Volume 18, Issue 6 (10-2018)                   Modares Mechanical Engineering 2018, 18(6): 69-78 | Back to browse issues page

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bahari A, mahmoudimehr J. Numerical simulation and optimum operational point determination of a downdraft gasfier regarding pollutant emissions. Modares Mechanical Engineering. 2018; 18 (6) :69-78
URL: http://mme.modares.ac.ir/article-15-15886-en.html
1- Department of Mechanical EngineeringFaculty of EngineeringUniversity of GuilanP.O.Box 3756, Rasht, Iran.
Abstract:   (4542 Views)
The use of biomass by means of gasification to produce bio fuels and reducing the environmental impact of fossil fuels has been the focus of many researchers in recent years. In the present study, the computational fluid dynamics method is used to predict the process of gasification inside a downdraft gasifier. Recent studies have shown that although many studies have been carried out by various researchers to maximize the cold gas efficiency in the gasification process, so far, no study has been done to minimize the emission of pollutants as one of the other important design parameters along with the increase of cold gas efficiency. So, in this study, the effect of changing the equivalence ratio as design variable on the gasification efficiency as well as the amount of pollutant produced simultaneously is investigated. Also, in this study, CO/CO2 and H2 /H2O molar ratios are considered as another objective function in selecting the optimal process point. In order to verify the validity of the results, the simulation data was compared with the experimental results and the previous numerical study, and a good agreement was shown between their comparison. The results of this study show that in the ratio of 0.64, the rate of production of nitrogen oxides relative to cold gas efficiency is optimal considering the maximum production of CO/CO2 and H2/H2O molar ratios . This point is the optimal point. Under the working conditions of the gasification process.
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Article Type: Research Article | Subject: Aerospace Structures
Received: 2018/01/29 | Accepted: 2018/02/26 | Published: 2018/09/24

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