The numerical simulation research on Thermal Flow-Reversal Reactor
(TFRR) of mine ventilation gas
Sanfeng Zhang1, a, Hulan Liu2, b and Dada Xi1, c
1
School of xxx, xxx University, Guangzhou 510000, China;
2
School of yyy, zzz University, Guangzhou 510000, China.
a
MAME2013@163.com, bConf_51EiSCi@163.com, cyyyy@ccc.com
Keywords: Mine ventilation gas, orthogonal test, operating parameter, reactor performance
Abstract. The paper uses computational fluid dynamics software FLUENT to build a single channel
numerical simulation model of the mine ventilation gas Thermal Flow-Reversal Reactor (TFRR).
Combining with the analysis of orthogonal test, the influences that four factors (Initial temperature
distribution, Ventilation gas flow rate, Volume fraction of methane, Exchange period) act on reactor
performance is investigated. An optimal operation condition is proposed by the establishment of the
priority sequence of these four factors.
Introduction
In the coal mine methane emissions of China, the percentage of ventilation methane is about 85%.
Every year, the amount of CH4 from ventilation gas is about 10-15 billion cubic meters which amount
to 12 billion cubic meters natural gas in west-east natural gas transmission project, means to burn
11.4-17 million tons standard coal[1-2]. The thermal flow-reversal react technology of ventilation gas
realizes the effective utilization of ventilation air methane. It has favorable environment benefit and
economic benefit, and has a very wide application prospects [3-4].
The Thermal Flow-Reversal Reactor (TFRR) of ventilation gas is a kind of relatively complex and
precise thermodynamic system. Its performances are affected by the combined action of many
parameters, for example the operating parameters such as ventilation air flow rate, methane volume
fraction, exchange period, initial temperature distribution, and structure parameters such as heat
accumulator height, honeycomb ceramics shape and specific heat capacity. Therefore, the research on
how operating parameters and structure parameters affect performance is significance.
This paper used FLUENT software to build the single-channel model of the reactor, and then
figure out the law that how the reactor was affected by the operating parameters such as the ventilation
air flow rate, concentration of methane and initial temperature distribution. By introducing the
orthogonal test design, paper proposed an effective research method on the determination of the
optimal operating condition.
Single-channel modeling
Physical model. The modeling object of this paper is a self-designed small size Thermal
Flow-Reversal Reactor (TFRR) of ventilation air methane. This reactor was designed of a 1000m3/h
ventilation processing capability. It has a two-bed vertical construction and was ordered filled by
several honeycomb ceramics. The size of unilateral heat accumulator is 610×610×1400mm. The
channel shape of heat accumulator is square and its cross section is shown in Fig.1. The size of
channel is 3×3mm and the thickness is 0.35mm. In the calculation, we only choose the
three-dimensional space which composed by half wall thickness, channel section and height direction
as the calculating area to build mathematical modeling. The geometric model of calculating area is
shown in Fig.2.
wall thickness
pore size
Fig.1 heat accumulator and single channel
or
cR
Half Wall Thickness
t of
igh
Gy
He
Gz
Gx
i
ram
Ce
at
ner
ege
Pore Size
Fig.2 Three dimension calculating area
Mathematical model. The numerical calculation was processed under the FLUENT software. In
order to simplify the calculation, we proposed several hypotheses below in mathematical modeling
[5-7]:
A. Regarding ventilation air methane as ideal gas and follow the ideal gas state equation.
B. Ignoring the radiation heat transfer and energy loss produced by environment dissipation and
then regarding the material as the heat insulation surface.
C. Simplifying the chemical reaction to single step reaction as a whole.
Based on the physical model and hypotheses above, the flow and heat transfer control equation set
of honeycomb heat accumulator can be expressed as:
 

(  i )  0
Pre-mix gas continuity equation
t x j
Pre-mix gas momentum equation
 j  i


p

(  i ) 
(  j )  

[ (

)]   gi
t
x j
x j x j
xi x j
Pre-mix gas energy equation (low Mach number, specific heats of each component are similar):



T
(  c pT ) 
(  j c pT ) 
(
)  wsQs
t
x j
x j x j
Pre-mix gas component equation:
Y



( Ys ) 
(  jYs ) 
( D s )  ws
t
x j
x j
x j
Heat accumulator energy equation
T


( s c psTs ) 
(s s )
t
x j
x j
In the equations above, ws is the response rate of s component, that is, the generated or consumed
quality of s component in reactor volume, Ys   s /  is the mass fraction of s component, Qs is
the component formation heat in reactor mass.
Chemical reaction models. From the test data analysis of flow rate, we found that the flow of
ventilation gas in honeycomb ceramics is laminar fluid. Moreover, since the test use mixture gas of
methane and air to simulate ventilation gas, the Thermal Flow-Reversal Reactor (TFRR) of
ventilation gas is kind of pre-mix gas burning. Therefore, paper used general laminar finite-rate model
to describe chemical reaction model. The chemical reaction rate was determined by the Arrhenius
formula.
Determination of physical property parameter. Physical property parameter of honeycomb
ceramics. The physical property parameter was determined by the chosen honeycomb ceramics
materials used in test.
A. Density:   2500kg / m3 ;
B. The Solid matrix’s specific heat capacity changing with temperature meets the equation:
c p  0.23T  907.61
C. The Solid matrix’s coefficient of heat conduction changing with temperature meets the
equation:   0.000666T  1.305 .
The Solid matrix’s coefficient of heat conduction changing with temperature meets the equation.
Physical property parameter of mixture gas. The temperature is an important factor affecting
physical property of gas, that is, the physical property parameter of mixture gas would change
significantly with temperature. Hence, this paper used variation physical property parameter value
with temperature to meet the simulation demand.
Setting of rest conditions.
A. Inflow boundary condition. The inflow boundary condition was described by rate inflow
boundary condition. The flow direction of ventilation gas was vertical to inlet section and gas
temperature was set to 300K. Since the methane content in ventilation gas is measured by volume
fraction, the mass fraction calculation of each component in mixture gas is below:
 ch4  M ch4
wch4 
(1  ch4 )   N2  M N2  (1  ch4 )  O2  M O2  ch4  M ch4
Above,  ch4 is the volume fraction of methane in mixture gas, M ch4 , M N 2 , M O2 are the molar
masses of methane, nitrogen and oxygen,  N 2 ,  O2 are the volume faction of nitrogen and oxygen in
air. Based on the formula above, it was able to calculate the mass fraction of O2 , CO2 and other gases
in similar way.
B. Outflow boundary condition. The outflow boundary condition was described by the pressure
outflow boundary condition. The static pressure was set 0. Pressure outlet boundary is also needs to
define reflux condition. The mass fraction of methane and oxygen is 0 and 0.24376.
C. Wall boundary condition. The end region and wall of heat accumulator are set to heat
insulation wall and its temperature is 300K.
D. Initial condition. The initial condition would be fitted into piecewise linear function based on
the interior temperature distribution data of oxidation bed when reactor is on steady operation. By
importing UDF program in FLUENT, initializes the temperature field of oxidation bed.
E. Calculation end condition. This paper uses the gas temperature variation condition at
oxidation bed outlet to judge whether the reactor is in steady operation. Normally, the calculation
could be ended once the outlet temperature at the end of one cycle is less 1℃ differ from previous
cycle’s.
The orthogonal test design on main influence factors of reactor performance
Since the numerical simulation work of this paper is based on the laboratory test, that is, the test
system was already built up and the shape, type and size of honeycomb ceramics heat accumulator
were already determined. Therefore, we do not study the structure parameter of reactor, and only
consider some main influence factors such as ventilation gas flow rate, volume fraction of methane,
initial temperature distribution and so on.
Establishment of orthogonal test table. There are four factors: ventilation gas flow rate, volume
fraction of methane, exchange (half) period and initial temperature distribution. Each factor has three
levels, form the table.1 below.
Table.1 factors and levels of orthogonal test
factor
level
1
2
3
Gas flow
rate(m/s)
1.0
1.5
2.0
Volume fraction of
methane(%)
0.2
0.5
1.0
Exchange half
period(s)
30
60
90
Maximum value of initial temperature
distribution Tmax(K)
973
1073
1173
Assuming that there are no interaction among each factors, we chosen L9 (34)orthogonal table to
conduct the test.
Analysis of orthogonal test results. Following the test schedule, each test was numerically
simulated respectively. The test results are shown in table.2.
Table 2 result of orthogonal test
column
factor
test1
test2
test3
test4
test5
test6
test7
test8
test9
Mean value1
Mean value 2
Mean value 3
Range
A
Gas flow
rate
(m/s)
1
1
1
2
2
2
3
3
3
53.433
43.100
37.350
16.083
B
Volume
fraction of
methane (%)
1
2
3
1
2
3
1
2
3
40.667
51.783
41.433
11.116
C
Exchange
half period
(s)
1
2
3
2
3
1
3
1
2
41.917
51.533
40.433
11.100
D
Maximum value of
initial temperature
distribution Tmax (K)
1
2
3
3
1
2
2
3
1
9.367
25.933
98.583
89.216
Test result
Temperature
oxygenation
ratio (%)
at outlet (℃)
11.50
953
48.80
1063
100
1175
100
1120
10.80
910
18.50
1052
10.50
978
95.75
909
5.80
1155
Based on the test results in table. 2, the effect curve of ventilation gas oxygenation ratio to factors
and levels was drawn and shown in Fig.3
Figure.3 The effect curve of ventilation gas oxygenation ratio to factors and levels
Fig.3 shows that the average oxygenation ratio on outlet surface decreases due to the increasing of
ventilation gas flow rate, it means that the smaller flow rate is better. When the maximum value of
initial temperature distribution Tmax increases, oxygenation ratio increases accordingly. It means that
the larger Tmax is better. With the increasing of methane volume fraction and exchange (half) period,
the oxygenation ratio was increasing and then decreasing. It reaches maximum value at the methane
volume fraction of 0.5% and exchange (half) period of 60s. So these two factor levels are better to be
set to peak value[8].
In order to analyze the influence rule these factors act on oxidation reactor, table.3 shows the
variance analysis of oxygenation ratio. In the table, F ratio uses methane volume fraction as deviation
column (the choice of deviation column has no influence on result).
Table3 Variance analysis of oxygenation ratio ratio
factor
Gas flow rate
Volume fraction of methane
Exchange half period
Maximum value of initial
temperature distribution
deviation
DevSq
398.514
231.291
217.891
DOF
2
2
2
F ratio
1.723
1.000
0.942
F0.05 critical value
19.000
19.000
19.000
significance
13512.091
2
58.420
19.000
※
231.29
2
By analyzing table.3 we found that the F ratio value is 58.420 on maximum value of initial
temperature distribution Tmax and greater than F0.05 critical value 19. It means that it has a reliability
of 95% and the influence this factor act on reactor is significant. Uses the F value to determine the
factors of primary and secondary and the order is: (primary) initial temperature distribution →
ventilation gas flow rate → volume fraction of methane → exchange (half) period (secondary).
According to the factors order and the effect curve of ventilation gas oxygenation ratio to factors
and levels, this test obtained the reactor’s optimal operation scheme which is D3A1B2C2, that is,
when the maximum value of initial temperature distribution is 1173k, ventilation gas flow rate is
1m/s, methane volume fraction is 0.5% and exchange half period is 60s, the oxygenation ratio of
ventilation gas would be highest.
Conclusion
This paper built the single channel numerical simulation model of the ventilation gas Thermal
Flow-Reversal Reactor (TFRR). Combining with the analysis of orthogonal test, the influence that
four factors (Initial temperature distribution, Ventilation gas flow rate, Volume fraction of methane,
Exchange period) act on reactor performance was investigated. The primary and secondary order of
these four factors and the optimal operation conditions are determined, which has significance on
reactor performance optimization.
References
[1] W.J. Long: Mining Safety & Environmental Protection, vol. 37 (2010) no. 4, p. 74-77.
[2] B. Lan, H.J. Xu: Zhongzhou Coal, (2012) no. 7, p. 37-41.
[3] J.D. Kang, P.F. Gao, W.J. Long, et al: Mining Safety & Environmental Protection, vol. 39 (2012)
no. 2, p. 80-83.
[4] N.E. Machin, E.E. Caklrca, A.Ates. Catalytic Combustion of Methane.6th International
Advanced Technologies Symposium, 16-18 May 2011, Elazig, Turkey.
[5] H.Q. Zhou, B. Lan, B. Chen: Safety in Coal Mines, (2010) no. 11, p. 11-15.
[6] P.F. Wang: Study on Theory and Experiment of Thermal Flow-Reversal Oxidation of Coal Mine
Ventilation Air Methane (Ph.D., Central South University, China 2012).
[7] K. Gosiewski, A. Pawlaczyk, M. Jaschik: Chem. Eng. J., vol. 207-208 (2012) no. 1, p. 76-84.
[8] A.Z. Shui, H. Gong, L.K. Zeng, et al: Industrial Furnace, vol. 31 (2009) no. 2, p. 9-14.