Proceedings of the ASME 2016 Heat Transfer Summer Conference HT2016 July 10-14, 2016, Washington, DC, USA
HT2016-7281
NUMERICAL SIMULATION AND OPTIMIZATION OF A CARBON MONOXIDE BOILER Guangwu Tang, Bin Wu, Chenn Q. Zhou Center for Innovation through Visualization and Simulation (CIVS), Purdue University Calumet, Hammond, IN, 46323 Email:
[email protected] ABSTRACT Carbon monoxide (CO) boilers play an important role in the petroleum refining industry, completing the combustion of CO in the flue gas generated by the regeneration of fluidized cracking catalyst. The heat released by the CO combustion is used to generate steam for use in the refinery. The flue gas flow path can have a significant effect on the thermal efficiency and operation safety of the boiler. In this paper, a CO boiler which had been experiencing low thermal efficiency and high operation risks was studied. A three-dimensional (3D) computational fluid dynamics (CFD) model was developed with detailed description on the combustion process, flow characteristics and heat transfer. The results obtained from the model have good agreement with the plant measurement data. The heat transfer between the tubes and the combustion flue gas was optimized by adding a checker wall.
The FCC flue gas treating can be composed of several sections: an oxidizer section, a flue gas cooler section (boiler), a DeNOx section, a DeSOx section and a stack. The process during the operation of a CO boiler involves many complicated mechanisms, such as combustion, turbulent mixing, convection and radiation heat transfer, and DeNOx/DeSOx reactions [2]. Therefore, a poor performance of a CO boiler can have a detrimental effect on steam production and pollutant reduction. In an operating CO boiler, evidence of poor performance can be seen in low efficiency combustion process, uneven heat convection between high temperature combustion flue gas and the steam in the tubes, refractory damaged by high temperature combustion flue gas and so on. Any of the poor performance issues could lead to mechanical or structural failures requiring shutdown, inspection and maintenance. In order to alleviate the extra-cost due to unsatisfactory performance, further studies on the CO boilers are needed. Physical experimentation methodology is an old but practical way engineers often use to gain a better understanding of the boilers, but full scale measurements are restricted by high risk and cost [3]. In conjunction with physical experiments, numerical methods can help to conduct computational experiments effectively and safely.
Key words: CFD, Carbon Monoxide Boiler, Fluid Flow, Heat Transfer, Optimization. INTRODUCTION In the modern petroleum-refining plants, a large amount of flue gas generated in the Fluid Catalytic Cracking (FCC) regenerator has a certain fraction of carbon monoxide, which contains a wealth of thermal energy that could be retrieved. In addition, the flue gas generated in the FCC regenerator has other regulated contaminant species besides CO, such as NOx and SO2, which need further treatment before being released to the outside environment. The carbon monoxide boiler plays an important role in the petroleum refining process for its function in retrieving the flue gas thermal energy and reducing the air pollutant [1]. The thermal energy retrieved by the CO boiler produces steam for other processes, and therefore reduces the cost of petroleum refining.
Computational Fluid Dynamics (CFD) is a process of replacing the complex Partial Differential Equations (PDEs) that govern the flow and reactions with a simpler system of algebraic equations, and then performing calculations on the large amount of divided cells in a domain through iterations that refer to boundary conditions. Using CFD models, individuals can conduct experiments using computers at different operation conditions, and can help visualize the results both statistically and graphically [4-6]. Chun-Lang Yeh conducted numerical investigation on a carbon monoxide boiler, based on the CFD model, the effect of important
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parameters including refractory thickness, geometry change, inlet air flow rate and flue gas flow rate were studied. Other researchers also numerically studied boilers combust CO. S.S. Hou et al[3] studied steel mill boilers which mainly combust CO from the blast furnace. The results show that the CO combustion has good flame stability and reduces NOx emission. Qingyan Fang et al[7] numerically studied a 200 tangentially fired utility boiler combust multi-fuel including pulverized coal, blast furnace gas (BFG) and coke oven gas (COG), where the large amount blast furnace gas contains around 20 percent CO. The results indicate that with the cofiring of 20% heat input blast furnace gas and 10% heat input coke oven gas, the performance improved. Many other research papers also reported advantages in using low BTU fuel sources in the boilers [8-12].
volume dilation. By the long-time averaged method, Equation (2) can be converted to Reynolds-averaged Navier-Stokes (RANS) equation as follows 𝜕 𝜕𝑥𝑗
(𝜌𝑢𝑖 𝑢𝑗 ) = −
𝜕𝑝 𝜕𝑥𝑖
+
𝜕
[𝜇 (
𝜕𝑢𝑖
𝜕𝑥𝑗
𝜕𝑥𝑖 𝜕
𝜕𝑥𝑗
+
𝜕𝑢𝑗 𝜕𝑥𝑖
2
𝜕𝑢𝑙
3
𝜕𝑥𝑙
− 𝜎𝑖𝑗
)] +
(−𝜌𝑢𝑖 ′ 𝑢𝑗 ′ )
(4)
In Equation (4), the Reynolds stresses may be related to the velocity gradient by Boussinesq hypothesis as follows: −𝜌𝑢𝑖 ′ 𝑢𝑗 ′ = 𝜇𝑡 (
𝜕𝑢𝑖
𝜕𝑥𝑗
+
𝜕𝑢𝑗 𝜕𝑥𝑖
2
𝜕𝑢 𝑘
3
𝜕𝑥𝑘
) − (𝜌𝑘 + 𝜇𝑡
)𝛿𝑖𝑗
(5)
where 𝜎𝑖𝑗 is the stress tensor due to molecular viscosity 3.
The Energy Equation ∇ ∙ [𝑣⃗(𝜌𝐸 + 𝑃)] = ∇ ∙ [𝑘𝑒𝑓𝑓 ∇𝑇 − ∑𝑗 ℎ𝑗 𝐽⃗𝑗 + (𝜏̿𝑒𝑓𝑓 ∙ 𝑣⃗) ] + 𝑆ℎ (6) where k eff is the effective conductivity and 𝐽⃗𝑗 is the diffusion flux of species j. The first three terms on the righthand side of the equation represent energy transfer due to conduction, species diffusion, and viscous dissipation respectively. Sh includes the heat of chemical reaction, and any other volumetric heat sources.
In this paper, simulations are conducted on one CO boiler in a petroleum refining plant suffering from some heat transfer deficiencies between the hot combustion flue gas and the steam in the tubes. The combustion process in the existing CO boiler under different boundary conditions was not fully understood and may cause some deficiencies in the combustion reactions. Additionally, the flow characteristics under the existing boiler geometry may influence the combustion and heat transfer phenomena, which need to be studied and further optimized. In order to solve deficiency related problems, such water pipe failure, a three-dimensional (3D) turbulence reacting flow computational fluid dynamics model was developed. The model took turbulence, combustion, convection and radiation into consideration. The developed CFD model was validated by field data, which showed good agreement. Based on the developed CFD model, the combustion process, flow characteristics, and heat transfer in the CO boiler were studied. The effect of one checked wall design on the flow pattern inside the CO boiler was evaluated.
𝑆ℎ = − ∑𝑖 where − ∑𝑖
ℎ𝑖0 𝑀𝑊,𝑖
ℎ𝑖0
𝑀𝑊,𝑖
𝑅𝑖 −∇qr
(7)
𝑅𝑖 is the heat source due to chemical
reaction. ℎ𝑖0 is the enthalpy of formation of species i and 𝑅𝑖 is the volumetric rate of creation of species i. −∇qr is the heat sources due to the radiation. E is defined as: 𝑝
𝑣2
𝜌
2
𝐸 =ℎ− +
(8)
Where sensible enthalpy h is defined for incompressible ideal gases as 𝑝 ℎ = ∑𝑗 𝑌𝑗 ℎ𝑗 + (9)
CFD MODEL AND METHODOLOGY Various boiler configurations and fuel inputs may require different computational fluid dynamics models. In this study, numerical models were developed based on the real process and conditions. Detailed turbulent combustion flow with heat and mass transfer was examined. The Eddy Dissipation Concept turbulence combustion model was used to calculate the combustion reactions. The realizable k-ε turbulence model was applied to predict flow turbulence. The P1 radiation model was used to take account of the dominant heat transfer flux.
𝜌
where 𝑌𝑗 is the mass fraction of species j, and ℎ𝑗 is defined as 𝑇 ℎ𝑗 = ∫298.15𝐾 𝐶𝑝,𝑗 𝑑𝑇 (10) where 𝐶𝑝,𝑗 is the constant pressure specific heat of species j. 4.
Turbulence Model
The gas flow pattern in the urea decomposition chamber after entering the burner shows high turbulence intensity characteristic as its vortex mixing mechanism. This turbulence phenomenon can be solved by time averaged velocity scalar. The averaged Reynolds stresses term can be solved through the conservation of kinetic energy and dissipation rate, which called the k- turbulence model [13]. The Realizable k- turbulence model is used due to its ability to model flow with strong streamline curvature, vortices and rotation. It is a semiempirical model based on the transport equation for the turbulence energy (𝑘) expressed below respectively:
Governing equations 1. The Mass Conservation Equation (Continuity equation) ∇ ∙ (𝜌𝑣⃗) = 0 (1) 2. The Momentum Conservation Equation ∇ ∙ (𝜌𝑣⃗𝑣⃗) = −∇𝑝 + ∇ ∙ (𝜏̿) + 𝜌𝑔̅ + 𝐹̅ (2) Where p is the static pressure, ρg̅ and F are the gravitational body force and external body force, and τ is the stress tensor which is given by 2 𝜏̿ = 𝜇 [(∇𝑣⃗ + ∇𝑣⃗ 𝑇 ) − ∇ ∙ 𝑣⃗𝐼] (3) 3 Where 𝜇 is the molecular viscosity, 𝐼 is the unit tensor, and the second term on the right hand side is the effect of
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𝜕 𝜕𝑥𝑖
(𝜌𝑘𝑢𝑖 ) =
𝜕 𝜕𝑥𝑖
𝜇𝑡
[(𝜇 +
)
𝜕𝑘
𝜎𝑘 𝜕𝑥𝑖
concept model (EDC) [14]. The EDC model relies on the Kolmogorov cascade of energy dissipation on all lengths scales in turbulence flow. The chemical reactions and molecular mixing were assumed associate with turbulence dissipation occurred in fine structure of the flow. The source terms in the conservation equation for the mean species, i modeled as
] + 𝐺𝑘 + 𝐺𝑏 − 𝜌𝜀 − 𝑌𝑀 + 𝑆𝐾 (11)
𝜇𝑡 = 𝑐𝜇 𝜌
𝑘2
(12)
𝜀
The generation of kinetic energy and buoyance force attribution are: 𝜕𝑢𝑗 𝐺𝑘 = −̅̅̅̅̅̅ 𝑢𝑖′ 𝑢′𝑗
(13)
𝐺𝑏 = 𝛽𝑔𝑖
(14)
𝜕𝑥𝑖 𝜇𝑡 𝜕𝑇
𝑃𝑟𝑡 𝜕𝑥𝑖
𝑅𝑖 =
𝜕𝑥𝑗
(𝜌𝜀𝑢𝑗 ) =
𝜕
𝜇
𝜕𝑥𝑗
[(𝜇 + 𝑡)
𝜕𝜀
] + 𝜌𝐶1 𝑆 − 𝜌𝐶2
𝜎𝜀 𝜕𝑥𝑗 𝜀 𝐶1𝜀 𝐶3𝜀 𝐺𝑏 𝑘
𝜀2 𝑘+√𝜈𝜀
+ 𝑆𝜀
ŋ
ŋ+5
1 𝜕𝑢𝑗 2 𝜕𝑥𝑖
𝑘
), ŋ =s , s= √2𝑆𝑖𝑗 𝑆𝑖𝑗 , 𝑆𝑖𝑗 = ( 𝜀
and C1ε are constant.
𝜕𝑢𝑖
𝜕𝑥𝑗
𝑣𝜀
∗ = 𝐶 (𝑘 2)1/4
), C2
𝑣
𝜏 ∗ = 𝐶𝜏 ( )1/2 𝜀
𝜇𝑡
)∇𝑌𝑖
(20)
(21)
Radiation Model In an operating boiler where the heat transfer is dominated by radiation, correct computation of the thermal radiation can accurately predict the temperature field and the heat fluxes at the walls of the boiler, which are of great importance. The discrete ordinate method has been applied by previous researchers [15]. Daniel J.O. Ferreira investigated two different numerical radiation methods to simulate a boiler and proposed that both the P1 approximation and Discrete Transfer Model are adequate for the radiation inside the boiler [16]. The radiation heat flux qr as function of incident radiation intensity in P1 model is:
(16)
Ri is the net rate of production of species i by chemical reactions. ⃑𝐽𝑖 is the diffusion flux term of species i, which arises due to gradients of concentration and temperature, under which the diffusion flux is given bellow: 𝑆𝑐𝑡
(19)
7.
Species Conservation Equation During the operation process, the natural gas burns with the combustion air supplied from the burner and water evaporation occurs in the high temperature circumstance. Therefore, the species transport model is used to track the species conservation and transportation. The local mass fraction of each species, Yi, can be solved by the convection-diffusion equations. The conservation equation of each species can be expressed by
⃑𝐽𝑖 = −(𝜌𝐷𝑖,𝑚 +
(18)
Where ∗ is the mass fraction occupied by the fine structure regions, 𝐶 is a volume fraction constant with a value of 2.1377. The reactions are assumed to occur in the fine structures over a residence time scale 𝜏 ∗ . 𝑣 is Kinematic viscosity.
5.
∇ ∗ (𝜌𝑣̅ 𝑌𝑖 ) = −∇ ∗ ⃑𝐽𝑖 + 𝑅𝑖
(𝑌𝑖∗ − 𝑌𝑖 )
Where, 𝑌𝑖0 represents the mass fraction of species 𝑖 in the fluid surrounding the fine structures.
(15)
+
𝜏∗ [1−( ) ]
𝑌𝑖 = (∗ )3 𝑌𝑖∗ + (1 − (∗ )3 )𝑌𝑖0
+
Where the equations are given for the 𝑥𝑗 direction. σk and σε are the turbulent Prandtl number for 𝑘 and ε, 1.0, 1.2. 𝜇𝑡 is the turbulence viscosity, Gk is the generation of turbulent kinetic energy due to the mean velocity gradients. Gb is the generation of turbulence kinetic energy due to buoyancy. YM represents the contribution of the fluctuating dilatation in compressible turbulence to the overall dissipation rate. Sk and Sε are user-defined source terms, which are 0 in this model. C1 = max(0.43,
∗ 3
Where 𝜌 is the mean fluid density, 𝑌𝑖∗ is the mass fraction of species 𝑖 within the fine structures after reacting over the time 𝜏 ∗ . Yi is the Favre-averaged mass fraction of species 𝑖 obtained from
The turbulent dissipation rate ε is expressed by: 𝜕
2
𝜌(∗ )
qr = −
1 3(a+σs )−Cσs
∇G = −∇G
(20)
where a is the absorption coefficient, σs is the scattering coefficient, G is the incident radiation, C is the linearanisotropic phase function coefficient. The transportation equation for incident radiation G is:
(17)
∇(∇G) − aG + 4a𝑛2 σT 4 = 𝑆𝐺
Where, 𝐷𝑖,𝑚 is the diffusion coefficient for specie i in the mixture, 𝑆𝑐𝑡 is the turbulent Schmidt number, which is 0.7.
(21)
where σ is the Stefan-Boltzmann constant and 𝑆𝐺 is the user-defined radiation source, in this case, 0.
6.
Eddy Dissipation Concept Combustion Model The detailed Arrhenius chemical reaction kinetics of natural gas, ethylene, and thane combustion can be incorporated in turbulent flames through Eddy-dissipation
−∇qr = aG − 4an2 σT 4
3
(22)
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The expression for −∇qr can be directly substituted into the energy equation to account for the heat sources due to the radiation.
Approximately 6 million cells were used in the simulation. The hybrid technique was used with fine mesh near the steam tubes to increase the accuracy for predicting heat transfer phenomena near steam tubes. The mesh is shown in Figure 1 (b). The Yplus value near the tubes is around 180.
8.
Convection Model The convection heat transfer between the high temperature combustion flue gas and the steam in the tubes was naturally occurring during CO boiler operation. For the turbulent steam flow in the tubes, the heat transfer coefficient can be calculated by equation: ℎ=
𝑘𝑤 𝐷𝐻
𝑁𝑢
Outlet
(23)
Tempering Air Inlet CO Inlet
Where ℎ is the heat transfer coefficient, 𝑘𝑤 is the thermal conductivity of the bulk fluid, 𝐷𝐻 is the hydraulic diameter. The Nusselt number 𝑁𝑢 , Prandtl number 𝑃𝑟 and Reynolds number 𝑅𝑒 can be calculated by the following equations: 𝑁𝑢 = 0.023 × 𝑅𝑒 0.8 × 𝑃𝑟 0.4 𝐷𝑉𝜌 𝑅𝑒 = 𝑃𝑟 =
𝜇 𝜇𝐶𝑝 𝑘
Air Inlet
Water tubes
(24) (25) (26)
(a)
21 3 4 5 Burners 6
where 𝐷 is tube diameter, 𝑉 is the steam velocity, 𝜌 is the steam density, 𝐶𝑝 is the specific heat, 𝑘 is the thermal conductivity, and 𝜇 is the dynamic viscosity. n = 0.4 for heating (wall hotter than the bulk fluid) and 0.33 for cooling (wall cooler than the bulk fluid). GEOMETRY AND SIMULATION METHOD Simulation domain and mesh A 3-D geometry has been developed based on the drawings of CO boiler structure, which is shown in Figure 1 (a). The flue gas generated in the FCC regenerator will be charged into the CO boiler through the CO inlet. The tempering air is supplied for the combustion of flue gas. The tempering air and the flue gas will mix at the channels and be directed down to the CO combustion chamber. Auxiliary fuel is charged though the fuel inlets which consist of 6 burners equally spaced with each other. During the operation, only two of the fuel burners are normally used. The air inlet supplies air for the auxiliary fuel combustion process. The combustion of both flue gas and fuel occurs in the combustion chamber, and the high temperature combustion flue gas will be directed upwards and travel through the tubes. The radiation and convection heat transfer occur between the high temperature flue gas and the steam in the tubes.
(b) Figure 1. (a) Simulation domain and (b) mesh Simulation code and solution method This simulation was conducted by the commercial software package ANSYS Fluent 13.0. The Finite Volume Method (FVM) was used to solve the partial differential equations by discretizing the equations using an upwind differencing scheme over the finite volumes [17]. The SIMPLE algorithm was used to adjust the pressure and velocities after each iteration when solve the gas momentum equations. The calculations were conducted on the HPC (High Performance Computer) cluster Peregrine1 in Purdue University Calumet.
The geometry modeling process was conducted in software ANSYS Workbench Design Modeler, which is a powerful tool for the construction of complicated geometry. The inner profile of the carbon monoxide boiler was drawn without taking into consideration the wall thickness. Additionally, the wall boundary condition was considered to be adiabatic.
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BOUNDARY CONDITIONS During the boiler operation, different fuels are input through different boundaries. The operation boundary conditions are shown in Table 1.
As seen in Figure 2, three thermocouples are used to measure the temperature at different positions. In the combustion chamber zone, TC3 and TC2 were placed below the combustion chamber top wall near the elbow turning point. In the convection zone, TC1 was placed below the tubes. The temperature contour indicates that after the CO and auxiliary fuel mix with the combustion air, combustion takes place. The high temperature zone is mostly located in the combustion chamber. The high temperature combustion flue gas also appears along the chamber floor, reaching the convection zone and being directed upwards by the back side wall. The temperature measurements by these three thermocouples and the simulation results are listed in Table 4.
Table 1 Boundary conditions Boundaries
CO
Velocity(ft/s) Temperature
(oF)
Flue
Auxiliary
Tempering
Air
Gas Inlet
Fuel Inlet
Air Inlet
Inlet
221.5
111.0
7.3
7.3
1346
100
95
95
Based on the composition of the fuels, the chemical reaction mechanisms are referred from the ANSYS Fluent database, shown in Table 2. The two step methane combustion mechanism is applied and the reaction rates are controlled by the reaction kinetics. The fuel species compositions are shown in Table 3. Table 2 Reaction Mechanism FUEL Methane
CHEMICAL FORMULA
F
3
1CH4 + O2 → 1CO + 2H2O 2 1
TC 1
1CO + O2 → 1CO2 + 0H2O 2
1CO2 → 1CO + 0.5 O2
TC 3 TC 2
1
Hydrogen
1H2+ O2→1H2O
Ethane
1C2H6+ O2→2CO2 + 3H2O
Ethylene
1C2H4 + 3O2 → 2CO2 + 2H2O
7
2
Figure 2. Temperature contour and Thermocouple positions
2
Table 3 Fuel species compositions Species O2 N2 H2O CO2 CO C2H6 C2H4 CH4 H2
Air (mol) 21% 79%
Flue Gas (mol)
Auxiliary Fuel (mol)
71.49% 8.98% 9.84% 9.69%
5.55%
31.81% 10.27% 38.93% 13.44%
A B
C D
F North
South RESULTS AND DISCUSSIONS
Figure 3. Temperature contour and Thermocouple positions near the back wall
Validation In order to evaluate the developed CFD model, a field experiment was conducted under a certain operation condition to compare CFD results with the measurement. In this validation, temperature measurements were obtained by the thermocouples in both the combustion chamber zone and the convection zone. The temperature contour at the center plane of the CO boiler shown in Figure 2 is the simulation results output from the CFD model. The temperature contour near the back wall is shown in Figure 3.
Table 4 Fuel species compositions
5
TC1
TC2
TC3
Measurement
1746 oF
1779.3 oF
1758.5 oF
Validation
1700 oF
1650 oF
1600 oF
Difference
46 oF
129 oF
158.5 oF
Percentage error
2.60 %
7.25 %
8.98 %
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convection area. The third circulation occurs near the major CO combustion flue gas stream due to the velocity difference.
Table 5 Fuel species compositions TC Position
mid north C
north
A
mid south B
Measurement oF Validation oF
1842.7
1873.3
1734.0
1730.5
1790
1820
1800
1780
Difference oF
52.7
53.3
66
50.5
2.86 %
2.85 %
3.81 %
2.92 %
TC Name
Percentage error
south
D
Figure 3 shows the temperature contour of a face near the back wall. It is shown that below the water tubes, the combustion gas temperature appears high and the temperature varies from the center to the left and right sides. As the combustion gas passes by the water tubes, the gas temperature decreases due to the heat exchange between the water tube and the combustion flue gas. The thermocouples on the back wall were placed below the tubes and the measured temperature values are close to the simulation results. According to Table 5, the difference between the measurement and the CFD results ranges from 50.5 oF to 66 oF. The percentage error of the difference ranges from 2.85% to 3.81%, which indicates that the prediction from the CFD model is quite close to the real measurement. Therefore, based on the temperature validation, the developed CFD model on this particular CO boiler can give a good prediction of the flow and heat transfer inside the boiler.
ft/s
Figure 4. Flow streamline colored by velocity By looking at the velocity distribution at the crosssectional area in and under the steam tubes as shown in Figure 6, the velocity contours indicates a high velocity deviation across the tubes. The contour shows a high velocity, above 100 ft/s, at the back wall side, and a low velocity of 25ft/s at the leading edge side.
Flow Characteristics The flow characteristics are represented by the flow streamlines post-processed in the software ParaView, which is shown in Figure 4. The flow streamlines indicate a strong turbulent reacting flow with recirculation and velocity of the flue gas went through the steam tubes presents a non-uniformities characteristics in the CO boiler. According to the streamlines in the CO inlet area, after the flue gas goes into the CO inlet, due to the configuration of the geometry, the majority of the flue gas is directed down and mixed with the air to form combustion in the combustion chamber. The combustion air supplied for the auxiliary fuel combustion is also showing turbulent recirculation characteristics before mixing with the fuels due to the configurations of the geometry. After the combustion air and the auxiliary fuel reaching the combustion chamber, the fuel and air circulate and combust before mixing with the main CO combustion flue gas stream. Then, the main flue gas stream formed by the CO combustion and the auxiliary fuel combustion will move forward through the combustion chamber area to the convection zone. Due to the velocity deviation shown by color of the streamline, three major flue gas circulations are formed in both the convection zone and the combustion chamber. As seen in Figure 4, the high velocity flue gas stream shifts to the back wall side, and causes a large recirculation of flue gas right below the water tubes. This recirculation may limit the flow rate of high temperature flue gas going through the water tubes. Another circulation happens at the turning elbow right below the chamber top wall due to the turning configuration and the major circulation in the
Therefore, the flow streamline of the typical operation condition shows a high turbulence and non-uniformity characteristics, especially the flow at the convection zone. The non-uniformity flow at the convection zone would cause the non-uniformity of the heat transfer between the tubes and the combustion flue gas, which also could potentially cause the steam tube overheating and low heat transfer efficiency problems.
ft/s
ft/s
Figure 5. Velocity contour and vectors at the center plane
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Left
Center
2
Right (Btu/hr-ft ) Bottom View Figure 8. Heat flux and heat transfer coefficient profiles
on the water tubes
ft/s
The heat flux contour also indicates a heat transfer deviation in Figure 8. The heat flux decreases gradually from the back wall side to the leading edge side. And therefore, the heat transfer coefficient profiles also show high deviation along the tubes, which can be seen in the profiles in Figure 8. Under the typical operation condition, the heat transfer coefficient deviation is around 20 Btu/hr-ft2.
Figure 6. Velocity contours at different levels cross the water tubes Combustion and heat transfer In order to investigate the performance of the carbon monoxide boiler, heat transfer between the combustion flue gas and the steam tubes has been modeled in this CFD model. Under the typical operation condition, the steam tube temperature is shown in Figure 7 and the total heat flux and heat transfer coefficient are shown in Figure 8.
Flow Optimization The flow uneven distribution properties in the baseline case under typical operation condition have been investigated. And the potential risks under such flow properties are apparently high. Therefore, numerical optimization on such operation condition is needed. Checker walls are normally installed to direct the flow. According to the industrial construction capability, a design idea which opens only half of the combustion chamber cross-sectional area at the elbow turning point has been investigated by the developed CFD model.
According to Figure 7, the heat transfer between the combustion flue gas and the water tubes is directly related to the velocity and temperature profiles. Due to the temperature and velocity deviation in the convection zone, the water tube temperature shows deviations. the steam tubes exhibit high temperature at the back wall side and low temperature at the leading edge side, which is directly related to the flow distribution as shown in Figure 6. The temperature difference is around 50F, which indicates that the high velocity deviations would affect the steam tube temperature distribution and the risks of suffering hot spots is high.
Figure 9 shows a design of checker wall with twenty by twenty inches square openings. Based on the developed CFD model, the effects of this half open checker walls on the flow distributions was tested. The flow streamlines are shown in Figure 10.
F Figure 9. Checker wall design Figure 10 demonstrates the flow streamlines of base case and the checker wall design case. As stated before, the flow distribution of base case has high velocity deviations with most of the combustion flue gas flows near the back wall, and it also
Figure 7. Water tube temperature contour
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transfer coefficient would create hot spot on the tubes and also potentially reduce the overall heat transfer. In the checker wall design case, the heat flux and the heat transfer coefficient on the steam tubes are more uniform than the base case. And the deviation of the heat transfer coefficient decreased to less than 25 Btu/hr-ft2.
experiences significant recirculation in the convection zone near the water tubes. The flow streamline characteristics of the checker wall design case were considerably different from the base case. According to Figure 10, the high velocity flue gas flow stream was blocked and dispersed by the checker wall and then flows evenly toward the convection water tubes. The flow in the convection zone does not create a strong recirculation as the base case flow. Therefore, the square opening checker wall design could help to form a more uniform flow distribution at the convection zone. In order to understand the velocity distribution, the velocity contours of base case and the checker wall design cases are shown in Figure 11.
ft/s Base Case Checker wall design Figure 10. Flow streamline comparison between base case and case with checker wall ft/s
Base Case
Optimization design
Figure 12. Comparison of heat flux and heat transfer coefficient profiles on the water tubes between base case and case with checker wall CONCLUSION A detailed three-dimensional computational fluid dynamics model for a Carbon Monoxide boiler was developed. The model was validated by temperature measurements under certain operation conditions. The simulation results indicate a high flow deviation which could possibly cause the temperature and heat transfer deviations. A checker wall was used to optimize the flow in the convection zone, and the developed CFD model was used to investigate the effects. The simulation results show that the high velocity turbulent reacting flow passes through the convection tubes with high velocity deviations under typical operation conditions. And the velocity deviations directly cause the deviation of the heat transfer coefficient. The heat transfer coefficient deviations is around 50 Btu/hr-ft2 along the water tubes, which would create hot spots on the tubes and also potentially reduce the overall heat transfer. The effect of adding a square opening checker wall design on the flow pattern inside the CO boiler was evaluated. The results indicate that the heat flux deviations along the water tubes were reduced by adding checker walls and the deviation of the heat transfer coefficient can be decreased to less than 25 Btu/hr-ft2.
ft/s
Base Case
Optimization design
Figure 11. Velocity contour comparison between base case and case with checker wall Figure 11 shows the velocity contours of base case and checker wall design cases at the center plane of the CO boiler. The base case velocity contour shows a high velocity deviation near the convection tubes. In the square opening checker wall design, the high speed combustion flue gas stream is spread by the checker wall, and the flow is more evenly distributed before reaching the convection tubes compared with base case. The velocity profile before the convection tubes has a significant effect on heat transfer, as seen in Figure 12. As observed in Figure 12, the heat transfer between the steam tubes and the combustion flue gas vary significantly when using the checker wall design. In the base case, the uneven flow distribution directly causes the heat transfer deviations. The high speed combustion stream close to the back side wall leads to a high heat transfer coefficient between the flue gas and the steam tubes. Because of this, the heat transfer flux and coefficient is extremely high at the back wall compared to the leading edge. The deviation of the heat transfer coefficient is around 50 Btu/hr-ft2. Deviation in the heat
ACKNOWLEDGEMENT The authors would also like to thank the Center for Innovation through Visualization and Simulation (CIVS) at Purdue University Calumet for providing all the resources required for this work.
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NOMENCLATURE 𝑎 Absorption coefficient, m-1 𝐴 Empirical constant, 4.0 𝐵 Empirical constant, 0.5 C1ε Constant, 1.44 C2 Constant, 1.9 𝐶 Linear-anisotropic phase function coefficient 𝐷𝑖,𝑚 Diffusion coefficient for specie i in the mixture 𝐷𝑇,𝑖 Thermal diffusion coefficient F External body force, N 𝑔̅ Gravity, m/s2 𝑔𝑖 Component of the gravitational vector in the 𝑖 th direction, m/s2 𝐺𝑏 Generation of turbulence kinetic energy due to buoyancy, m2/s2 𝐺𝑘 Generation of turbulence kinetic energy due to the mean velocity gradients, m2/s2 ℎ𝑗 Sensible enthalpy of species j 𝐼 Unit tensor ⃑𝐽𝑖 Diffusion flux of species i Diffusion flux of species j 𝐽⃗𝑗 k eff Effective conductivity, w/m-K 𝑘 Turbulence energy, m2/s2 Mw,i Molecular weight of species i 𝑁 Number of Species in the system 𝑛 Refractive index 𝑝 Static pressure, pascal 𝑅𝑖 Net rate of production of species i by chemical reactions 𝑆 Modulus of the mean rate-of-strain tensor 𝑆𝐾 User defined source term 𝑆𝜀 User defined source term 𝑆ℎ Heat of chemical reaction, and any other volumetric heat sources, J 𝑆𝑚 Mass added to the continuous phase from the dispersed second phase (e.g., due to vaporization of liquid droplets) and any user-defined sources 𝑇 Local temperature, K 𝑢𝑗 Velocity component along the direction xj , m/s Instant turbulence velocity on the direction xi , m/s 𝑢𝑖′ ′ Stoichiometric coefficient for reactant R in reaction r vR,r ′′ v𝑗,r Stoichiometric coefficient for product j in reaction r 𝑣⃗ Velocity, m/s 𝑌𝑖 Local mass fraction of each species YR Mass fraction of a particular reactant, R YP Mass fraction of any product species, P 𝑌𝑀 Contribution of the fluctuating dilatation in compressible turbulence to the overall dissipation rate 𝜌 Density, kg/m3 τ Stress tensor 𝜇 Molecular viscosity, kgm/s 𝜖 Turbulent dissipation rate m2/s3 σk Turbulent Prandtl number for 𝑘, 1.0 σε Turbulent Prandtl number for 𝜖, 1.2 𝜇𝑡 Turbulence viscosity, kgm/s β Thermal expansion coefficient K-1
𝑐𝜇 𝑃𝑟𝑡 𝜎𝑠 𝜎 𝑆𝑐𝑡
Constant Turbulent Prandtl number for energy Scattering coefficient, m-1 Stefan-Boltzmann constant (5.669 x 10-8 𝑊/ 𝑚2 𝐾 4 ) Turbulent Schmidt number, 0.7
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