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您的检索式：作者名="B.C.Meikap"
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| 1 | Application of response surface methodology(RSM) for optimization of leaching parameters for ash reduction from low-grade coal显示文摘Coal is the world's most abundant energy source because of its abundance and relatively low cost. Due to the scarcity in the supply of high-grade coal, it is necessary to use low-grade coal for fulfilling energy demands of modern civilization. However, due to its high ash and moisture content, low-grade coal exerts the substantial impact on their consumption like pyrolysis, liquefaction, gasification and combustion process. The present research aimed to develop the efficient technique for the production of clean coal by optimizing the operating parameters with the help of response surface methodology. The effect of three independent variables such as hydrofluoric acid(HF) concentration(10–20% by volume), temperature(60–100 °C), and time(90–180 min), for ash reduction from the low-grade coal was investigated. A quadratic model was proposed to correlate the independent variables for maximum ash reduction at the optimum process condition by using central composite design(CCD) method. The study reveals that HF concentration was the most effective parameter for ash reduction in comparison with time and temperature. It may be due to the higher F-statistics value for HF concentration, which effects to large extent of ash reduction. The characterization of coal was evaluated by Fourier transform infrared spectroscopy(FTIR) analysis and Field-emission scanning electron microscopy with energy-dispersive X-ray(FESEMEDX) analysis for confirmation of the ash reduction. | Sushanta Kumar Behera Himanshu Meena Sudipto Chakraborty B.C.Meikap | 2018 | International Journal of Mining Science and Technology2018，28，4： | 9 |
| 2 | Artificial neural network approach for rheological characteristics of coal-water slurry using microwave pre-treatment显示文摘Detailed experimental investigations were carried out for microwave pre-treatment of high ash Indian coal at high power level(900 W) in microwave oven. The microwave exposure times were fixed at60 s and 120 s. A rheology characteristic for microwave pre-treatment of coal-water slurry(CWS) was performed in an online Bohlin viscometer. The non-Newtonian character of the slurry follows the rheological model of Ostwald de Waele. The values of n and k vary from 0.31 to 0.64 and 0.19 to 0.81 Pa·sn,respectively. This paper presents an artificial neural network(ANN) model to predict the effects of operational parameters on apparent viscosity of CWS. A 4-2-1 topology with Levenberg-Marquardt training algorithm(trainlm) was selected as the controlled ANN. Mean squared error(MSE) of 0.002 and coefficient of multiple determinations(R^2) of 0.99 were obtained for the outperforming model. The promising values of correlation coefficient further confirm the robustness and satisfactory performance of the proposed ANN model. | B.K.Sahoo S.De B.C.Meikap | 2017 | International Journal of Mining Science and Technology2017，27，2： | 3 |
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