Mathematical modelling of MSW incineration on a travelling bed

Yang, Yao; Goh, Y. R.; Zakaria, Rahimah; Nasserzadeh, V.; Swithenbank, J.

doi:10.1016/s0956-053x(02)00019-3

Cited by 202 publications

(136 citation statements)

References 5 publications

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“…At the surface of the fuel bed, x = a The heat conduction coefficient from the study of Yagi and Kunii (1957) is used to describe heat conduction in the bed:…”

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

“…Equation (7) describes the solid surface-to-solid surface heat conduction coefficient, k rv . The normal values of γ, φ, and β for cylinders and spheres, as well as for granules, are as follows ( Yagi and Kunii, 1957): γ = 1, β = 1, and φ = 0.040.…”

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

“…According to Yagi and Kunii (1957), flowing fluid improves the heat conduction of the bed due to the effect of axial dispersion; therefore, the effective heat conduction coefficient becomes:…”

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

“…The geometrical constant is reported to typically take values between 0.1 and 0.13 (Yagi and Kunii, 1957). In the model, the average of  = 0.115 is used.…”

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

“…Goh et al (2001) have constructed a model of grate combustion of municipal solid waste in order to study the process, since efficient incinerator design requires extensive knowledge of the combustion process. Later, Yang et al (2002) developed a 2-D model of an MSW incinerator, which was then verified using experimental data obtained from a pot reactor. Kaer (2005) has developed a one-dimensional model to describe the fixed-bed combustion of straw and using the walking grate concept extended to cover the moving bed of a straw bed.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic modeling of combustion in a BioGrate furnace: The effect of operation parameters on biomass firing

Boriouchkine

Zakharov

Jämsä‐Jounela

2012

Chemical Engineering Science

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The development of efficient operation and control of a biomass boiler requires extensive knowledge of the combustion process inside the boiler furnace However, it is not possible to obtain the required knowledge through process measurements because the high temperatures and aggressive environment inside the furnace prevent taking accurate sensor readings. Instead, the process can be studied with the help of mathematical modeling. This paper describes dynamic modeling of bed combustion in a BioGrate boiler furnace. The developed dynamic model is heterogeneous, including solid and gas phases and corresponding reactions. The model is used for process phenomena investigation; the results are presented and discussed. Keywords

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“…At the surface of the fuel bed, x = a The heat conduction coefficient from the study of Yagi and Kunii (1957) is used to describe heat conduction in the bed:…”

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

“…The geometrical constant is reported to typically take values between 0.1 and 0.13 (Yagi and Kunii, 1957). In the model, the average of  = 0.115 is used.…”

Section: ) Energy Continuity Equation Of the Solid Phasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Dynamic modeling of combustion in a BioGrate furnace: The effect of operation parameters on biomass firing

Boriouchkine

Zakharov

Jämsä‐Jounela

2012

Chemical Engineering Science

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Substoichiometric conversion of biomass and solid wastes to energy in packed beds

2005

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Modeling of fixed bed downdraft biomass gasification: Application on lab-scale and industrial reactors

Pérez

Melgar

Fluixá

2013

Int. J. Energy Res.

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SUMMARY This study aimed at presenting a model to simulate downdraft biomass gasification under steady‐state or unsteady‐state conditions. The model takes into account several processes that are relevant to the transformation of solid biomass into fuel gas, such as drying; devolatilization; oxidation; CO2, H2O, and H2 reduction with char, pressure losses, solid and gas temperature, particle diameter, and bed void fraction evolution; and heat transfer by several mechanisms such as solid–gas convection, bed–wall convection, and radiation in the solid phase. Model validation is carried out by performing experiments in two lab‐scale downdraft fixed bed reactors (unsteady‐state conditions) and in a novel industrial pilot plant of 400 kWth–100 kWe (steady‐state conditions). The capability of the model to predict the effect of several factors (reactor diameter, air superficial velocity, and particle size and biomass moisture) on key response variables (temperature field, maximum temperature inside the bed, flame front velocity, biomass consumption rate, and composition and calorific value of the producer gas) is evaluated. For most response variables, a good agreement between experimental and estimated values is attained, and the model is able to reproduce the trend of variation of the experimental results. In general terms, the process performance improves with higher reactor diameter and lesser air superficial velocity, particle size, and moisture content of biomass. The steady‐state simulation appears to be a versatile tool for simulating different reactor configurations (preheating systems, variable geometry, and different materials). Copyright © 2013 John Wiley & Sons, Ltd.

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Mathematical modelling of MSW incineration on a travelling bed

Cited by 202 publications

References 5 publications

Dynamic modeling of combustion in a BioGrate furnace: The effect of operation parameters on biomass firing

Dynamic modeling of combustion in a BioGrate furnace: The effect of operation parameters on biomass firing

Substoichiometric conversion of biomass and solid wastes to energy in packed beds

Modeling of fixed bed downdraft biomass gasification: Application on lab-scale and industrial reactors

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