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Ashis Mukherjee

Bio: Ashis Mukherjee is an academic researcher from Council of Scientific and Industrial Research. The author has contributed to research in topics: Coal & Coal combustion products. The author has an hindex of 6, co-authored 12 publications receiving 134 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, a comparative assessment of the combustion performance for two types of binary blends viz. "coal sawdust (SD) and "coal-SD char" have been done in this study using a Thermogravimetric analyzer (TGA) and a Drop Tube Furnace (DTF), based on which judicial selection of blends may be made possible.

47 citations

Journal ArticleDOI
TL;DR: In this article, the combustion behavior of four coals and their blends at different proportion under high oxygen concentrations more than 21% for use as feed coal in pulverized coal injection (PCI) in the blast furnace was investigated.

29 citations

Journal ArticleDOI
TL;DR: In this paper, three blend combinations of high-ash and low-ash coals have been examined through lab- and bench-scale combustion experiments, and the results reveal the necessity of pre-assessment of certain blends through lab/bench scale studies before those are adopted in power plant.

27 citations

Book ChapterDOI
29 May 2019
TL;DR: In this article, a 400-ml and 25-l flat panel photo-bioreactor (PSI Photo-Bioreactors) was used for CO2 capture and the algal biomass was used to extract value-added products such as amino acid rich feed, algal oil, and algal pellets.
Abstract: The increased usage of fossil fuels has led to increase in the concentration of CO2, which is a greenhouse gas responsible for global warming. Algae-based CO2 conversion is a cost-effective option for reducing carbon footprint. In addition, algae-based CO2 mitigation strategy has the potential to obtain valuable products at the end of the process. In the present study, freshwater algal species were isolated and identified for CO2 capture, such as Hydrodictyon, Spirogyra, Oscillatoria, Oedogonium, and Chlorella. The algal strains were screened based on different parameters like fast growth rate, high rate of photosynthesis, strong tolerance to the trace constituents of other gases (gaseous hydrocarbons, NOx, SOx, etc.), high temperature tolerance, and possibility to produce high value products, etc. The study involves integrated methods for utilizing 90–99% CO2 from a natural gas processing industry (GAIL India, Ltd.) as well as 13–15% of CO2 from flue gas of thermal power plants (Chandrapura and Santaldih Thermal Power Station) as carbon nutrient source along with the additional nutritional supplements. A 400-ml and 25-l flat panel photo-bioreactor (PSI Photo-bioreactors) was used for CO2 capture. After CO2 capture, the algal biomass was used to extract value-added products such as amino acid rich feed, algal oil, algal pellets, etc.

14 citations

Journal ArticleDOI
TL;DR: In this article, the authors presented computational intelligence (CI) based nonlinear models to predict the four types of AFT, namely initial deformation temperature, softening temperature, hemispherical temperature and flow temperature.
Abstract: In the coal-based combustion and gasification processes, the mineral matter contained in the coal (predominantly oxides), is left as an incombustible residue, termed ash Commonly, ash deposits are formed on the heat absorbing surfaces of the exposed equipment of the combustion/gasification processes These deposits lead to the occurrence of slagging or fouling and, consequently, reduced process efficiency The ash fusion temperatures (AFTs) signify the temperature range over which the ash deposits are formed on the heat absorbing surfaces of the process equipment Thus, for designing and operating the coal-based processes, it is important to have mathematical models predicting accurately the four types of AFTs namely initial deformation temperature, softening temperature, hemispherical temperature, and flow temperature Several linear/nonlinear models with varying prediction accuracies and complexities are available for the AFT prediction Their principal drawback is their applicability to the coals originating from a limited number of geographical regions Accordingly, this study presents computational intelligence (CI) based nonlinear models to predict the four AFTs using the oxide composition of the coal ash as the model input The CI methods used in the modeling are genetic programming (GP), artificial neural networks, and support vector regression The notable features of this study are that the models with a better AFT prediction and generalization performance, a wider application potential, and reduced complexity, have been developed Among the CI-based models, GP and MLP based models have yielded overall improved performance in predicting all four AFTs

12 citations


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Journal ArticleDOI
TL;DR: In this article, the authors deal with the technical aspects of co-combustion with emphasis on the fundamentals of devolatilization, ignition, burnout and ash deposition behavior along with the constraints and uncertainties associated with the use of different types of biomass of diverse characteristics and the likely impact of partial replacement of coal by biomass on the emission of CO2, SOx, NOx.
Abstract: The energy sector in the global scenario faces a major challenge of providing energy at an affordable cost and simultaneously protecting the environment. The energy mix globally is primarily dominated by fossil fuels, coal being the major contributor. Increasing concerns on the adverse effect of the emissions arising from coal conversion technologies on the environment and the gradual depletion of the fossil fuel reserves had led to global initiatives on using renewables and other opportunity resources to meet the future energy demands in a sustainable manner. Use of coal with biomass as a supplementary fuel in the combustion or gasification based processes is a viable technological option for reducing the harmful emissions. Co-combustion of coal with biomass for electricity generation is gradually gaining ground in spite of the fact that their combustion behavior differ widely due to wide variations in their physical and chemical properties. This article deals with the technical aspects of co-combustion with emphasis on the fundamentals of devolatilization, ignition, burnout and ash deposition behavior along with the constraints and uncertainties associated with the use of different types of biomass of diverse characteristics and the likely impact of partial replacement of coal by biomass on the emission of CO2, SOx, NOx. Other issues of no less importance like sustained availability of biomass, transportation and storage, effect on biodiversity, etc., are left out in the study. The investigations reported in the study reflect the potential of biomass as co-fuel, and the scope of maximizing its proportion in the blend in the coal based power plants and the derived benefits.

248 citations

Journal ArticleDOI
TL;DR: Poultry litters can be used as a substitute fuel in coal/biomass co-firing systems by blending with lignocellulosic biomass through non-isothermal thermogravimetric method under air atmosphere.

156 citations

Journal ArticleDOI
TL;DR: In this article, the cleat-scale characterisation of coal is discussed and the application of micro-CT imaging for studying diffusion processes in ultralow permeability media is shown.

118 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigated the major factors influencing gas adsorption capacity and desorption rate of some Indian coals ranging in rank from high-volatile bituminous C (062% Ro max) to mediumvolatile coal (146% Romax) and found that coal type had a stronger influence on the gas adaption capacity.
Abstract: Details of methane sorption properties of some Indian coals ranging in rank from high-volatile bituminous C (062% Ro max) to medium-volatile bituminous coal (146% Ro max) were investigated to determine the major factors influencing gas adsorption capacity and desorption rate Variables studied included moisture content, mineral-matter content, rank, and coal type (maceral composition) Adsorption isotherm analysis of dry coals showed that adsorption capacity followed a second-order polynomial trend with rank Equilibrium moist samples showed a linear increase in adsorption capacity with rank and had a significantly reduced adsorption capacity compared to the dry coals, with the reduction being related to the moisture content Mineral matter acted as a simple diluent to the gas adsorption capacity of the coals and was found to be nonadsorbent Adsorption capacity (moist) was reduced by 032 cm3/g (10 ft3 gas/t) for every 1% increase in the ash yield Bright and dull coal lithotypes showed strong separation in their adsorption capacities on an as analyzed basis, with the bright coals adsorbing greater quantities of gas On a dmmf basis, however, no relationship was observed between coal type and gas storage capacity Comparison of maceral composition with adsorption capacity (dry) confirmed this observation Effective diffusivity (De) of methane through the coal was seen to be affected by coal type and rank Effective diffusivity, De, decreased as rank increased, which is related to the increasing microporous nature of the coal Bulk coals tested had 2-3 times larger effective diffusivities than bright coals, and dull coals had intermediate rates The larger De values for the bulk coals may be related to the presence of collodetrinite coupled with mineral matter, which acts as higher permeability pathways for the gas compared with the high-ash dull coals dominated by inertinite macerals Differences were noted with similar-age (Permian) Australian coals, where methane adsorption capacities were larger and coal type had a stronger influence on adsorption capacity (Begin page 202)

118 citations

Journal ArticleDOI
15 May 2015-Fuel
TL;DR: In this article, the authors focused on the study of ashes from eighteen different biomass samples, including energy crops, agricultural, industrial and forestry wastes and commercial fuels, and found a homogeneous structure with low quantities of health risky fine particles for most samples after 550°C burning.

96 citations