IR@CIMFR - Central Institute of Mining and Fuel Research (CSIR)
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An Empirical Modeling and Evaluation Approach for the Safe use of Industrial Electric Detonators in the Hazards of Radio Frequency Radiation
No full textThe major causes of radio frequency radiation hazards are the transmitting antennas of radio, TV, radar, cell phones, wireless data acquisition systems and global positioning systems in the new age of communication technology using various modulation schemes such as amplitude modulation (AM), frequency modulation (FM) etc. The transmitting antennas of these communication devices generate electromagnetic fields (EMFs). Under such conditions, electric detonator wires work as receiving antenna and pickup sufficient energy from electromagnetic fields to initiate an accidental explosion. There have been several instances of accidental firing of detonators by radio frequency pickup. In this study an attempt has been made to minimize such explosions and to provide a basis for the assessment and simulation of the radio frequency radiation hazard parameters associated with industrial electric detonators. This research examines the radiated powers of various frequency bands to determine the safe distance from transmitting antenna. Two empirical relationships for the estimation of minimum safe distance (MSD) have been suggested based on mathematical simulation. Using these relations desired MSDs have been calculated for the relevant frequency bands. The values obtained have been compared with the experimental values available that demonstrated strong agreement between them. The average percentage deviations of calculated MSDs from suggested relations are found between 0.096% and 10.718%, with regression coefficient 0.970 ≤ R ≤ 1. This reflects the soundness of the proposed empirical relations. The blasting engineers, detonator designers and researchers may use these relations as a handy tool to prevent undesired explosions by maintaining minimum safe distance in radio frequency prone hazardous are
Thermal behavior of some Indian coals: inferences from simultaneous thermogravimetry–calorimetry and rock–eval. Natural Resources Research
No full textIn this work, thermal behaviors of ten coal samples (across different thermal maturity levels) collected from five different open cast mines in the Jharia and Raniganj basins, India, were examined using differential scanning calorimeter (DSC), thermogravimetry (TG–DTG), Rock–Eval, and organo-petrographic techniques. Rank played a critical factor in controlling their thermal behavior, and with increasing coal rank the combustion parameters shifted towards higher temperatures. The oil-window mature non-coking coals were marked by least ignition and burnout temperatures, least DSC Tpeak, DTG Tpeak, and maximum reactivity. In contrast, the coking-coal samples of peak-oil window and condensate wet–gas window stages of maturity, because of their higher thermal maturity level and lower reactivity, required higher temperatures for combustion. Among the peak-oil window mature coking coals, one sample (C4) showed distinct lower combustion parameters relative to others, although vitrinite reflectance (Ro; %) and Rock–Eval pyrolysis Tmax showed similar results as the other coals. This sample was marked by higher reactive maceral content. Highest combustion parameters and least reactivity were shown by the Jhama sample (baked coal), followed by the condensate wet–gas window mature coking coals. The Rock–Eval S4 Tpeak clearly resolved the coal samples with distinct maturities and complemented the results from TG–DTG–DSC thermograms. Our results indicate that Rock–Eval S4Tpeak can be used to decipher convincingly the thermal maturity level of coals
Using Rock-Eval S4Tpeak as thermal maturity proxy for shales.
No full textThe Rock-Eval pyrolysis-stage derived parameters such as free hydrocarbons (S1), heavier pyrolysis-hydrocarbons (S2), pyrolyzable carbon (PC) and pyrolysis Tmax (from S2 curve) have received considerable interest for source-rock screening and thermal maturity assessment. On the other hand, the Rock-Eval oxidation-stage S4CO2 curve, which gives the amount of residual carbon (RC), only recently has received some interest. While the pyrolysis-stage S2 temperature-peak (Tmax) is conventionally used as a maturity proxy, in this work we show that the temperature-peak of S4CO2 curve (S4Tmax) can also be used as a thermal maturity proxy for shales. For overmature and low-TOC shale samples, showing asymmetric S2 shape and concomitantly producing doubtful Tmax, the S4 curves showed symmetric nature and consequently the S4Tmax was observed to be a reliable thermal maturity estimate. While the S4Tmax clearly resolved immature and overmature shales, for the early mature and peak mature shales the S4Tmax showed overlapping values. S4Tmax of pre-pyrolyzed and pyrolyzed masses showed good positive correlation with differential scanning calorimetry temperature-peak (DSCTpeak), and consequently indicated its applicability as a thermal maturity proxy. When early mature pre-pyrolyzed samples were directly analyzed using the Rock-Eval oxidation stage, the S4 curves showed formation of two sub-peaks, and consequently the Tmax was observed to decrease. It is recommended that analysts and interpreters should thoroughly cross-check S2 curves before reporting data, and in case of asymmetric or unreliable S2 curves, the S4Tmax can be used as a maturity proxy
Instights of Cleat Attribute of Barakar Coal Deposits of Son Valley basin, India; Implication for Coal Bed methane Exploration
No full textCleat attribute and coal quality have been evaluate
Development of ANN-Based Universal Predictor for Prediction of Blast-Induced Vibration Indicators and its Performance Comparison with Existing Empirical Models
No full textAir overpressure (AOp) and peak particle velocity (PPV) are the most undesirable effects of blasting in mines. It is an urgent need to design a predictor model for AOp and PPV for universal applications to minimize environmental effects and damages that occur due to blasting. The present study attempts to design an artificial neural network (ANN) model for the prediction of AOp and PPV in different conditions. In this study, the blast design parameters (number of holes, depth of the blast hole, stemming length, spacing, burden, distance of vibration monitoring location from the blast site, charge weight per delay) of two active mines (coal and iron ore) are considered in four different conditions for training and testing of the model for the prediction of AOp and PPV. The model was trained and tested in four different combinations of data (trained using data of one mine and tested using data of another mine, trained and tested using data of coal mine, trained and tested using data of an iron ore mine, trained and tested using combined data of both the mines) for examining the applicability in different conditions. The results indicate that R2 values are ranged from 0.886 to 0.908 and 0.8728 to 0.8959, respectively, in the prediction of PPV and AOp. A comparative study of the performances of the developed model with the other empirical model is also demonstrated. For this, the site constants of different empirical models were estimated individually for both the mines. The study results indicated that the ANN model performs much better than all the empirical models. It can be inferred from the results that blast vibration cannot be accurately predicted only from charge per delay and distance from the blast hole. The ANN model was considered many other factors and thus can predict the vibration level more accurately
Non-carcinogenic health risk assessment for fluoride and nitrate in the groundwater of the mica belt of Jharkhand, India
No full textGroundwater quality was investigated for fluoride and nitrate contamination in the mica mining areas of Jharkhand with special emphasis on seasonal fluctuation, source apportionment and human health risk assessment. Samples were collected from thirty-seven locations on a seasonal basis. The results indicated 31% and 32% samples of groundwater to exceed the Indian drinking water quality standards for F– and NO3–, respectively. Marked seasonal variation was observed in the concentration of NO3– with highest levels in monsoon season; however, the seasonal fluctuation was insignificant for F–. The NO3– contamination can be attributed to agricultural activities while F– can be related to geogenic sources. For the evaluation of non-carcinogenic risk, Hazard Quotient (HQ) and Hazard Indices (HI) were calculated as per United States Environmental Protection Agency methodology. The results suggested the child population to be most vulnerable to health risks due to ingestion of F– and NO3–. The HI values for men (0.34–18.4), women (0.29–15.8) and children (0.55–29.3) suggested considerable health risk related to F– and NO3– to all the population groups. As high as 95% of the groundwater samples were likely to cause non cancer health effects in the child populace advocating upgraded water management plan for the resident
Hardening of Steel Through High-Voltage Low-Current Energy Input
No full textA novel approach of high-voltage low-current energy input is applied for hardening of plain carbon eutectoid steel. Initial fine lamellar pearlitic structure disintegrates into four characteristic regions: lamellar pearlite often containing nucleated cementite spheroids (Region-I), fragmented cementite lamella in α-ferrite matrix (Region-II), submicroscopic cementite particles/clusters dispersed in α-ferrite matrix (Region-III), and supersaturated α-ferrite (Region-IV). At a particular applied voltage, structural refinement and matrix supersaturation (evolving martensite) progress concomitantly up to 5 min, followed by a reverse trend of coarsening and degeneration of martensite. The refinement effect and martensite-peak-broadening effect are augmented with increasing voltage up to 75 kV at which the highest hardness (429 HV) of the steel is achieved with treatment duration of 5 min. While primary hardening effect arises from the martensite region of stratified plate morphology (Region-IV), a secondary effect of hardening is resulted from the region containing dispersed submicroscopic cementite particles/clusters in α-ferrite matrix (Region-III). In addition, in the specimen exhibiting maximum hardening effect (at 75 kV, 5 min), as a unique feature, nanosized cementite particles also appear in Region-IV being dispersed in martensite matrix so as to provide further effect of dispersion hardening along with martensitic hardening
Utilization of mill tailings, fly ash and slag as mine paste backfill material: Review and future perspective
No full textAn enormous amount of waste materials (tailings, fly ash and slag) are generated during mineral processing, power generation and metallurgical processes. A vast literature on utilising mill tailings for paste backfilling, fly ash and slag as partial replacement to cement is available. However, a detailed review on the application of mill tailings, fly ash and slag as mine paste backfill material has been lacking. This article provides a critical review of these industrial wastes’ utilisation as paste backfill material for backfilling of the underground mine voids. The properties of backfill materials affecting the paste backfill performance, advancements made in geomechanical, microstructural properties, strength prediction, leaching and economic aspects are scientifically reviewed. In addition to the above, the effect of alternative binders, specifically fly ash and slag, modification of paste backfill using alkali activator, superplasticizer, admixture and fibre reinforcement are comprehensively reviewed. The review ended with some future research directions in mine paste backfilling, especially applying natural and artificial additives for early strength development, strength and flowability prediction using statistical and artificial intelligence tools, leachates stabilization and geochemical modeling of leaching. Hence, this review would help in further application of such industrial waste materials for mine paste backfilling
UMAP and LSTM based fire status and explosibility prediction for sealed-off area in underground coal mine
No full textA uniform manifold approximation and projection (UMAP) and long short-term memory (LSTM) deep learning model have been proposed to forecast a sealed-off area's fire status in underground coal mines. It protects miners' life by providing early warning to the miners regarding the impending mine hazards. The proposed forecasting model graphically displays fire status in the form of Ellicott's extension graph. An experiment has been conducted to measure the proposed forecasting model's efficiency and two existing machine learning models, namely support vector regression (SVR) and auto-regressive integrated moving average (ARIMA) models. It has been found that gas concentration prediction of the proposed UMAP-LSTM model has the lowest root mean square error of 0.288, 0.006, 0.0995, 0.902, 0.238, 0.452, and 0.006 for O2, CO, CH4, CO2, H2, N2, and C2H4 gases respectively than the existing SVR and ARIMA models, which indicates higher efficiency of the proposed prediction model
Criticality in computation of volume excavated by opencast mining: some key observations
No full textSurvey plays a vital role in computation of actual volume excavated. Precise computation of opencast excavation is of prime importance as it affects the quantity of mineral/coal and in turn economy. The paper covers the methodology encompassing the concept and procedure for estimation of volume of irregular excavated geometry by section method on varying section orientation. The same approach has been correlated with field measurement done in New Akashkinari mine of Jharia Coalfield. Susceptible aspects like type of software used, process of preparation of cross sections, position of sections, and interval between two sections are discussed to assess the cause for variation in volume computed for the same input data