کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6630261 | 1424931 | 2018 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Pyrolysis of high-ash sewage sludge: Thermo-kinetic study using TGA and artificial neural networks
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
مهندسی شیمی (عمومی)
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چکیده انگلیسی
Pyrolysis of high-ash sewage sludge (HASS) is a considered as an effective method and a promising way for energy production from solid waste of wastewater treatment facilities. The main purpose of this work is to build knowledge on pyrolysis mechanisms, kinetics, thermos-gravimetric analysis of high-ash (44.6%) sewage sludge using model-free methods & results validation with artificial neural network (ANN). TG-DTG curves at 5,10 and 20â¯Â°C/min showed the pyrolysis zone was divided into three zone. In kinetics, E values of models ranges are; Friedman (10.6-306.2â¯kJ/mol), FWO (45.6-231.7â¯kJ/mol), KAS (41.4-232.1â¯kJ/mol) and Popescu (44.1-241.1â¯kJ/mol) respectively. ÎH and ÎG values predicted by OFW, KAS and Popescu method are in good agreement and ranged from (41-236â¯kJ/mol) and 53-304â¯kJ/mol, respectively. Negative value of ÎS showed the non-spontaneity of the process. An artificial neural network (ANN) model of 2â¯*â¯5â¯*â¯1 architecture was employed to predict the thermal decomposition of high-ash sewage sludge, showed a good agreement between the experimental values and predicted values (R2â¯â©¾â¯0.999) are much closer to 1. Overall, the study reflected the significance of ANN model that could be used as an effective fit model to the thermogravimetric experimental data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuel - Volume 233, 1 December 2018, Pages 529-538
Journal: Fuel - Volume 233, 1 December 2018, Pages 529-538
نویسندگان
Salman Raza Naqvi, Rumaisa Tariq, Zeeshan Hameed, Imtiaz Ali, Syed A. Taqvi, Muhammad Naqvi, M.B.K. Niazi, Tayyaba Noor, Wasif Farooq,