PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL
The use of fossil fuels produces greenhouse gas emissions which are the leading cause of global warming. One effort to reduce greenhouse gas emissions is the use of biomass as an alternative fuel. Nevertheless, the combustion of biomass often causes slagging and fouling problems in furnaces. Ther...
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id-itb.:656352022-06-24T10:00:59ZPREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL Syaiful Islam, Muhammad Teknik kimia Indonesia Final Project Thermodynamic model, Biomass and coal ash, Ash fusion temperature (AFT), Slagging and fouling, FactSage INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/65635 The use of fossil fuels produces greenhouse gas emissions which are the leading cause of global warming. One effort to reduce greenhouse gas emissions is the use of biomass as an alternative fuel. Nevertheless, the combustion of biomass often causes slagging and fouling problems in furnaces. Therefore, this study aims to predict the physical properties and behavior of biomass ash and coal ash to overcome slagging and fouling problems. The prediction of physical properties and behavior of ash is performed by using (1) thermodynamic modeling, (2) ash composition review, and (3) slagging and fouling indices calculation. The composition of ashes is obtained from literature studies. Thermodynamic modeling using FactSage version 7.3 consists of (1) simulation of alkali metals behavior in biomass combustion, (2) simulation of ash melting, and (3) creation and interpretation of ternary phase diagrams (TPD). The S-C-K-CK classification is used for predicting the range of IDT and HT of biomass ash, whereas the slagging and fouling indices are used for predicting slagging and fouling tendency of biomass and coal ash. Biomass combustion simulation predicts the vaporization of alkali compounds in the form of K, KOH, KCl, (KCl)2, K2SO4, Na, NaOH, and NaCl. Higher K and Na content in biomass leads to a higher tendency for slagging and fouling to occur. Ash melting simulation shows that under reducing atmosphere, AFT values (IDT, ST, HT, and FT) are best correlated with T75, T75, T45, and T50, while under oxidizing atmosphere, AFT values are best correlated with T35, T45, T45, and T50, with Tn is the temperature when n%-weight of ash is already melted. Despite that, there is no clear trend between AFT values and Tn because the ash melting simulation is only considering the thermodynamic aspects whereas ash melting is also influenced by physicochemical properties of the ash. Liquidus temperature reading from TPD have been used to predict AFT values. The standard deviation of the AFT prediction from liquidus temperature readings for biomass ash are 155oC (reducing atmosphere) and 110oC (oxidizing atmosphere) whereas the standard deviation for coal ash are 85oC (reducing atmosphere) and 50oC (oxidizing atmosphere). The S-C-K-CK classification provides AFT range predictions for biomass ash with a suitability of 82% for IDT and 71% for HT. The best slagging and fouling index to predict slagging and fouling tendency is the ash fusibility index (AFI) with a predictive agreement with the AFT value index of 82% for biomass ash and 64% for coal ash. The comprehensive thermodynamic modeling that is used in this research can predict alkali metal compounds formation during biomass combustion and prediction of AFT values of ash. The results from this modeling can be used to help predict slagging dan fouling tendencies of ash. text |
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Teknik kimia Syaiful Islam, Muhammad PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL |
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The use of fossil fuels produces greenhouse gas emissions which are the leading cause of global
warming. One effort to reduce greenhouse gas emissions is the use of biomass as an alternative fuel.
Nevertheless, the combustion of biomass often causes slagging and fouling problems in furnaces.
Therefore, this study aims to predict the physical properties and behavior of biomass ash and coal ash
to overcome slagging and fouling problems.
The prediction of physical properties and behavior of ash is performed by using (1) thermodynamic
modeling, (2) ash composition review, and (3) slagging and fouling indices calculation. The
composition of ashes is obtained from literature studies. Thermodynamic modeling using FactSage
version 7.3 consists of (1) simulation of alkali metals behavior in biomass combustion, (2) simulation
of ash melting, and (3) creation and interpretation of ternary phase diagrams (TPD). The S-C-K-CK
classification is used for predicting the range of IDT and HT of biomass ash, whereas the slagging and
fouling indices are used for predicting slagging and fouling tendency of biomass and coal ash.
Biomass combustion simulation predicts the vaporization of alkali compounds in the form of K, KOH,
KCl, (KCl)2, K2SO4, Na, NaOH, and NaCl. Higher K and Na content in biomass leads to a higher
tendency for slagging and fouling to occur. Ash melting simulation shows that under reducing
atmosphere, AFT values (IDT, ST, HT, and FT) are best correlated with T75, T75, T45, and T50, while
under oxidizing atmosphere, AFT values are best correlated with T35, T45, T45, and T50, with Tn is the
temperature when n%-weight of ash is already melted. Despite that, there is no clear trend between
AFT values and Tn because the ash melting simulation is only considering the thermodynamic aspects
whereas ash melting is also influenced by physicochemical properties of the ash. Liquidus temperature
reading from TPD have been used to predict AFT values. The standard deviation of the AFT prediction
from liquidus temperature readings for biomass ash are 155oC (reducing atmosphere) and 110oC
(oxidizing atmosphere) whereas the standard deviation for coal ash are 85oC (reducing atmosphere)
and 50oC (oxidizing atmosphere). The S-C-K-CK classification provides AFT range predictions for
biomass ash with a suitability of 82% for IDT and 71% for HT. The best slagging and fouling index
to predict slagging and fouling tendency is the ash fusibility index (AFI) with a predictive agreement
with the AFT value index of 82% for biomass ash and 64% for coal ash. The comprehensive
thermodynamic modeling that is used in this research can predict alkali metal compounds formation
during biomass combustion and prediction of AFT values of ash. The results from this modeling can
be used to help predict slagging dan fouling tendencies of ash.
|
format |
Final Project |
author |
Syaiful Islam, Muhammad |
author_facet |
Syaiful Islam, Muhammad |
author_sort |
Syaiful Islam, Muhammad |
title |
PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL |
title_short |
PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL |
title_full |
PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL |
title_fullStr |
PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL |
title_full_unstemmed |
PREDICTION OF BIOMASS AND COAL COMBUSTION ASH BEHAVIOUR USING THERMODYNAMIC MODEL |
title_sort |
prediction of biomass and coal combustion ash behaviour using thermodynamic model |
url |
https://digilib.itb.ac.id/gdl/view/65635 |
_version_ |
1822004912380182528 |