Multicomponent conjugate heat and mass transfer in biomass materials during microwave pyrolysis for biofuel production

Fuel 211 (2018) 649–660

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Full Length Article

Multicomponent conjugate heat and mass transfer in biomass materials during microwave pyrolysis for biofuel production ⁎

F. Motasemi , A.G. Gerber

MARK

⁎

Department of Mechanical Engineering, University of New Brunswick, P. O. Box 4400, Fredericton, NB E3B 5A3, Canada

A R T I C L E I N F O

A B S T R A C T

Keywords: Numerical simulation CFD model Multicomponent analysis Microwave pyrolysis Biomass Biofuels

The aim of this paper is to investigate the heating behavior of biomass materials under microwave pyrolysis process. A detailed computational fluid dynamics (CFD) model is developed based on the finite volume method using ANSYS CFX (14.0) software to describe the heat and mass transfer during the microwave processing of biomass pellets. The article presents a modeling approach for incorporating the basic fundamentals of microwave pyrolysis process in the form of source terms for mass, momentum, heat and species into the general transport equations for nitrogen and volatiles in the gas phase and wood and bio-char in the solid phase. The model covers the complex coupling between several key elements of the process including microwave heating, pyrolysis kinetics, phase change, rapid variation in mixture properties and gas phase transport. The developed CFD model is validated through the experimental trials in a custom-built microwave pyrolysis unit. The model predicts the maximum temperature, temperature rates and temperature profiles during the process. Close agreement is obtained between the results obtained from the experiments and simulations. It was found that the biomass temperature is affected by the microwave absorbed power which is a function of biomass mixture properties and the released volatile during the process. The results also indicated that increase in microwave power level increases the maximum obtained temperature; however, the amount of absorbed power within the material decreases significantly in higher temperature levels. As temperature and power requirement are vital factors in making microwave processing viable, a useful CFD tool that provides this information could be invaluable for industry.

1. Introduction Biomass is one of the most promising alternative energy resources which is abundantly available on earth and has the potential to alleviate the reliance on fossil fuel, reduce pollution and global warming, and it can contribute to sustainable development [1]. Biomass can be used directly to produce energy e.g. dead trees/wood, or can be converted into value-added bio-products such as bio-oil, biodiesel, biofuels, bio-char and a variety of different bio-chemicals [2]. There are several thermal conversion routes available to process the biomass and waste materials such as torrefaction, pyrolysis and gasification. Pyrolysis is one of the emerging thermo-chemical processes in which the biomass is converted into solid, liquid and gaseous products at elevated temperatures (300–600 °C) and it takes place in the total absence of oxygen. Of various pyrolysis approaches, microwave technology has been demonstrated as an energy efficient technique for thermal processing of materials [3]. Microwave pyrolysis brings several advantages compared to conventional pyrolysis including rapid, selective and volumetric

⁎

heating [4]. Microwave systems have overall higher efficiencies and they can process high moisture content and large size materials. This can save considerable cost on unit operations such as drying and particle size reduction and ease the treatment and utilization of nonhomogeneous wastes [5]. The microwave assisted pyrolysis of biomass material has been reviewed extensively by Motasemi et al. [5]. Based on this review, microwave has been used to process different types of agricultural and forestry based biomass materials such as switchgrass [6], wheat straws [7], rice straws [8], corn stover [9], algae [10], coffee hulls [11], oil palm biomass [12], and different types of wood [13–15]. This technology has been used to process a variety of different waste materials as well and produce value added products such as bio-oil and bio-char [3]. The liquid or oil fraction is product of biomass pyrolysis which can be a promising alternative energy source for fuel oil or diesel [16]. It also has application in production of resin [17], adhesives [18] and several other bio-chemicals. Bio-char is another product of pyrolysis with several industrial applications such as feedstock for activated carbon

Corresponding authors. E-mail addresses: [email protected] (F. Motasemi), [email protected] (A.G. Gerber).

http://dx.doi.org/10.1016/j.fuel.2017.09.082 Received 29 March 2017; Received in revised form 16 September 2017; Accepted 18 September 2017 0016-2361/ © 2017 Elsevier Ltd. All rights reserved.

Fuel 211 (2018) 649–660

F. Motasemi, A.G. Gerber

Nomenclature

wt

A A0 Afs Cp D D Dh DP f h j k k0 kK K L MP P P P0 S T u uD uP VP

Greek symbols

cross section area specific surface area interfacial area between the liquid and solid specific heat diameter binary diffusion coefficient hydraulic diameter penetration depth mass fraction enthalpy imaginary unit thermal conductivity shape factor Kozeny constant permeability sample thickness microwave input power pressure power microwave surface power absorption source term temperature mixture velocity filter velocity pore velocity volume of the pellets

α ∊ μ ρ Δt τ Г

weight

volume fraction porosity dynamic viscosity (molecular) density time step tortuosity molecular diffusion coefficient

Superscripts h, h1, h2 energy u momentum f mass Subscripts s g r wp v c mod

solid phase gas phase relative wood pellet volatile char modified

however, the high temperature variation during the heating process can cause the change of material properties. There have been a few numerical studies conducted on the microwave processing of materials. The following are two representative studies on microwave pyrolysis simulation of biomass materials. Recently, Hussain et al. [28] investigated the microwave heating of large samples of oil palm empty fruit bunches using ANSYS CFX and Salema at al. [29] studied the effect of biomass loading height on the temperature profiles of empty fruit bunch (EFB) pellets under microwave irradiation. In both studies, energy equation was the only equation solved to predict the temperature profiles, while mass, momentum, energy and species equations along with microwave absorbed power equation need to be solved simultaneously in order to define the thermo-fluid phenomena correctly. Material properties were mostly assumed constant; however, the literature proves that these properties change greatly during the process [30–35]. Moreover, microwave pyrolysis is a transient problem; however, Hussain et al. assumed a steady state solution and Salema et al. solved the transient problem for only 10 s of the process which does not even present the moisture removal (drying) phase. Lastly, microwave absorbed power needs to be defined carefully based on the microwave theory and system efficiencies in order to obtain reliable results. It is apparent that previous studies have investigated the numerical simulation of biomass materials under microwave heating, but none have completed a comprehensive analysis considering the variation on material properties, multicomponent analysis and conjugate heat and mass transfer for biomass materials as a porous media. In most of the simulations, material properties were assumed constant while these properties are changing significantly in respect to temperature and processing phase of the process. It was also found that the majority of simulation studies were completed on food, ceramic, minerals, water and even human tissues [36] and there is a lack of sufficient research work on the microwave processing in forestry or agricultural based biomass materials. The main objectives of this research work are therefore:

production, feedstock for carbon nano-laments production and enhancing the soil quality as well [19–21]. The non-condensable gas produced during the pyrolysis process (light molecular weight gases) is an intermediate product which is mainly used for heating purposes. Recently, NASA is investigating the application of microwave pyrolysis for processing of space craft solid waste [22]. It was concluded that the microwave pyrolysis is a feasible technique for waste recovery in space. This method brings a significant reduction in the total energy requirement (∼70%) compared to conventional heating with a simpler and more compact apparatus [23]. Microwave pyrolysis has been also introduced as a method of recycling glass fiber from used blades of wind turbines in Europe [24]. Most of the previous studies have been completed using lab-scale microwave systems as a proof of concept. The following are the most relevant research works on microwave pyrolysis of biomass pellets into value-added products. Processing of Douglas fir sawdust pellet [25], wood pellets [26] and empty fruit bunch pellets [27] were reported using the microwave pyrolysis method. The results indicated that microwave input power, pyrolysis reaction temperature and material properties play critical roles in microwave processing of biomass materials which was in agreement with microwave pyrolysis of other sort of materials as well [5]. There is no doubt on the importance of experimental and theoretical studies in microwave heating; however, numerical simulations are crucial for further understanding of the microwave processing of materials, in particular the complex multiphysics problems which includes coupling between several elements of the process including microwave heating, pyrolysis kinetics, phase change, rapid variation in mixture properties and gas phase transport. This will allow us to have a more accurate temperature profile prediction during the process (thermal behavior of the material), and avoiding the design of unnecessary experimental prototypes. Numerical simulation of the microwave heating process is basically a multicomponent analysis which includes the microwave absorption equations (i.e. Lambert equation) and the mass, momentum, heat and species transport equations. The heating source in energy equation can be calculated by microwave dissipated power; 650

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• to propose a comprehensive CFD model in order to describe the heat • •

fN2 =

and mass transfer during microwave processing of biomass pellets using the finite volume method. to develop a modeling approach for incorporating the key elements of microwave pyrolysis process in form of source terms such as mass, momentum, heat and species added to the general transport equations. to validate the model with the results obtained from the experiments.

fv =

α N2 ρ N2 ρ

α v ρv ρ

(3) (4)

The thermal heat conductivity and density of nitrogen and volatile are assumed to be constant and not varied in respect to temperature. These properties including specific heat capacity are following the mixture rules as follows:

This study presents a tool to researchers and industrial players to examine the interaction between important elements of the microwave pyrolysis. Deeper insights will support improved designs and develop more efficient microwave processing systems and move toward commercialization of thermochemical microwave processing of biomass and waste materials.

cP = α N2 cP,N2 + α v cP,v

(5)

k = α N2 k N2 + α v k v

(6)

ρ = α N2 ρ N2 + α v ρv

(7)

2.1.2. Porous zone, gas phase In this zone, the multicomponent and mixture properties models are implemented, where the volatile from biomass pellets is released and mixed with the inlet nitrogen from zone A. The released volatile is defined as a source term, (Sgf 1) , in Table 1, and is equal to the mass source term, (Sgf 2) , which is added to the porous zone in gas phase. The heat transferred to porous zone (gas phase) from the solid phase, and the heat transferred by the movement of the released volatile to the gas phase in the porous zone are defined as a source term, (Sgh1) . This is equal to (Sgh2) generated in porous zone (solid phase) and the heat transferred from solid to gas phase has been explained in more details in section 2.1.5. The incorporation of the multicomponent model with species transport follows the spirit of the mixture approach with modifications related to CFD implementation in a finite volume solution method. In this zone, the governing energy equation conserves the diffusion, advection, and transient evolution in the domain, while the momentum equations account for the presence of biomass pellets and its resistance to volatile motion. The viscous and inertial forces are taken into account in momentum equations which has been explained extensively in section 2.1.4.

2. Mathematical modeling A CFD model is developed for simulating the thermo-fluid phenomena during microwave processing of biomass as a porous material. The model couples microwave heating, fluid flow, multicomponent analysis and mixture properties of the materials. In this study, the mechanism of biomass pyrolysis is based on absorbing the energy from the microwave source and transferring the thermal heat by conduction and convection. In fact, this model is implemented in order to solve the mass, momentum, heat and species transport equations through the biomass materials as porous media. 2.1. Governing equations The temperature profiles of biomass pellets under microwave heating are difficult to predict due to the complexity of the problem. Fig. 1 shows the layout of the problem and coupling of three different zones in the process. These three zones each contain their own combination of physical models; however, in order to determine the overall heating behavior of the biomass pellets, these models must be solved in a coupled manner. The basic zones include a non-porous zone, gas phase (zone A), a porous zone, gas phase (zone B) and a porous zone, solid phase (zone C). Table 1 has summarized the implementation of the governing equations for each zone in a compact manner. A general scalar advection-diffusion equation (GSADE), with source terms, is applied for each dependent variable in the solution with coefficients and source terms as outlined in this table. On the other hand, Fig. 2 demonstrates the numerical simulation procedure of microwave processing of biomass pellets. It indicates how the mixture properties and multicomponent analysis are coupled in the solution. As it can be seen, the individual component properties, mass fractions and eventually the mixture properties will be updated and calculated in each calculation loop. It will lead to the calculation of the microwave absorbed power and finally the temperature profiles of the biomass pellets during the pyrolysis process.

2.1.3. Porous zone, solid phase (porous zone) In the solid phase of porous zone, only the energy equation is solved. The material properties such as density, thermal heat conductivity, specific heat capacity, relative dielectric constant and loss factor are all functions of temperature. The source of heat, microwave oven, is following the Lambert’s law approach as it is described in the microwave absorbed power calculation in section 2.1.6. 2.1.4. Momentum source term, gas phase (porous zone) Porous medium is a material that consists of interconnected pores (voids). The porosity is defined as the fraction of the volume of voids over the total volume of the porous medium, a value between 0 and 1 [37], and it can be expressed as follows:

∊ = volume of voids /total volume

(8)

The permeability is a measure of the ability of porous materials to allow fluids to pass through it and has the unit of square meters (m2 ).

2.1.1. Non-porous zone, gas phase In zone A, mass, momentum, energy and species equations are solved for the inlet nitrogen and the outlet mixture of nitrogen and the released volatile from zone B. This provides the best estimate of inlet and outlet properties. Constitutive equations for mass fraction ( f ) and volume fraction (α ) describing the nitrogen (N2 ) and volatile (v ) in the non-porous gas phase are expressed as follows:

fN2 + fv = 1

(1)

α N2 + α v = 1

(2)

Fig. 1. Schematic of three different zones of microwave processing of biomass pellets.

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where Ap,t , is the total surface area of the pellets and ΔTfs is the difference between the temperature of wood pellets (solid phase) and the temperature of the mixture of nitrogen and volatile (gas phase), passing through the biomass bed. Based on this, the heat transferred out from the biomass pellets is defined as a source term in the solid phase, (Sgh2) , and the heat transferred into the gas phase is defined as a source term in the gas phase, ((Sgh1) ), as it is described in Table 2. These source terms are correlated and explained as follows:

Table 1 Governing equations for porous and non-porous zones. Governing equations

∂ (ρ∅)/ ∂t + div (ρ∅u ) = div (Γgrad∅) + S∅

∅

Γ

Source terms, S∅ = S∅ 1 + S∅ 2

S∅ 1

S∅ 2

Non-porous zone, gas phase 1 Massmix Momentummix (u)g ,(v )g

0 (μ)g

0 −∂P / ∂x ,−∂P / ∂y

0 0

Energymix

(h)g

(k / cp)g

0

0

Species, N2

fN2

ρD N2,m

0

0

Species, volatile

fv

ρD v,m

0

0

Sgh1 = −(Sgh2) = q/ VC . V

(14)

Porous zone, gas phase Massmix

1

0

0

(S f2)g

Momentummix

(u)g ,(v )g

(μ)g

−∂P / ∂x ,−∂P / ∂y

(S u)g

Energymix

(h)g

(k / cp)g

0

(S h1)g

Species, N2

fN2

ρD N2,m

0

0

Species, volatile

fv

ρD v,m

0

(S f1)g

Porous zone, solid phase Governing equations

∂ (ρ∅)/ ∂t = div (Γgrad∅) + S∅

2.1.6. Energy source term (microwave absorbed power), solid phase (porous zone) In this study, the internal generation of heat due to the microwave energy which quantifies the amount of absorbed power in the biomass materials is defined based on the famous Lambert’s law. Then, the temperature rise in biomass pellets during the microwave heating depends on the total microwave energy absorbed by the material. The volumetric microwave absorbed power can be expressed using an exponential decay proportional to penetration depth and surface absorption. The following discussion on Lambert’s law is based on the theory developed by Van Hipple [39].

∅

Source terms, S∅ = S∅ 1 + S∅ 2

P = P0 e (−y / Dp)

S∅ 1

S∅ 1

(S h3)

(S h2)s

where y is the distance from the surface, Dp is the penetration depth and P0 is the microwave surface power absorption and they can be presented as follow:

Energymix

(h)s

Γ

(k / cp)s

(15)

DP = (λ 0 /(2π 2εr′ ))/( 1 + (εr″/ εr′)2 ) Darcy found the relation between the pressure drop in a pipe to the filter velocity, (uD ), which is the measure of the mass flow rate divided by the product of the fluid density and the cross-sectional area of the system. The relation Darcy found is as follows:

μ ∇P = − uD K

MP = AP0

P = [(MP / A)/(1−e (−L / Dp) ) Dp] e (−y / Dp)

Pr ≈ 0.7 and 90 < ReD < 4000

(10)

Sgh3 = P / volume of pellets

(11)

(12)

The Reynolds number ReD = ρVD / μ is defined is term of the pellet diameter D and upstream velocity V that would exist in the empty channel without the pellets. The correction may also apply for a cylinder shape packed bed by multiplying the right hand side of Eq. (12) by correction factor of 0.79 [38]. The properties should be evaluated at the mean values of the fluid temperature entering and leaving the control volume. If the pellets are in the uniform temperature, the heat transfer rate from the pellets to the fluid can be computed from:

q = hAp,t ΔTfs

(18)

(19)

(20)

2.1.7. Mass/volatile source term, solid phase to gas phase (porous zone) The volatile (which is a mixture of bio-oil, gas and biomass moisture content) is defined as a fixed composition mixture and it is added into the gas phase of the porous zone as a source term (Sgf ). The volatile source term was modeled based on a widely used single overall reaction of pyrolysis kinetics mechanism for formation of bio-char and volatile (wood → biochar + volatile ) . This model neglects the presence and formation of ash and assumes released moisture content remains in the volatile. Most of the discussion in this section has been described by Prabir Basu [40]. In this model, the reaction rate depends on the portion of biomass which is not pyrolyzed and the decomposition rate of biomass, mb , can be expressed as:

which JH is the colburn j factor and is defined as

jH = (h / ρVCp ) Pr 2/3

(17)

The microwave absorbed power has been used to define the volumetric microwave absorbed power as a source term, (Sgh3) (Table 1) and it is defined as:

2.1.5. Energy source term, gas phase (porous zone) For a packed porous media, a large amount of heat transfer surface area can be obtained in a small volume. Many correlations have been developed based on shape, size and density. The following correlation has been recommended for gas flow in a sphere packed porous media to obtain the volumetric heat transfer coefficient, h [38].

εJH = 2.06ReD−0.575

e (−y / Dp) dy

where MP is the actual microwave input power, L is the sample thickness (m ), A is the cross section (m2 ), λ 0 is the microwave wavelength in free space, εr′ is the dielectric constant and εr″ is the dielectric loss factor, hence the absorbed power is as follow:

(9)

μ 1−ε uD + 1.8 3 ρ|uD |uD K εd

L

P0 = (MP / A)/(1−e (−L / Dp) ) Dp

The momentum source, is defined based on interfacial area density between solid and fluid ( Afs ) in the porous media, tortuosity and the extension of Macdonald’s correlation for multi-dimensional flows and it has been explained in details by M. Kaviany [37]. This momentum source term (Sgu ) can be expressed as follows:

Sgu = −∇P =

∫0

(16)

dmb = −K (T )(mb−mf ) dt

(21)

In this Equation, mb is the initial mass of biomass and mf indicates the mass of the remaining solid material during and after the reaction, K (T ) is the first order reaction rate which is a function of temperature (T ) and t is the time. The reaction rates were depends on the mass fractions of the reacting solid obtained from Thermogravimetric

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Fig. 2. The numerical simulation procedure of microwave processing of biomass pellets.

energy and pre-exponential factor were all estimated based on the pyrolysis model for wood developed and described by Prabir Basu [40] and Di Blasi [41]. The volatile conversion rate, k (T ) volatile , can also be easily calculated from Eq. (22). Based on these equations, the volatile released from biomass and the produced bio-char can be estimated as a functions of time and temperature. The volatile is introduced as a volumetric source term (Sgf ) into the gas phase of the porous zone.

Table 2 Specific heat capacity and thermal heat conductivity. Material properties of individual components Specific heat cp,gas = 770 + 0.629T −1.91 × 10−4T2 Capacity cp,bio − oil = −100 + 4.4T −1.57 × 10−3T2 ( J / kgK ) [42] cp,char = 420 + 2.09T + 6.85 × 10−4T2

cp,wood = 1500 + T Thermal heat Conductivity (W / mK ) [43]

kwood = 0.285;T ⩽ 473K

2.1.8. Assumptions The following are a few assumptions made in the present study in order to simplify the problem and reduce the computational time:

kwood − char = −0.617 + 0.0038T −4 × 10−6T2;473K ⩽ T ⩽ 663K

k char = 4.429 × 10−2 + 1.477 × 10−4T ;663K ⩽ T ⩽ 923K

• The initial temperature of biomass pellets is considered homogeneous • The simulation is completed by considering only a single 2.45 GHz magnetron frequency • The biomass pellet bed is considered and treated as a porous media • The volume change during the heating process is considered negligible • The incident microwave irradiation is considered normal to the

Analyzer and the famous Arrhenius equation and it is well-described by Di Blasi [41]. Equations below describe the reaction rates and their linear dependency:

k (T )i = Ai exp(−Ei/ RT )

(22)

k (T ) = k (T )bio − char + k (T ) volatile

(23)

where E is the activation energy and A is the pre-exponential factor. The reaction mechanism and the kinetics parameters including activation

material surface

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• Local thermal equilibrium • Biomass pellet properties are all temperature dependent

top of each other to form one test sample, with diameter (3.980 ± 0.050 mm), length (15.800 ± 0.100 mm), mass (0.119 ± 0.002 g), initial density (0.600 ± 0.050 g/cc), and final density at the end of the experiment (0.24 ± 0.050 g/cc). The samples were heated to the desired temperatures with a ramp rate of 5 (°C/min), starting at room temperature and progressing in ∼25 °C steps up to 150 °C, then 50 °C steps to ∼700 °C. The pyrolysis reaction was done with the spruce biomass sample pellets mounted inside a 4 mm ID quartz tube with a 0.01 (L/min) flow of nitrogen (N2 ) in order to avoid the oxidation and combustion. Further details of the experimental apparatus and cavity perturbation technique to measure the dielectric properties at high temperatures can be found in my previous publication on microwave dielectric characterization of switchgrass [31]. Thermogravimetric analysis (TGA) of spruce biomass was carried out in a TGA model Q500 (TA Instrument Inc., USA) in an inert environment (with nitrogen gas flow rate of 45 ml/min) from room temperature to 700 °C with heating rate of 25 (°C/min). The moisture content of the sample was determined by using an oven drying method as per the ASTM D4442-07 standard. The proximate analysis of the spruce biomass was as follows; volatile 77.86 wt%, fixed carbon 17.20 wt%, moisture content 4.94 wt% and the ultimate analysis of the spruce biomass was as follows; carbon 49.68 wt%, oxygen 43.88 wt%, hydrogen 6.21 wt%, nitrogen 0.21 wt%, and sulphur 0.02 wt%. The specific heat capacity, Cp , and the thermal heat conductivity, k , of the individual components of the material have been reported in the literature [42,43] and used in this study. The summary of these properties are presented in Table 2.

2.2. ANSYS CFX ANSYS CFX is a high-performance general-purpose Computational Fluid Dynamics (CFD) software. This tool integrates an advanced solver with pre and post processing capabilities that delivers reliable and accurate solutions across a wide range of CFD and multiphysics applications by solving the unsteady Navier-Stokes equations in their conservative form. A variety of problems including steady-state/transient flows, laminar/turbulent flows, heat transfer and thermal radiation, multiphase flows, etc. can be modeled using ANSYS CFX. This tool uses an element-based finite volume method, which first involves discretizing the spatial domain using a mesh. The transient response of the problem was needed for this study; therefore, a transient approximation was applied to the problem. Time discretization is achieved by Second Order Backward Euler scheme in order to solve the equations during the computational iterations. This solution approach uses a fully implicit discretization of the equations at any given time step. The finite volume method satisfies the conservation of the relevant equations (mass, momentum, energy, species, etc.) in a discrete sense for every value calculated in the iterative process. In the current work, CFX Expression Language (CEL) and User Functions were used in order to define the details of multiphysics phenomena which is described extensively in the previous section. 3. Validation

3.2. Microwave pyrolysis experiments 3.1. Material properties 3.2.1. Experimental apparatus and procedure The experimental results of microwave pyrolysis of biomass pellets were obtained from Bioenergy and Bioproducts Research Lab (BBRL), University of New Brunswick. The schematic diagram of the experimental set up is shown in Fig. 3. A domestic multimode microwave system (Panasonic, NN ST-6615, with maximum power of 1200 W and

The dielectric properties and thermogravimetric analysis of spruce biomass obtained from local region were measured in this study. The relative dielectric constant and loss factor (εr′ and εr″) of the samples were measured during pyrolysis using the cavity perturbation technique. Three pellets of spruce with similar dimension were stacked on

Fig. 3. The schematic diagram of microwave pyrolysis experimental set-up: (1) nitrogen generator; (2) nitrogen flow meter; (3) distributer plate; (4) biomass bed; (5) thermocouple; (6) the quartz glass reactor; (7) three-neck glass cap; (8) mechanical motor; (9) Pico data logger; (10) personal computer; (11) microwave magnetron; (12) condenser; (13) bio-oil collector.

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rate of mass loss remained almost insignificant and this phase was considered as the char stage. Dielectric properties of the spruce biomass increased from 75 to 200 °C due to low moisture content and higher dielectric properties of spruce biomass as it is shown in Fig. 4a. With the further increase in temperature from 250 °C to 300 °C, the dielectric properties in the pyrolysis stage decreased due to the breaking of biomass chemical bonds and release of volatile matter. From temperature 300 °C to 450 °C the dielectric properties almost remained constant. This might be due to continuation of pyrolysis reaction in which the polar components released during “thermal cracking” of biomass are immediately volatized, and therefore this might not contribute to the increase in dielectric properties [32,33,35]. There are two main reasons behind this drastic drop in dielectric properties during the pyrolysis reaction. Firstly, most of the biomass weight (about 70–90%) is lost during the drying and pyrolysis stages as shown by TG analysis in Fig. 4a. Consequently, this decreases the density which might cause a significant decrease in the number of atoms per unit volume and polarizability of the sample. The second reason might be the release of remaining bound or capillary water during the early pyrolysis stage within the chemical structure of biomass [45]. This behavior of dielectric properties during the drying and pyrolysis stages was in total agreement with previous studies [26,31,45,46]. Fig. 4b illustrate the TG analysis and a drastic increase in dielectric properties of biomass pellets in the char stage. The loss of an electrically insulating barrier [45] due to the thermal decomposition of biomass samples, transformation of phase to carboneous char [26] and increase in temperature could be the main reasons behind this sudden increase in dielectric properties. The char also consists of free electron conduction due to possible change in the structure order during pyrolysis which might have led to high dielectric constant and loss factor in the char stage compared to drying and pyrolysis. Therefore, researchers have used it as an efficient microwave absorber in many biomass pyrolysis applications [12,26,47]. The results were in agreement with dielectric properties of bituminous coal [46], pine pellets [26], hay [32], switchgrass [31], corn stover [30], oat and barley straws [48]. It can be concluded that the ability of the char to convert electromagnetic energy into heat is significantly higher than the original biomass. The results also indicated that dielectric properties of woody based biomass are nearly three times bigger than agricultural based biomass [30–32,48]. Then woody based biomass or a mixture of woody [49] and agricultural biomass are more suitable material for microwave processing.

2450 MHz frequency) was modified to carry out the experiments. A quartz glass tube with 10 cm inner diameter and 15 cm length was placed in the microwave cavity as the reactor. It was covered with a three neck glass lid from the top and a single neck glass lid from the bottom. The system was equipped with an overhead stirrer ( ± 3 rpm), an anchored single-blade stainless steel, with 0.007 m diameter and 0.07 m wide, and a K-type thermocouple ( ± 2.2 °C/0.75%, greater value). The nitrogen gas (99% purity) was fed from the top of the reactor 6 min prior to the start of microwave pyrolysis experiments to provide an inert environment (oxygen-free gas environment). Three thin wire meshes of 100 µm were used to support the biomass pellets at the bottom of the reactor which also facilitated the exit of vapors from the bottom of the reactor into the condensing unit. The stirrer speed was controlled by a 70 W motor IKA®Works, Inc. The thermocouple was connected to a Pico data logger acquisition system ( ± 0.5 °C/0.2%, greater value). The data logger was linked to a personal computer for continuous recording of real time data. The reactor was connected by a pipe to the condensers and the collector. During pyrolysis the heavier volatiles were condensed and collected into liquids as bio-oils and the lighter volatiles (non-condensable gases) escaped at the end of the condensers. The spruce biomass pellet was used as the feedstock for the experiments. The Denver Instrument SI-2002 with 2000 g capacity ( ± 0.01 g readability) was used to weight the samples before the experiments. The experimental temperature profiles obtained from microwave pyrolysis process are used for validation of the numerical model. 3.2.2. Microwave system efficiency According to the literature, the microwave systems have the overall efficiency of 80–85% depending on the microwave frequency and applied power [44]. This value for the lab-scale microwave pyrolysis system used in this study is calculated using the theory of the microwave oven power measurement. In this method, microwave oven power is measured in terms of the temperature rise experienced by a given volume of water (1 L), when exposed to the microwave oven power for a specific time period of 87 s. 3.3. Thermogravimetric analysis and dielectric properties Based on TG analysis, the thermal decompositions of biomass pellets are divided into three distinct stages. The initial mass loss of the material between room temperature and ∼100 °C was due to the removal of the free and bound moisture. This initial stage of biomass heating is referred as the drying phase. After the removal of moisture, heat is transferred to the biomass interior which causes a sharp drop in the weight specially between 200 °C and 450 °C. This stage is referred as pyrolysis stage, where the major loss (∼75 wt%) in biomass weight occurred due to the release of volatile components. Beyond 450 °C, the

3.4. Microwave system efficiency Based on the results from microwave efficiency measurement, it was found that the overall efficiency of the microwave pyrolysis system

Fig. 4. Thermogravimetric analysis and dielectric properties of spruce biomass pellets vs. temperature under nitrogen environment at 2450 MHz in two temperature ranges of (a) room temperature to 450 °C and (b) 450 °C to ∼700 °C.

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4. Results and discussion

used in this study is about 81.89%. This is an average value of microwave efficiency with power levels of 120 W to 1200 W. The microwave efficiency and the actual microwave input power levels in specific nominal input power levels of 360, 480 and 600 W are presented in Table 3. As it can be seen from the results, the estimation of actual microwave input power levels can play an important role on estimating the actual microwave absorbed power by the material and the temperature profiles obtained from the simulations as well.

4.1. Model representative results Fig. 7 shows the simulated surface temperature distribution, microwave absorbed power, volumetric volatile mass flow rate and specific heat capacity of the biomass pellets bed at the end (t = 600 s) of the process. As it can be seen, the temperature profile in different locations of the sample are different. This is mainly due to two reasons; first the variation in microwave absorbed by the biomass in different locations and the flow of carrier gas which is moving from top to the bottom of the reactor. As it can be seen, the microwave absorption characteristics of biomass is higher at lower bottom left of the biomass bed compared to the lower bottom right, then the temperature is at higher levels. It is also found that the biomass pellets temperature is lower at the top due to the continuous flow of nitrogen which was fed from top of the reactor in order to create an oxygen free environment for the pyrolysis process. Biomass characteristics and the released volatiles are also affected by the change in temperature of the material. This behavior is expected as material properties (e.g. Table 2 and Fig. 4) and the kinetics of pyrolysis (Eqs. (22) and (23)) are functions of temperature. This figure also shows the ability of the developed model in predicting the temperature profiles while taking into account the effects of different physics and changes which is happening during the process.

3.6. Validation of temperature profiles (numerical vs experimental) The simulation results of the microwave pyrolysis of biomass pellets including temperature profiles are presented and compared with the results obtained from the experiments. The simulation results are obtained by solving mass, momentum, energy and species equations in ANSYS CFX 14.0 for 200 g of biomass pellet load and microwave input power of 360, 480 and 600 W. The porous media properties used in the simulations are summarized in Table 4. Porosity, interfacial area density, volumetric heat transfer coefficient and permeability (in order to calculate the viscous, Kperm , and inertial forces, Kloss , in momentum equation) are all calculated based on the developed theory which is discussed in the methodology. Fig. 5a, c and e illustrate a comparison between temperature profiles from simulation and the mean value of temperature profiles obtained from experiments including the two standard deviation for the microwave input power level of 360, 480 and 600 W, respectively. It can be seen that the simulation and experimental results follow the same trend and they are in good agreement. The minimum and maximum temperatures obtained from the experiments versus the results obtained from simulation are also presented in for the microwave input power level of 360, 480 and 600 W in Fig. 5b, d and f, respectively. The results clearly show that the developed CFD model can be applied in different power levels and the simulated results agreed closely with the experimental temperature profiles. The minimal disagreement between the simulated and experimental temperatures can be attributed due to a few following reasons. First of all, inaccurate placing the thermocouples during the experiments can lead to measurement errors of temperature. The main reason behind this phenomenon is the low temperature nitrogen gas which is fed from the top of the reactor. If the thermocouple is placed above the tracking point (which in this study was the middle of biomass bed), the experimental measured temperature would be lower and if the thermocouple is placed below the tracking point, the experimental measured temperature would be higher. Motasemi et al. [5] and Fernandez et al. [3] considered this as the major problem during the experimental temperature measurements and Pitchai et al. [50] reported this as one of the main obstacles for validation of temperature profiles from experiments with the simulation. All the small errors in temperature reading might result in significant changes in experimental temperature profiles. Fig. 6 shows the effect of probe location on the temperature profiles for 200 g of biomass pellets under 480 W microwave power. As it can be seen, the maximum temperature obtained from the simulation can be varied by over 40 °C with only 4 mm adjustment in probe location. This proves the importance of probe location and the effect of fluctuation of the probe location on the final recorded temperature profiles during the process. Secondly, the moisture present at the surface of biomass materials can be heated at a very fast rate during microwave processing of materials [51]. At temperatures more than 100 °C, the present moisture in the biomass moves out of the surface which would prevent further increase in the surface temperature of the biomass. Lastly, intraparticle mass and heat transport resistance of material could also result in deviations of the simulated temperature profiles from experimental data. Such microscopic details of material that is treated macroscopically in the physics applied may cause errors in predicted values [52].

4.2. Effect of microwave input power The effect of microwave input power level on the stabilized temperatures obtained by the material is also illustrated in Fig. 5. The final/ stabilized process temperature is an effectual factor in design and development of microwave pyrolysis systems [3,5,53]. The temperature profiles reached a steady condition after 400, 300 and 200 (sec) for microwave input power of 360, 480 and 600 W, respectively. The results indicate that the stabilized temperature is increasing by using higher microwave power levels. The match between the biomass load and microwave input power can increase the overall efficiency of the process for that particular type of biomass material [5]. The microwave input power also has a clear effect of the rate at which temperature is rising during the microwave pyrolysis process. As it can be seen from Fig. 5, the simulated temperature profiles are growing with a higher rate to be stabilized at higher power level of 600 W compared to 480 W and 360 W. These results are verified with the experimental data. Table 5 presents the stabilized process temperature and the rate of increase in temperature in different power levels obtained from simulations and experiments. The stabilized temperature during the process are in a close agreement with the maximum stabilized temperature obtained from different runs in each experimental conditions; however, the temperature rates obtained from simulation are slightly higher compared to experimental data. This difference may be attributed due to the complex pyrolysis process and the effect of primary and secondary reactions during the pyrolysis process [40]. 4.3. Effect of material properties Another remarkable feature of the developed CFD model was Table 3 Nominal and actual microwave input power levels.

656

Nominal power level (W)

Microwave system efficiency (%)

Actual power level (W)

360 480 600

87.50 79.69 89.58

316.24 382.51 534.99

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Table 4 Summary of the properties in porous media. Properties

Value

Porosity, ε Interfacial area density, Afs

0.199 620.068

Volumetric heat transfer coefficient, h Kperm

137.971

K loss

15246.303

9.826 × 10−9

implementing the variation of material properties of biomass materials during the process and applying the mixture rule to define the mixture properties. Material properties are influencing the simulated temperature profiles during microwave processing of materials [29]. As it is mentioned in the previous chapter, specific heat capacity, thermal heat conductivity and density are defined as functions of temperature for individual components. Defining the mixture properties based on the fractions of individual components and mixture rules makes the mixture properties as functions of temperature and time. Fig. 8 shows the change in the mixture properties of spruce biomass material during the process (converting from wood to biofuels). It can be clearly seen that defining the mixture properties based on the stage of the process and eventually temperature resulted in a more accurate trend of temperature profiles. The agreement between simulated and experimental

Fig. 6. Effect of 2 mm adjustment in probe location (480 W and 200 g biomass).

Fig. 5. Numerical vs. experimental temperature profiles including two standard deviation, minimum and maximum temperatures for 200 g of biomass pellets; (a) and (b) 360 W, (c) and (d) 480 W, (e) and (f) 600 W.

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Fig. 7. Simulated temperature profile (a), microwave absorbed power (b), volumetric volatile mass flow rate (c) and specific heat capacity (d) of biomass pellets bed under microwave field (360 W and 200 g biomass) at the end of the process (t = 600 sec).

Fig. 8. The change of material mixture properties during the process.

The main reason for the significant fall in the amount of microwave power absorbed by biomass pellets is behind the decrease in dielectric properties of the material with increase in temperature as it is illustrated in Fig. 4. This result indicates the need to use a power level combination in order to minimize the energy consumption which plays a critical role in viability of biomass processing.

Table 5 Difference in simulated and maximum experimental stabilized temperatures and corresponding temperature rates during microwave pyrolysis. Power level (W)

360 480 600

Max Temperature (°C)

Temperature Rate (°C/s)

Simulation

Experiment

Simulation

Experiment

347.06 386.98 427.80

360.11 389.98 408.01

0.795 1.181 1.869

0.773 1.105 1.587

temperature profiles indicated the accurate mixture properties prediction. 4.4. Effect of dielectric properties on microwave absorbed power Fig. 9 shows the temperature profiles and microwave absorbed power for three different actual microwave power levels of 360, 480 and 600 W. As it can be seen, when the power level increases, consequently the maximum obtained temperature rises. This is mainly due to the higher microwave absorbed power exclusively in the first stage of the process. Another interesting finding is that, by increasing the temperature of biomass pellets, the amount of absorbed power within the material decreases significantly. The drop in absorbed power is happening sharper in higher power levels and higher temperatures.

Fig. 9. Temperature and microwave absorbed power profiles versus time at three different actual microwave input power levels of 360, 480 and 600 Watts.

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Appl Pyrolysis 2013;100:49–55. http://dx.doi.org/10.1016/j.jaap.2012.11.016. [8] Huang YF, Kuan WH, Lo SL, Lin CF. Hydrogen-rich fuel gas from rice straw via microwave-induced pyrolysis. Bioresour Technol 2010;101:1968–73. http://dx.doi. org/10.1016/j.biortech.2009.09.073. [9] Huang Y-F, Kuan W-H, Chang C-C, Tzou Y-M. Catalytic and atmospheric effects on microwave pyrolysis of corn stover. Bioresour Technol 2013;131:274–80. http://dx. doi.org/10.1016/j.biortech.2012.12.177. [10] Yiqin Wan, Yingkuan Wang, Xiangyang Lin, Yuhuan Liu, Chen Paul, Yecong RRLi. Experimental investigation on microwave assisted pyrolysis of algae for rapid biooil production. Nongye Gongcheng Xuebao/Trans Chin Soc Agric Eng 2010;26:295–300. [11] Dominguez A, Menendez JA, Fernandez Y, Pis JJ, Nabais JMV, Carrott PJM, et al. Conventional and microwave induced pyrolysis of coffee hulls for the production of a hydrogen rich fuel gas. J Anal Appl Pyrolysis 2007;79:128–35. http://dx.doi.org/ 10.1016/j.jaap.2006.08.003. [12] Salema AA, Ani FN. Microwave induced pyrolysis of oil palm biomass. Bioresour Technol 2011;102:3388–95. http://dx.doi.org/10.1016/j.biortech.2010.09.115. [13] Miura M, Kaga H, Tanaka S, Takahashi K, Ando K. Rapid microwave pyrolysis of wood. J Chem Eng Japan 2000;33:299–302. http://dx.doi.org/10.1252/jcej.33. 299. [14] Miura M, Kaga H, Sakurai A, Kakuchi T, Takahashi K. Rapid pyrolysis of wood block by microwave heating. J Anal Appl Pyrolysis 2004;71:187–99. http://dx.doi.org/ 10.1016/S0165-2370(03)00087-1. [15] Chen M, Wang J, Zhang M, Chen M, Zhu X, Min F, et al. Catalytic effects of eight inorganic additives on pyrolysis of pine wood sawdust by microwave heating. J Anal Appl Pyrolysis 2008;82:145–50. http://dx.doi.org/10.1016/j.jaap.2008.03. 001. [16] Ikura M, Mirmiran S, Stanciulescu M, Sawatzky H. Pyrolysis liquid-in-diesel oil microemulsions. 1998. [17] Fini EH, Kalberer EW, Shahbazi A. Biobinder from swine manure: sustainable alternative for asphalt binder. 2011. [18] Oehr K. Acid emission reduction. 1995. [19] Day D, Evans RJ, Lee JW, Reicosky D. Economical CO2, SOx, and NOx capture from fossil-fuel utilization with combined renewable hydrogen production and largescale carbon sequestration. Energy 2005;30:2558–79. http://dx.doi.org/10.1016/j. energy.2004.07.016. [20] Imam T, Capareda S. Characterization of bio-oil, syn-gas and bio-char from switchgrass pyrolysis at various temperatures. J Anal Appl Pyrolysis 2012;93:170–7. http://dx.doi.org/10.1016/j.jaap.2011.11.010. [21] Mullen CA, Boateng AA, Goldberg NM, Lima IM, Laird DA, Hicks KB. Bio-oil and bio-char production from corn cobs and stover by fast pyrolysis. Biomass Bioenergy 2010;34:67–74. http://dx.doi.org/10.1016/j.biombioe.2009.09.012. [22] Serio MA, Cosgrove JE, Wójtowicz MA. Microwave-assisted pyrolysis of solid waste. System 2011:1–20. http://dx.doi.org/10.2514/6.2011-5124. [23] Serio M, Cosgrove J, Wójtowicz M, Wignarajah K, Fisher J. A compact, efficient pyrolysis/oxidation system for solid waste. 40th Int. Conf. Environ. Syst. American Institute of Aeronautics and Astronautics; 2010. http://dx.doi.org/10.2514/6.20106009. [24] Akesson D, Foltynowicz Z, Christeen J, Skrifvars M. Microwave pyrolysis as a method of recycling glass fibre from used blades of wind turbines. J Reinf Plast Compos 2012;31:1136–42. http://dx.doi.org/10.1177/0731684412453512. [25] Ren S, Lei H, Wang L, Bu Q, Chen S, Wu J, et al. Biofuel production and kinetics analysis for microwave pyrolysis of Douglas fir sawdust pellet. J Anal Appl Pyrolysis 2012;94:163–9. http://dx.doi.org/10.1016/j.jaap.2011.12.004. [26] Robinson JP, Kingman SW, Barranco R, Snape CE, Al-Sayegh H. Microwave pyrolysis of wood pellets. Ind Eng Chem Res 2010;49:459–63. http://dx.doi.org/10. 1021/ie901336k. [27] Salema AA, Ani FN. Pyrolysis of oil palm empty fruit bunch biomass pellets using multimode microwave irradiation. Bioresour Technol 2012;125:102–7. http://dx. doi.org/10.1016/j.biortech.2012.08.002. [28] Hussain SA, Bano S, Yeoh HS, Rozita O. Simulation on temperature distribution of oil palm empty fruit bunches during the microwave pyrolysis process. Asia-Pacific J Chem Eng 2014;9:39–49. http://dx.doi.org/10.1002/apj.1744. [29] Salema AA, Afzal MT. Numerical simulation of heating behaviour in biomass bed and pellets under multimode microwave system. Int J Therm Sci 2015;91:12–24. http://dx.doi.org/10.1016/j.ijthermalsci.2015.01.003. [30] Motasemi F, Salema AA, Afzal MT. Dielectric characterization of corn stover for microwave processing technology. Fuel Process Technol 2015;131:370–5. http:// dx.doi.org/10.1016/j.fuproc.2014.12.006. [31] Motasemi F, Afzal MT, Salema AA, Mouris J, Hutcheon RM. Microwave dielectric characterization of switchgrass for bioenergy and biofuel. Fuel 2014;124:151–7. http://dx.doi.org/10.1016/j.fuel.2014.01.085. [32] Motasemi F, Afzal MT, Salema AA. Microwave dielectric characterization of hay during pyrolysis. Ind Crops Prod 2014;61:492–8. http://dx.doi.org/10.1016/j. indcrop.2014.07.046. [33] Sait HH, Salema AA. Microwave dielectric characterization of Saudi Arabian date palm biomass during pyrolysis and at industrial frequencies. Fuel 2015;161:239–47. http://dx.doi.org/10.1016/j.fuel.2015.08.058. [34] Beneroso D, Albero-Ortiz A, Monzó-Cabrera J, Díaz-Morcillo A, Arenillas A, Menéndez JA. Dielectric characterization of biodegradable wastes during pyrolysis. Fuel 2016;172:146–52. http://dx.doi.org/10.1016/j.fuel.2016.01.016. [35] Tripathi M, Sahu JN, Ganesan P, Dey TK. Effect of temperature on dielectric properties and penetration depth of oil palm shell (OPS) and OPS char synthesized by microwave pyrolysis of OPS. Fuel 2015;153:257–66. http://dx.doi.org/10.1016/ j.fuel.2015.02.118. [36] Menendez JA, Arenillas A, Fidalgo B, Fernandez Y, Zubizarreta L, Calvo EG, et al.

5. Conclusions A CFD model is developed to describe the heat and mass transfer phenomena during microwave processing of biomass pellets. The numerical multicomponent fluid flow with heat and mass transfer of biomass pellets as porous media is successfully solved using ANSYS CFX (14.0). The model presents an approach for incorporating the key elements of microwave pyrolysis process in form of source terms such as mass, momentum, heat and species to provide the necessary details of the process. The developed CFD model can be applied to Torrefaction process without any changes and it can also be applied to gasification process with minimal changes. Torrefaction is considered a mild or pyrolysis at lower temperature levels with the same process mechanism and pyrolysis is one of the main steps in gasification which means gasification kinetics is slightly different from pyrolysis kinetics. This shows the generality of the model. The temperature profile, the maximum temperature during the process and the heating rate obtained from simulations were in close agreement with the experimental results. It was concluded that the biomass temperature is affected by microwave absorbed power, biomass mixture properties and the released volatile during the process. These key elements are crucial for further development and optimization of thermochemical processing of biomass materials for biofuel production. It was concluded that the probe location significantly influences the temperature profiles obtained during the experiments. A sensitivity study was performed and the maximum temperature obtained from the simulation was varied by over 40 °C with only 4 mm adjustment in probe location for 200 g of biomass and 480 W microwave power input. It was also found that higher microwave input power (600 W) is more suitable to start the process with; however, lower microwave input power (360 W) is a better choice to continue the process with after the temperature is reached the desired temperature for pyrolysis. This is mainly due to the drop in dielectric properties at temperatures between 200 °C and 500 °C. Implementation of this power level range can significantly decrease the required energy to produce biofuels using microwave processing. The developed model is useful for design and simulate the microwave processing systems for biofuel and bio-product applications. It can also improve the quality of the heating process for chemical processing industries and microwave manufacturers. Acknowledgments The authors appreciate the financial support from Graduate School (University of New Brunswick, Canada). Microwave Properties North (http://microwavepropertiesnorth.ca/) and Bioenergy and Bioproducts Research Lab (BBRL) from University of New Brunswick are acknowledged for the dielectric measurements and microwave pyrolysis experiments. References [1] Hall DO. Biomass energy in industrialised countries—a view of the future. For Ecol Manage 1997;91:17–45. http://dx.doi.org/10.1016/s0378-1127(96)03883-2. [2] Enweremadu CC, Mbarawa MM. Technical aspects of production and analysis of biodiesel from used cooking oil—a review. Renew Sustain Energy Rev 2009;13:2205–24. http://dx.doi.org/10.1016/j.rser.2009.06.007. [3] Fernandez Y, Arenillas A, Menendez JA. Microwave heating applied to pyrolysis. InTech 2011. [4] Motasemi F, Ani FN. A review on microwave-assisted production of biodiesel. Renew Sustain Energy Rev 2012;16:4719–33. http://dx.doi.org/10.1016/j.rser. 2012.03.069. [5] Motasemi F, Afzal MT. A review on the microwave-assisted pyrolysis technique. Renew Sustain Energy Rev 2013;28:317–30. http://dx.doi.org/10.1016/j.rser. 2013.08.008. [6] Zhou R, Lei H, Julson JL. Effects of reaction temperature, time and particle size on switchgrass microwave pyrolysis and reaction kinetics. Int J Agric Biol Eng 2013;6:53–61. [7] Zhao X, Wang M, Liu H, Zhao C, Ma C, Song Z. Effect of temperature and additives on the yields of products and microwave pyrolysis behaviors of wheat straw. J Anal

659

Fuel 211 (2018) 649–660

F. Motasemi, A.G. Gerber

[37] [38] [39] [40] [41]

[42] [43] [44] [45]

[46]

Microwave heating processes involving carbon materials. Fuel Process Technol 2010;91:1–8. http://dx.doi.org/10.1016/j.fuproc.2009.08.021. Kaviany M. Principles of heat transfer in porous media. New York: Springer; 1999. Bergman TL, Incropera FP, DeWitt DP, Lavine AS. Fundamentals of heat and mass transfer. Wiley; 2011. Von Hippel A. Dielectric materials and applications. Artech House; 1995. Basu P. Biomass gasification, pyrolysis and torrefaction: practical design and theory. Academic Press; 2013. Di Blasi C. Modeling chemical and physical processes of wood and biomass pyrolysis. Prog Energy Combust Sci 2008;34:47–90. http://dx.doi.org/10.1016/j.pecs. 2006.12.001. Grønli MG. A theoretical and experimental study of thermal degradation of biomass. na; 1996. Hankalin V, Ahonen T, Raiko R. On thermal properties of a pyrolysing wood particle. Process Eng 2009:1–20. Meredith RJ. Engineers' handbook of industrial microwave heating. Institution of Electrical Engineers; 1998. Peng Z, Hwang J-Y, Mouris J, Hutcheon R, Sun X. Microwave absorption characteristics of conventionally heated nonstoichiometric ferrous oxide. Metall Mater Trans A 2011;42:2259–63. http://dx.doi.org/10.1007/s11661-011-0652-9. Peng Z, Hwang J-Y, Kim B-G, Mouris J, Hutcheon R. Microwave absorption

[47]

[48]

[49] [50]

[51]

[52] [53]

660

capability of high volatile bituminous coal during pyrolysis. Energy Fuels 2012;26:5146–51. http://dx.doi.org/10.1021/ef300914f. Abubakar Z, Salema AA, Ani FN. A new technique to pyrolyse biomass in a microwave system: effect of stirrer speed. Bioresour Technol 2013;128:578–85. http://dx.doi.org/10.1016/j.biortech.2012.10.084. Motasemi Farough, Adam Salema Arshad, Afzal MT. Microwave dielectric properties of agricultural biomass at high temperature and in inert environment. Trans ASABE 2015;58. Torgovnikov GI. Dielectric properties of wood and wood-based materials. SpringerVerlag; 1993. Pitchai K, Birla SL, Subbiah J, Jones D, Thippareddi H. Coupled electromagnetic and heat transfer model for microwave heating in domestic ovens. J Food Eng 2012;112:100–11. http://dx.doi.org/10.1016/j.jfoodeng.2012.03.013. Pitchai K, Chen J, Birla S, Gonzalez R, Jones D, Subbiah J. A microwave heat transfer model for a rotating multi-component meal in a domestic oven: development and validation. J Food Eng 2014;128:60–71. http://dx.doi.org/10.1016/j. jfoodeng.2013.12.015. Christie M, Glimm J, Grove JW, Higdon DM, Sharp DH, Wood-schultz MM. Error analysis and simulations of complex phenomena. Los Alamos Sci 2005:6–25. Mohan D, Pittman CU, Steele PH. Pyrolysis of wood/biomass for bio-oil: a critical review. Energy Fuels 2006;20:848–89. http://dx.doi.org/10.1021/ef0502397.