the adsorption methods data. The data successfully fit the Freundlich,
Hill adsorption model and interparticle models with R2
values of 0.99, 0.99 and 0.97, respectively.
The adsorption capacity of C. album based biosorbent was greater in batch experiments in comparison
to bulk-using column operations. The biosorbent made of C. album can be used as a robust mate�rial for removing the dye Crystal violet. The bio-adsorbent used in the present study has exhibited
much better efficiency (Qe = 219.4 mg/g) in comparison to the ash of the C. album employed for the
adsorption of Crystal violet dye
Precise mosaicing of mouza plans for the preparation of digital cadastral map using GNSS
No full textGlobal Navigation Satellite System (GNSS), an advanced surveying system, is used to determine three-dimensional points accurately. The present study was conducted in Kasta East Coal Block of the West Bengal Power Development Corporation Limited (WBPDCL), India, focusing on data generation, establishing boundary coordinates and mosaicing of mouza plans using real-time kinematic approach. Base station and primary control points were established by the static method. It evaluates the geospatial information using GNSS and quantification of the accuracy of the geo-referenced cadastral map of kasta east coal block of WBPDCL. Scanned mouza plans were converted to vector format through AutoCAD, oriented and placed precisely with the help of established ground control points. The features of the cadastral map were tuned by superimposing the vector cadastral map of the study area. Assessment of the vector cadastral map showed better accuracy and less distortion in large-area parcels/khasras. More variations were observed in small-area khasras. Similarly, smaller mouzas showed more variation compared to larger ones. Distortions were due to manual error in digitization and technical error in scanning. The methodology of mosaicing presented here will be useful for updating the cadastral maps with improved precision in digital cadastral plan preparation
Influence of ring blasting pattern on the safety of nearby underground structures
No full textLonghole stoping is a productive exploitation technique for underground metalliferous deposits. The method consists of deep-hole blasting with increased explosive charges to excavate larger volume of ore from a single blast. However, large scale blasting produces hazards in terms of blast-induced vibration. The underground structures viz. drivages, cross-cuts, shaft pillar, shaft, decline, etc. in the proximity of blasting face need to be safeguarded from damages due to blast vibration. This paper is a case study on investigating the influence of the charging parameters on the safety of nearby underground structures at Sindesar-Khurd Lead-Zinc underground mine. Experimental blasts with variations in charging parameters were performed at the mine for this purpose. The ground vibration data were recorded from the experiment and analysed using neural network analysis and regression analysis. The importance of different charging parameters on ground vibration magnitude has been identified using importance analysis. Regression analysis has been carried out to establish predictor equations correlating different charging parameters with peak particle velocity (PPV). The influence of charging parameters has also been investigated using Probability-value (P-value) approach. The neural network and regression analysis approaches have identified the zones from the blasting face where, distance, maximum charge weight per delay, total explosive charge in a ring and total explosive charge in a blasting round has significant impact. Accordingly, the predictors consisting of different charging parameters have been established. The optimum charging parameters have been suggested based on these predictors for blasting at the mine. The suggested charging parameters are focused on to reduce vibration near underground structures within the safe limit
Underground Coal Mine Environmental Multi-Parameter Monitoring Module with Embedded Sensors: Application of UHF Radio Transceiver Device
No full textUnderground coal mine environmental monitoring is required to ensure and maximize the safe working conditions in mines. For safety monitoring, there is a need to develop an active communication and information network that will be able to detect quickly and efficiently the mine environmental condition and take necessary actions to warn the workers about the environmental condition of the mining area. This can be achieved by the application of long-range wireless communication technology. In the present study, we designed and developed an embedded sensor module to monitor the multiple parameters of environment, including temperature, humidity, methane, carbon monoxide, hydrogen, and coal dust. These multi-parameter monitoring sensors have been interfaced with an Arduino microcontroller. The XBee S8 Ultra-High Frequency (UHF) transceiver device has been used to enable the long-range communication. The specified parameters have been predicted for the safety tenacity in the underground coal mine. A new approach for the calibration process of gas sensors and coal dust sensor has been suggested to acquire desired gas concentrations and dust density in the underground mine air. The computer has been interfaced with the system for environmental multi-parameter monitoring. A successful laboratory trial has been made under the real conditions. In addition, the rangeability of the UHF radio transceiver device and power management of the embedded monitoring module have also been discussed
Prevention and control of spontaneous combustion/fire in coal stockpiles of power plants using firefighting chemicals
No full textSpontaneous combustion of coal in stockpiles of power plants has a significant problem worldwide which leads to several health hazards, environmental pollution and coal loss. Spontaneous combustion coal stockpiles depend on both endogenous (coal characteristics) and exogenous parameters (stockpile geometry, wind speed, wind direction, local temperature). This paper describes the laboratory experiments to study the suitability of firefighting chemicals on the spontaneous combustion/fire of coal in stockpiles. Coal samples were collected from four different heaps of coal laid in coal storage yards of Talwandi Sabo Power Limited (TSPL), Punjab. This study comprises laboratory analysis i.e., proximate analysis, ultimate analysis, critical oxidation temperature, differential scanning calorimetry (DSC) analysis, gross calorific value (GCV), particle size analysis, and field studies i.e., thermal monitoring of fire-affected area before and after firefighting chemicals. Experiments on mixtures of coal and firefighting chemical having compositions viz. 1, 2, 3, and 5%, were carried out using DSC study for optimization of inhibitors as well as its efficacy. During the laboratory study the chemical composition of 3% was found to be optimum for field application to extinguish coal stockpile fire
Investigation on the combustion characteristics of different plant parts of Cassia siamea by DSC-TGA
No full textPlant parts like root, wood, twig and leaf of Cassia siamea, a fast-growing tree in the abandoned mines of Jharkhand, India, have been considered here as a possible fuel source for decentralized power generation. This is a low greenhouse gas emission pathway to cater the electricity need of the adjoining locality. Seasonal availability of the plant parts originated interests of studying the basic combustion characteristics of the plant parts separately. Finding out the roles of cellulose and lignin to regulate the combustion behavior of plant parts was another objective. Cellulose and lignin were extracted from each plant part, and their burning performances were evaluated against those of respective plant parts with the help of DSC-TGA. Cellulose and lignin were found to influence the combustion processes of plant parts differently. Lignin in case of leaf combustion and cellulose for wood combustion regulated the combustion process. Both lignin and cellulose were competitive in regulating the combustion of twig and root. Burning characteristics of cellulose or lignin extracted from different plant parts varied. Higher heating value (HHV) was low for celluloses (~ 16.8 ± 1 MJ kg−1) as compared to lignin (HHV ~ 23.0 ± 1 MJ kg−1). Leaf having substantial lignin and extractives showed the highest HHV around 23.5 MJ kg−1, while the lowest HHV (16.0 MJ kg−1) was observed for wood. Results are interesting for considering each plant part as a single fuel or as a potential component of coal–biomass blended fuel, where locally available low-grade high ash coal may be the other component
Green, economical synthesis of nitrogen enriched carbon nanoparticles from seaweed extract and their application as invisible ink and fluorescent film
No full textIn this article, we synthesized fluorescent nitrogen-enriched carbon nanoparticles (N-CNPs), which were pre-pared via the hydrothermal treatment of pyrolyzed seaweed extract and ethylene diamine at 160 ◦C for 12.0 h. These N-CNPs demonstrated a 12 nm average diameter with carbonyl, hydroxyl, and imine functionality on their surface. The zeta potential value was found to be negative which further conrms the presence of acid/imine groups on the surface of N-CNPs. The prepared N-CNPs showed strong blue fluorescence with 24% quantum yield under UV light illumination. Here, we introduced metal-free water dispersed N-CNPs as invisible ink for security purposes. The information was written by the N-CNPs in TLC plate and N-CNPs/PVA flexible composite film is invisible in daylight and can be readable in UV light illumination
Comparison of CO(2)gasification reactivity and kinetics: petcoke, biomass and high ash coal
No full textIt is desirable to exploit biomass energy along with coal and petcoke through gasification, and understanding the differences between petroleum coke (petcoke), coal and biomass gasification behaviour becomes very essential. Consequently, present investigation compares gasification components of petcoke, sawdust and high ash coal with their physico-chemical properties under isothermal conditions in CO2 atmosphere in the temperature range of 1173–1623 K. Physico-chemical characterisation includes proximate and ultimate analyses, porous structure analysis by Brunauer-Emmett-Teller (BET) surface area from nitrogen (N2) adsorption isotherm, ash composition analysis and ash fusion temperature. The effects of temperature and nature of different solid fuels on gasification reactivity have been discussed. Gasification kinetics has been investigated using two nth-order kinetic models, such as homogeneous model (HM) and shrinking core model (SCM). Influence of diffusion resistance on gasification behaviour of different solid fuels is also reported. Thus, the present study will be helpful to realise the effects of high ash in gasification behaviour as well as in designing and modelling of the suitable gasifier and to establish optimum gasification conditions for petcoke, biomass and high ash coal
INTERPRETATION ON OFFSET INTERVAL IN SECTIONAL AREA METHOD FOR VOLUME COMPUTATION OF OPENCAST EXCAVATION
No full textPrecision in survey of large opencast mine and the computational process are the key drivers for attaining actual rock excavated. The study involves the procedure for estimation of differences in volume of excavated area by sectional area method by varying cross-section intervals. Keeping the conceptual embodiment in consideration, fluctuation in the volume of rock excavation has been assessed by varying the spacing between the cross-sections from 10 m to 40 m with a key objective to arrive at selection of suitable interval, maintaining the precision within the acceptable range. Contribution of Artificial Neural Network (ANN) has been applied to strengthen the analysis with respect to relative importance and sensitivity on the parameters influencing volume. The paper expresses the view that denser sectional spacing result in precise outcome close to actuals