A variety of pyrolysis models have been derived therefore to account for the pyrolysis of particles, taking into account the process parameters noted in Table
2.3. Some of these models are summarised in Table 2.4 with their predictions and their shortcomings. A more detailed version which includes the formulation and assumptions has been complied by Bridge (85). Each model has its own particular feature or characteristic. These are detailed in Table 2.5.
|
Table 2.3 Process Parameters that Influence Pyrolysis with Their Effects
|
Parameter
|
Bfsa
|
|
Anisotropic nature
|
heat capacity, permeability, rate of heat transfer, diffusion
|
|
Moisture content
|
temperature profile, weight/density change, product yields and distribution, amount of water released initially during the drying stage, rate of heat transfer
|
|
Reactor temperature
|
temperature profile, weight/density change, product yields and distribution, competing reactions, properties such as thermal conductivity and heat capacity, heat of reaction
|
|
Particle size
|
temperature profile, weight/density change, product yields and distribution, release rate of products, rate of heat transfer, reaction time
|
|
Heat flux
|
rate of heat transfer, temperature profile, reaction profile
|
Vapour residence time product yield and distribution
|
|
Table 2.4 Summary of Single Particle Pyrolysis Models
|
|
|
Authors
Bamford et al. (84)
|
|
|
Predictions
• Predicts temperature and weight loss profiles
• Predicts volatiles evolution rate
|
|
|
Shortcomings
• Cannot be used to predict product yields or composition
• No sensitivity analyses were carried out
• No convection term
• Assumed constant physical properties
|
|
|
• Predicts temperature and reaction rate profiles
• Predicts gas generation rate
• Suggests that heat of reaction and activation energy are important parameters for gas generation
• Suggests that competing reactions are sensitive to the heat flux
|
|
|
Cannot be used to predict product yields or composition No convection term Breaks down at higher heating flux when investigating the effect of heating rate on the competing reactions
|
|
|
|
|
• Shows that convection term is needed in heat balance equation
• Suggests that the burning rate depends on particle size
|
|
|
Can only be used to investigate the importance of convective heat transfer
|
|
|
|
 |
|
|
|
|
|
• Introduces a new parameter,
Lewis No., the ratio of thermal diffusivity to mass d’rffusivity
• Predicts concentration and temperature profiles
• Suggests that the higher the Lewis No., the greater the conversion of the solid and the smaller the temperature gradient within particle
• Suggests that heat of reaction affects pyrolysis rate
|
|
|
Cannot be used to predict product yields or composition
Does not predict volatiles evolution rate
|
|
|
|
|
|
|
• Predicts mass loss, pressure and temperature profiles
• Suggests that heat of reaction, both the thermal conductivity and specific heat of char and the permeability constant are important parameters in wood pyrolysis
• Predicts product distribution
• Temperature and particle size influences product distribution
• Predicts temperature profile
• Predicts reaction time
• Suggests that the values of pyrolysis temperature, char thermal conductivity and heat of reaction significantly affect wood pyrolysis
• Predicts reaction rate and time
• Predicts both internal and surface temperature and mass loss
• Predicts mass loss profiles
• Predicts surface and internal temperature profiles
• Predicts char yields
|
|
|
Cannot be used to predict product yields or composition
Does not predict volatiles release rate
|
|
|
Does not predict temperature profiles Assumed constant physical properties
Cannot be used to predict product yields or composition
Does not predict volatiles release rate Assumed constant physical properties
Cannot be used to predict product yields or composition
Does not predict volatiles evolution rate
Does not predict volatiles yields
Does not predict volatiles release rate Assumed constant physical properties For large particles, kinetics and heat transfer are not coupled
Neglect of mass transfer resistance which may play a role in pyrolysis
|
|
|
|
|
|
|
|
|
|
|
• Predicts temperature, mass loss and density histories
• Predicts moisture distribution
• Predicts moisture and volatiles release rate
• Predicts generation of steam and volatiles
• Predicts under what conditions heat transfer or chemical reaction is rate controlling
• Introduces a thermal Thiele Modulus (ratio of heat penetration time to reaction time)
• Predicts temperature profile
• Predicts reaction time
|
|
|
|
|
Cannot be used to predict product yields or composition
Does not predict volatiles evolution rate Thermal properties are assumed to remain constant
|
|
|
1_ёс1ё et al. (50, 51,100)
|
|
• 
Introduced two pyrolysis numbers, • Py (ratio: reaction time to heat penetration time) and Р/ (Biot No x Py) •
• Evaluated the importance of external and internal heat transfer •
* Derived four simple models
* Predicts conversion and temperature profiles Predicts conversion times Particle size affects conversion Carried out sensitivity study
Predicts char yields Predicts cracking activation energies
Predicts temperature histories Predicts weight loss Calculates reaction times Derived simple expressions to calculate heat up time and devolatilisation time Pyrolysis is complete at 500°C
Predicts product yields and composition
Predicts volatiles release rate Predicts temperature profile Predicts effects of moisture Carried out sensitivity studies
Predicts product yields and composition
Predicts volatiles release rate Predicts temperature profile Predicts effects of moisture Carried out sensitivity studies
Predicts volatiles and gas yields Simple model gives good agreement with experimental work
Predicts high temperature drying profiles at >150°C applicable to wet particles up to the free-water continuity point (-0.45)
Simple kinetic scheme used internal flow convection effects on thermal degradation analysed on dependence of wood and char • properties
effects of grain orientation included • variation of transport phenomena, reacting medium properties and primary and secondary reactions included
Table 2.5 Features of the Models
Bamford et al. (84), Panton et al. (86), Wichman and Meleaan (113), Alves et al. (107,108).
Kanuary and Blackshear (87), Pyle and Zaror (101,102), Di В Iasi (109,111), Hastaoglu et al. (112), Kung (88,89).
Maa and Bailie (64,90)
Desrosiers and Lin (93), Saastamoinen (99),
Models including Mass Transfer Effects Fan et al. (91-93), Kansa et al. (94) Di Blasi
(109.111) , Kothari and Antal (78,79), Stiles (103), Villermaux et al. (50,51,100),
Uncoupled Heat and Kinetic Approach Philips et al. (98),
Models which predict product Yields Capart et al. (75,97), van Ginneken (95),
Wichman and Meleaan (113), Di Blasi et a!.
(109.110.111) .
