Particle scale char gasification models for biomass fuels

Transcription

1 Finnish-Swedish Flame Days 2013, Gasification Workshop, , Jyväskylä Particle scale char gasification models for biomass fuels Kentaro Umeki Div. Energy Science Dept. Engineering Sciences and Mathematics Luleå University of Technology, Sweden

2 Background Agenda Particle scale biomass char gasification models Phenomenological model for intrinsic reaction rate Reaction mechanism Surface area development Catalytic activity of ash (K, Na, Ca, Mg, Fe, etc.) Considering intra-particle diffusion Considering external diffusion Summary and future challenges Red letters: Focus of this presentation (especially important for biomass fuels)

3 Solid-phase Gasphase Raw biomass Drying ( 100 C) Dry biomass Devolatilization ( C) Char Ash Mass transfer Heat transfer Gasification (> 700 C) Combustion (>500 C)

4 Char gasification Rate controlling step Slower than devolatilization by a few orders of magnitude High heating value of char Char yield from devolatilization: ~10% on weight basis, but 15-30% on energy basis Target for energy balance in allothermal gasifiers Endothermic reactions (with CO 2 /H 2 O) Convert sensible heat to useful chemical energy

5 Reactor scale Particle scale Microscopic scale Plant scale

6 Partice scale (mass diffusion) models? Important to predict char conversion accurately hence, important for gas composition as well Majority of current CFD models do NOT consider particle-scale (diffusion) phenomena 1. Develop constitutive equations to implement? 2. Find (numerically) efficient ways for coupling particle and reactor models? This presentation focuses on approach 1.

7 Important factors for char gasification Catalytic activity of inorganic matters O 2 CO 2 H2O Surface area External and intra-particle diffusion

8 Residual mass [g] Char conversion X Definitions m m ini Conversion rate dx r dt ini m m fin Apparent rate 0,4 0,3 0,2 0,1 0 m m fin m ini Conversion rate observed as a lump of chemical reaction and mass diffusion Intrinsic rate m ini - m Conversion rate of pure chemical reaction (when diffusion is negligible) m ini - m fin Elapsed time [s]

9 Common strategy for modelling Intrinsic reaction rate (1) reaction conditions dependent models based on reaction mechanisms: (k(p,t)) (2) Char conversion dependent models describing reactive surface area and catalytic activity: f(x) Intra-particle diffusion Effectiveness factor: External particle diffusion Mass balance in gas film r int = k p, T f X r app = η r int [e.g. A. Gómez-Barea and B. Leckner, Prog. Combust. Energy Sci. 2010]

10 Phenomenological models for intrinsic reaction rate Reaction mechanism Surface area development Catalytic activity of ash (K, Na, Ca, Mg, Fe, etc.) For more detail: K. Umeki, A. Moilanen, A. Gómez-Barea, J. Konttinen, A model of biomass char gasification describing the change in catalytic activity, Chemical Engineering Journal (2012)

11 Single-step reaction model C+γ O 2 2(1-γ) CO+(2γ-1) CO 2 C+H 2 OCO+H 2 C+CO 2 2CO k p, T = AP ga n exp E/RT Arrhenius plots from the reference will be shown.here. [C. Di Blasi, Prog. Energ. Comb. Sci. 35 (2009) ]

12 Detailed reaction model C+γO 2 2(1-γ) CO+ (2γ-1) CO 2 2C+O 2 2C(O) C(O) CO 2C(O) CO 2 + C C+CO 2 C(O) + CO C+H 2 OCO+H 2 C+H 2 O C(O) + H 2 O C(O) CO C+H 2 C(H) 2 C+1/2H 2 C(H) C+CO 2 2CO C+CO 2 C(O) + CO C(O) CO k p, T = O2, H2O, CO2 C C C C C k 1f P CO2 H2, CO, CO2 Examples (Langmuir-Hinshelwood model) k p, T = k p, T = k 1fk 2 P O2 O k 1f P O2 + k 2 Char (carbon) k 1f P H2O 1 + k 1b /k 2 P CO + k 1f /k 2 P CO2 H 1 + k 1f /k 3 P H2O + k 3f /k 3b P H2

13 Phenomenological models for surface area Models Overall reaction Shrinking core Random pore [Yagi 1953] [Bhatia 1980] Overlapped grain Percolation [Adschiri 1987] [Reyes and Jensen 1986] Reaction Throughout particle Particle surface Pore surface Overlapped grains surface Each carbon site in lattice

14 Function f(x) for different models Models Overall reaction Shrinking core Random pore Overlapped grain Percolation f(x) with f(x=0)=1 ( 1 X ( 1 X 2 ) ( 1 X ) 1 ln(1 X ) ) /3 0 ) X ]{1 (ln 0) ln[1 (1 0 ) ]} [ 1 (1 X (1 1 X )[1 (1 0) 0 X ] Ψ= 4πL o (1-ε o )/S o ε o : Initial porosity L o : Total length of pores per unit volume S o : Pore surface area per unit volume

15 1. 2. Models 1. Overall reaction 2. Shrinking core Random pore 4. Overlapped grain 5. Percolation 4. 5.

16 Catalytic activity of inorganic content K, Ca, Na, Mg and Fe known as catalyst Si, P and Al known to deactivate catalytic activity Difficult to observe actual catalytic activity due to its own transformation (vaporization, reaction, sintering) In-situ experiments are necessary for the observation of catalytic activity

17 Previous models describing catalytic activity Ref. Zhang et al. Fuel (2008) Zhant et al. Fuel (2010) Struis et al. Chem Eng Sci (2002) Dupont et al. Bioresour Technol (2011) Kitsuka et al. Energy Fuel (2007) Kajita et al. Energy Fuel (2010) Löwenthal, PhD thesis (1993) Model r r int int k(1 X ) 1 ln(1 X ) 1 k(1 X ) 1 ln(1 X ) 1 cx p p p bt r k(1 X ) 1 ln(1 X ) 1 1 int am m b 2/ 3 rint k k Si 1 X r r r int int int k k k k t k X ) exp 2(1 k2(1 X ) 1 k t 2 k3(1 X ) 1 ln(1 X ) 2 2 p

18 Isothermal TGA Schematic diagram of isothermal TGA will be shown.here. Mimic reaction conditions of commercial gasifiers Rapid heating rate and in-situ gasification (no cooling and reheating) Reaction conditions of FBG and cyclone gasifiers ( K; CO 2 -CO-H 2 O-H 2 ; MPa) [A. Moilanen, Doctoral thesis, VTT publication 607, 2006]

19 Conversion rate analysis by integral method If conversion rate is first-order: dx/dt = k 1 X By integration:1 X = exp( kt) ln(1-x) should be linear function of t Three regimes were observed. 1st/2nd regimes: linear functions Which is first-order reaction with respect to char conversion? Typical experimental data

20 Instantaneous reaction rate 2nd regime is first-order reaction! If dx/dt = k 1 X 1 dx = const. 1 X dt Typical experimental data Initial stage of char gasification: K, Na evaporation 1st regime Loss of catalytic activity?

21 Observed reaction mechanism 1. Catalytic char gasification w/ fast catalyst loss 2. Non-catalytic char gasification 3. Catalytic char gasification w/o catalyst loss

22 Three-parallel reactions model r = dx dt = r cg,1 + r ncg + r cg,2 1st regime: Catalytic gasification with deactivation r cg,1 = k cg,1 exp ξx 2 2nd regime: Non-catalytic gasification r ncg = k ncg 1 X 3rd regime: Catalytic gasification without deactivation r cg,2 = k cg,2

23 Effect of biomass species Biomasses with low Si in ash Poor predictability. Negative rate coefficient Biomasses with high Si in ash Good model predictability!! Governing deactivation mechanism Reaction with Si?

24 Effect of reaction atmosphere H 2 O-H 2 system Poor predictability. CO 2 -CO system Good model predictability!! Catalytic activity maintained under H2O-H2 system?

25 Intra-particle mass diffusion K. Umeki, S. Roh, T. Min, T. Namioka, K. Yoshikawa, A simple expression for the apparent reaction rate of large wood char gasification with steam, Bioresource Technology 101 (2010),

26 Models describing pore diffusional effect : very good : good : not so good Effect of initial diameter Diameter change Pseudoactivation energy Effective factor Simplified numerical simulation Direct numerical simulation Comp. time General versatility Calc. method Arrhenius plot Theoritical value Modify! (Effective factor) = rapp/rint Quantum method Numerical solution of PDEs

27 Macro-TG experiments Precision scale Gas cylinder Pump MFC Syringe pump (water) Temp.: 1123, 1173, 1223 K Steam: 0.02, 0.04, 0.06 Mpa Gas velocity: 5 L/min Thermocouple

28 Effect of particle diameter (1173 K, PH2O =0.04 MPa)

29 Simplified reaction model 0 < X < X1 X1 < X < X2 X2 < X <1 1 X X X1 r r r r Change of local char conversion and particle size 0 < X < X1 Uniform reaction X1 < X < X2 Shrinking reaction X2 < X < 1 Uniform reaction

30 Modification of effective factor Original Modified expression Thiele module Thiele module V S n 1 2 k c cg D C ea n1 AS Effective factor 1 1 tanh(3 ) 1 3 [Bischoff 1965] Effect of particle size change Effective factor η= rapp/rint Effect of local intrinsic rate

31 Predictability with theoretical parameters (1173 K, H 2 O: 0.04 MPa) Experimental data: solid lines Calculated data: dashed lines

32 External mass diffusion

33 Overall conversion rate with external diffusion C+a Agases (CO, H 2 and CO 2 ) (Amount of agent consumed in particle) = (Amount of agent diffusing to char surface) S k p C Mass loss rate of carbon from stoichiometry dm c dma a dt dt M C kc D a S p Ab M k A c As S p D Ab D As As Ab kc D D dm dt c Effective rate constant: k e M a M k k c C A c S p k e D D Ab D Sh D d AB p

34 Summary Intrinsic rate can be usually expressed as k(p,t)f(x), but parallel reaction model may be appropriate for describing catalytic activity Effect of intra-particle diffusion can be included by applying effectiveness factor Effect of external diffusion can be included by effective rate constant Future works More understanding of ash transformation and modification of models of catalytic activity Consideration of fragmentation in particle scale models Generalization of models to various shape

35 Co-workers Acknowledgment Catalyst model: Dr. A. Moilanen (VTT); Prof. A. Gómez-Barea (U. Sevilla); Prof. J. Konttinen (U. Jyväskylä) Intra-particle diffusion model: Dr. S. Roh and Dr. M. Taijin (Korean Inst. Machinery and Materials); Prof. T. Namioka and Prof. K. Yoshikawa (Tokyo Inst. Tech.) Finance Catalyst model: Bio4Energy, Nordic Energy Top-Level Initiative Pore diffusion model: Japan Society for the promotion of Science and Korea Science and Engineering Foundation