Large Eddy Simulation of Soot Formation in Oxy-Coal Combustion David O. Lignell, Alex J. Josephson, Benjamin Isaac, Kamron Brinkerhoff Brigham Young University, University of Utah AIChE Annual Meeting Salt Lake City Utah November 1, 2017
Acknowledgements • This material is based upon work supported by the Department of Energy, National Nuclear Security Administration, under Award Number(s) DE- NA0002375 • Support is acknowledged from the University of Utah, and Brigham Young University
Oxy-Coal Combustion • Coal remains an important source of power generation in the world. • Increased concern over CO 2 has led to development of various carbon capture methods. • Oxy-fuel was developed to allow affordable and simpler carbon capture. • In order develop oxy-coal systems more quickly, computer simulations have rapidly increased in accuracy and capabilities
Oxy-Fuel Combustor (OFC) • Lab-scale combustor • University of Utah • 100 kW • Down fired • Refractory-lined • 3 inch, k=0.15 W/m*K • No swirl
� OFC • Diameter = 0.6 m • Simulation length = 1.7 m • 100 kW capacity • Streams • Primary • Secondary • Purge • D p =1.6 cm, D s =3.5 cm �
� OFC • Diameter = 0.6 m • Simulation length = 1.7 m • 100 kW capacity • Streams • Primary • Secondary • Purge • D p =1.6 cm, D s =3.5 cm �
OFC SUFCO SKYLINE Coal Properties Bituminous Coal Bitumionous Coal • Primary Stream Properties � • Coal: 3.81 kg/hr • Coal: 4.47 kg/hr • CO 2 : 5.40 kg/hr • CO 2 : 7.48 kg/hr • O 2 : 1.04 kg/hr • O 2 : 1.22 kg/hr • T=300 K • T=366 K • Secondary • O 2 : 7.48 kg/hr • O 2 : 10.23 kg/hr • T = 489 K • T = 529 K • Purge • CO 2 : 3.08 kg/hr (total) • CO 2 : 3.85 kg/hr (total) • T=300 K • T=294 K • 3 radiometer inlets • 3 radiometer inlets �
Simulation Parameters • # grid cells = 9,562,500 • Δ x = Δ y = Δ z = 4 mm • L x = 1.7 m (down), • L y = L z = 0.6 m • Runtime ~10 seconds. • # processors: 1000-2000
Simulation: Models Radiation • Discrete Ordinates • S 8 model (80 rays) Gas Combustion • Coal scattering Particle Combustion • Gray gases Soot formation • Boundaries • matching radiative and wall conductive heat fluxes w ) = k T w − T o ✏ ( q i − � T 4 ∆ x w
Simulation: Models Radiation • Transporting 2 mixture fraction variables Gas Combustion • ξ , η Particle Combustion • for mass fractions of Soot formation primary gas and coal-off- gas. • Lookup table • Equilibrium • Tabulated in terms of ξ , η , heat loss
Simulation: Models • Coal Devolatilization Radiation • Yamamoto et al. PCI 32 Gas Combustion (2011) Particle Combustion • Parameters tuned using CPD Soot formation • Char Oxidation • Murphy & Shaddix model C&F 144 (2006) • Radiation • Discrete Ordinates • S 8 model (80 rays) • Coal scattering, Grey Gases
Simulation: Models • Particle Transport Radiation • Pedel et al. C&F160 (2013) Gas Combustion • DQMOM Particle Combustion • 3 quadrature nodes Soot formation • 7 internal coordinates • Raw coal mass • Char mass • Particle enthalpy • 3 velocity components • Transport equations for node weights and weighted abscissas.
Simulation: Models • Semi-empirical model Radiation • Brown and Fletcher Gas Combustion • Energy and Fuels, 12, Particle Combustion 745-757, 1998 Soot formation • Soot formation in coal systems from tar formation • M tar ~350 g/mol
Simulation: Models Radiation Gas Combustion Particle Combustion Soot formation Gasification/Oxidation
Simulation: Models • Transport tar and two soot Radiation moments Gas Combustion Particle Combustion Tar mass Soot formation ρ ˜ ∂ ¯ Y T ρ ^ v ˜ + r · (¯ ρ ˜ Y T ) + r · (¯ v 00 Y 00 T ) = S Y T ∂ t S Ytar = form tar - form soot - gasif tar - oxid tar Soot mass ρ ˜ ∂ ¯ Y s ρ ^ v ˜ + r · (¯ ρ ˜ Y s ) + r · (¯ s ) = S Y s v 00 Y 00 ∂ t S Ys = form soot - oxid soot - gasif soot Number density ρ ˜ ∂ ¯ N s ρ ^ v ˜ + r · (¯ ρ ˜ N s ) + r · (¯ s ) = S N s v 00 N 00 ∂ t S Ns = nucleation - aggregation
Simulation: Models Radiation Soot Oxidation Gas Combustion Lee oxidation model Particle Combustion Soot formation ✓ − E O 2 ◆ oxid soot = SA soot ∗ P O 2 · A O 2 · exp T 1 / 2 R gas T
Simulation: Models Radiation Soot Oxidation Gas Combustion Lee oxidation model Particle Combustion Soot formation ✓ − E O 2 ◆ oxid soot = SA soot ∗ P O 2 · A O 2 · exp T 1 / 2 R gas T • Data limited to temperature range that Lee took his measurements • Assumes that oxidation happens by O 2 molecule only • Experiments only took into account input
Global Jet Structure—Vorticity
Global Jet Structure—Vorticity
Sufco Results Temperature Y O2 0.8 2600 0.4 1450 300 0
Gasification of Soot fv soot • High soot concentration 6 • Soot is dispersed throughout the domain • This was not observed in the experiments 3 • Neglecting soot gasification • Not a good assumption for oxy-fired conditions with high CO 2 concentrations. 0
Gasification of Soot fv soot • Preliminary soot gasification model added. 6 S gasif = ρ s X CO 2 k gs exp( − E gs /RT ) 3 • Qin K., Characterization of Residual Particulates from Biomass Entrained Flow Gasification , Energy and Fuels 27:263-270 0 (2013)
Gasification of Soot fv soot Without Gasification • Preliminary soot gasification model added. 6 S gasif = ρ s X CO 2 k gs exp( − E gs /RT ) 3 • Qin K., Characterization of Residual Particulates from Biomass Entrained Flow Gasification , Energy and Fuels 27:263-270 (2013) 0
Gasification of Soot Y O2 Y CO2 fv soot Without Gasification 6 1.0 3 0.5 0 0
Soot Gasification and Oxidation Rates • A detailed Bayesian anaylsis was used to find optimal soot gasification and oxidation rates. • Oxidation - O 2 , OH - 13 studies included - Premixed, nonpremixed, TGA - Parameters: A O2 , E O2 , A OH ✓ − E O 2 � ◆ 1 r ox = A O 2 P O 2 exp + A OH P OH T 0 . 5 RT A.J. Josephson et al., Energy and Fuels 31: 11291-11303 (2017)
Soot Gasification and Oxidation Rates • A detailed Bayesian anaylsis was used to find optimal soot gasification and oxidation rates. • Gasification - CO 2 , H 2 O - 8 studies included - Parameters: A CO2 , E CO2 , A H2O , n, E H2O ✓ − E CO 2 ◆ r CO 2 = A CO 2 P 0 . 5 CO 2 T 2 exp RT r H 2 O = A H 2 O P n ✓ − E H 2 O ◆ H 2 O exp T 1 / 2 RT A.J. Josephson et al., Energy and Fuels 31: 11291-11303 (2017)
Oxidation Rates ✓ − E O 2 � ◆ 1 10 0 r ox = A O 2 P O 2 exp + A OH P OH Fenimore T 0 . 5 RT Neoh Ghiassi 10 -2 Kim Calculated Rates (kg/m 2 *s) Garo Marginal Posterior Puri Xu 0.6 10 -4 Lee 0.4 Chan Higgins 0.2 Kalogirou 0 10 -6 Sharma 1e-2 1e-1 1e0 1e2 1e-2 A O 2 × 10 -4 Marginal Posterior 10 -8 2.0e5 1 2 E O 0.5 1.7e5 10 -10 10 -10 10 -8 10 -6 10 -4 10 -2 10 0 1.5e5 0 1e-2 1e-1 1e0 1e2 1e-2 1.5e5 1.7e5 2.0e5 Measured Rates (kg/m 2 *s) A O E O 2 2 Marginal Posterior 5e-3 5e-3 1500 1000 A OH A OH 2e-3 2e-3 500 1e-3 1e-3 0 1e-2 1e-1 1e0 1e2 1e-2 1.5e5 1.7e5 2.0e5 1e-3 2e-3 5e-3 A O E O A OH 2 2 A.J. Josephson et al., Energy and Fuels 31: 11291-11303 (2017)
Oxidation Rates 10 0 ✓ − E O 2 � ◆ 1 Fenimore r ox = A O 2 P O 2 exp + A OH P OH T 0 . 5 RT Neoh Ghiassi 10 -2 Kim Calculated Rates (kg/m 2 *s) Garo Marginal Posterior Puri Xu 0.6 10 -4 Lee 0.4 Chan Higgins 0.2 Kalogirou 0 10 -6 Sharma 1e-2 1e-1 1e0 1e2 1e-2 A O 2 × 10 -4 Marginal Posterior 10 -8 2.0e5 1 2 E O 0.5 1.7e5 10 -10 10 -10 10 -8 10 -6 10 -4 10 -2 10 0 1.5e5 0 1e-2 1e-1 1e0 1e2 1e-2 1.5e5 1.7e5 2.0e5 Measured Rates (kg/m 2 *s) A O E O 2 2 Marginal Posterior 5e-3 5e-3 1500 1000 A OH A OH 2e-3 2e-3 500 1e-3 1e-3 0 1e-2 1e-1 1e0 1e2 1e-2 1.5e5 1.7e5 2.0e5 1e-3 2e-3 5e-3 A O E O A OH 2 2 A.J. Josephson et al., Energy and Fuels 31: 11291-11303 (2017)
H 2 O Gasification r H 2 O = A H 2 O P n ✓ − E H 2 O ◆ 10 0 H 2 O exp T 1 / 2 RT Calculated Rates (kg/m 2 *s) 10 -5 × 10 -6 Marginal Posterior 4 2 0 10 -10 1e2 1e4 1e5 1e7 Arnal A H 2 O Chhiti × 10 -5 Marginal Posterior 3.5e5 Neoh 4 Otto 2 O 3e5 Xu E H 2 10 -15 10 -15 10 -10 10 -5 10 0 2.5e5 0 1e2 1e4 1e5 1e7 2.5e5 3e5 3.5e5 Measured Rates (kg/m 2 *s) A H E H 2 O 2 O Marginal Posterior 6 0.5 0.5 4 n n 0.25 0.25 2 0 0 0 1e2 1e4 1e5 1e7 1e5 4e5 7e5 0 0.25 0.5 A H E H n 2 O 2 O A.J. Josephson et al., Energy and Fuels 31: 11291-11303 (2017)
H 2 O Gasification r H 2 O = A H 2 O P n ✓ − E H 2 O ◆ 10 0 H 2 O exp T 1 / 2 RT Calculated Rates (kg/m 2 *s) 10 -5 × 10 -6 Marginal Posterior 4 2 0 10 -10 1e2 1e4 1e5 1e7 Arnal A H 2 O Chhiti × 10 -5 Marginal Posterior 3.5e5 Neoh 4 Otto 2 O 3e5 Xu E H 2 10 -15 10 -15 10 -10 10 -5 10 0 2.5e5 0 1e2 1e4 1e5 1e7 2.5e5 3e5 3.5e5 Measured Rates (kg/m 2 *s) A H E H 2 O 2 O Marginal Posterior 6 0.5 0.5 4 n n 0.25 0.25 2 0 0 0 1e2 1e4 1e5 1e7 1e5 4e5 7e5 0 0.25 0.5 A H E H n 2 O 2 O A.J. Josephson et al., Energy and Fuels 31: 11291-11303 (2017)
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