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Scale-up of a Cold Flow Model of FICFB Biomass Gasification Process to an Industrial Pilot Plant – Example of Dynamic Similarity

Written By

Jernej Mele

Submitted: 12 October 2010 Published: 27 July 2011

DOI: 10.5772/16439

From the Edited Volume

Progress in Biomass and Bioenergy Production

Edited by Syed Shahid Shaukat

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1. Introduction

In this chapter we are introducing the research of particles hydrodynamics in a cold flow model of Fast Internal Circulating Fluidized Bed (FICFB) biomass gasification process and its scale-up to industrial pilot plant. A laboratory unit has been made for the purposes of experimental research. The laboratory unit is three times smaller than the later pilot plant. For a reliable observation of the flow process, similar flow conditions must be created in the laboratory unit and the pilot plant. The results of the laboratory model will be similar to those of the actual device if geometry, flow and Reynolds numbers are the same. Therefore, there is no need to bring a full-scale gasificator into the laboratory and actually test it. This is an example of "dynamic similarity".

FICFB biomass gasification is a process for producing high caloric synthesis gas (syngas) from solid Hydrocarbons. The basic idea is to separate syngas from flue gas, and due to the separation we have a gasification zone for endothermic reactions and a riser for exothermic reactions. The bed material circulates between these two zones and serves as a heat carrier and a catalyst.

While researching the 250kW fluidized bed gasification pilot plant certain questions concerning particle dynamics in gas flows control arose. There is a zone where fluidized bed conditions are made with superheated steam, pneumatic transport with hot air and a pair of secondary gas inlets of CO2. These particle flows are difficult to describe with mathematical models. This is the main reason why the three-times smaller cold-flow laboratory unit has been made. The hydrodynamics of particles will be studied in the air flow at arbitrary conditions. Flow conditions in the laboratory unit and pilot plant must be similar for a reliable evaluation of the process in the pilot plant.


2. Laboratory unit

The laboratory unit is a device three times smaller than the pilot plant. Its main purpose is to simulate the hydrodynamic process of FICFB gasification in a cold flow. It is made from stainless steel and in the case of the parts that are of greatest interest to the present study is made of glass, so that the particle behaviour may be observed. Fig. 1 shows a model of laboratory unit. Its main elements are:

  • Reactor (A),

  • Riser (B),

  • Cyclone (C),

  • Siphon (D),

  • Chute (E),

  • Gas distributor (J1 and J2),

  • Auxiliary inlets (I1 and I2).

Figure 1.

model of laboratory unit

Firstly, let us look at the process. There are two gas distributors at the bottom of the reactor and riser, through which air is blown vertically. The pneumatic transport of the particles takes place in the riser, where they are separated from the air flow in cyclone and finally gathered in siphon. The second auxiliary inlet acts to fluidize the gathered particles and transport them to the reactor. Here, the fluidized bed is created with the upward blowing air. From here, the particles are transported to the riser through the chute and the speed of transportation is regulated by means of the first auxiliary inlet.

Laboratory unit Pilot plant
Dgas,1 [mm] 100 300
Dgas,2 [mm] 190 600
Dcomb [mm] 50 150
Hcomb [mm] 1500 4500

Table 1.

Main dimensions of laboratory unit and pilot plant

We are primarily interested in how to establish a stationary and self-sustainable process. In the laboratory unit there are glass parts through which the process in course can be directly observed. However, in the hot flow model we will not be able to see what happens inside the pilot plant, and therefore our control system must be able to initiate the process, keep it in a stationary state and halt it on the basis of measured data such as relative pressure and flow velocities. For this mater, our laboratory unit consists of 7 pressure and 2 flow velocity measuring points. Fig. 2 details the positions of the pressure places.

Figure 2.

Openings for the measuring of relative pressure

Trough experiments on the laboratory unit the effectiveness of elements will be studied so as to enable the correction and improvement of any construction flaws they contain. Fig. 3 shows the laboratory unit that will be used for studying the flow process. There are 7 places for pressure, 2 for temperature and 2 for gas flow measurements. For the proper operation of our solid flow system it is vital that the particles are maintained in dynamic suspension as settling down the particles can clog both the measuring openings and injection nozzles. Thus it is essential to design such systems with special care. All measurements involving the risk of clogging the measuring opening must be taken outside the solid flow zone if possible – gas flow velocity measurements with the Pitot tube must be taken in the gas pipeline before gas enters thru distributor. It is highly desirable for all measuring openings to be small and positioned rectangular to the direction of flow (Nicastro & Glicksman, 1982).

Figure 3.

Laboratory unit

2.1. Distributor

For the distributor 3 metal nets with openings of 225 μm have been used, with ceramic wool of 8mm placed in between as shown in fig. 4. We tried to achieve a sufficient pressure drop as to attain equal flow through the openings. According to Agarwal recommendation (Kunii & Levenspiel, 1991; Nicastro & Glicksman, 1982), the pressure drop across distributors must be 10 % of the pressure drop across the bed, with a minimum of 35 mm H2O. With this we are in approximate agreement. At higher pressure drops across the distributor we get more particulate or smooth fluidization with less channelling, slugging and fluctuation in density. The pressure drop across the distributor is shown in fig. 5.

Figure 4.

Distributor structure

Figure 5.

Pressure drop across the distributor with blowing of air

2.2. Cyclone

In our case, the cyclone separator is placed behind the riser to separate the particles from the air flow. It has to be able to separate particles larger than 50 μm. For these conditions these particles are considered large as cyclones are often used for the removal of particles of about 10 μm diameter or larger from air streams. Our model is shown in fig. 6.

Figure 6.

The characteristic dimensions of cyclone

We dimensioned our cyclone according to Perry (Perry, 1988). Dp,50 is the particle size at which 50 % of solids of a given size are collected by the cyclone.

D p , 50 = 9 η g B c y c π N s v g ( ρ p ρ g ) E1

By rearranging the equation (1), we obtain the following expression:

B c y c = D p , 50 2 π N s v g ( ρ p ρ g ) 9 η g E2

The width of the cyclone entering the opening and the characteristic diameter are correlated by the following expression:

B c y c = D c y c 4 E3

The diameter of our cyclone is 150 mm. Smaller particles, which are not separated in cyclone are being collected in a filter placed on the cyclone gas exit.


3. Basic equations for describing the fluidized state and similarity of flows

3.1. Reynolds number

The goal herein is to compare flows in the laboratory unit to those in the pilot plant. In order for the two flows to be similar they must have the same geometry and equal Reynolds numbers. When comparing fluid behaviour at homologous points in a model and a full-scale flow, the following holds:

Re(laboratory unit) = Re(Scale-up pilot plant)

The Reynolds number of particles can be determined by the following equation (Kunii & Levenspiel, 1991):

Re p = D p v g ρ g η g E4

For achieving the required similarity, the following conditions must be also fulfilled:

p ρ g v g 2 = p g , a r ρ g , a r v g , a r 2 E5

3.2. Minimal fluidizing velocity

The fluidization state starts when the drag force of by upward moving gas equals the weight of the particles (Oman, 2005)

F g _ p = 1 2 C x A p ρ p v g 2 E6
Δ p A t = ( A t L m f ) ( 1 ε m f ) [ ( ρ s ρ g ) g g c ] E7

By rearranging equation (7), for minimum fluidizing conditions we find the following expression (Kunii & Levenspiel, 1991),

Δ p m f L m f = ( 1 ε m f ) ( ρ s ρ g ) g g c E8

Voidage in fluidized bed εmf is larger than in the packed bed and it can be estimated experimentally from a random ladling sample. For small particles and low Reynolds numbers the viscous energy losses predominate and the equation simplifies to (Kunii & Levenspiel, 1991):

v m f = ( Φ s D p ) 2 150 ρ p ρ g η g g ε m f 2 ( 1 ε m f ) E9

for Rep< 20

For large particles only the kinetic energy losses need to be considered:

v m f = Φ s D p 1 , 75 ( ρ p ρ g ) η g g ε m f 3 E10

for Rep> 1000.

If ΦS and εmf are unknown, the following modifications suggested by Wen and Yu (Kunii & Levenspiel, 1991) are used:

1 ε m f Φ S 2 ε m f 2 11 E11
1 Φ S ε m f 3 14 E12

Equations (9) and (10) can now be simplified to:

v m f = D p 2 ( ρ p ρ g ) g 1650 η g E13

for Rep< 20

v m f = D p g ( ρ p ρ g ) 24 , 5 ρ g E14

for Rep> 1000.

3.3. Terminal velocity

The upper limit of gas flow rate is approximated by the terminal (free fall) velocity of the particles, which can be estimated from the fluid mechanics (Kunii & Levenspiel, 1991):

v t = 4 g D p ( ρ p ρ g ) 3 ρ g C x E15

There are spherical and non-spherical particle shapes in the bed and each of them has a different Cx value. If we combine equations (4) and (15) we get the velocity independent group:

C x Re p 2 = 4 g D p 3 ρ g ( ρ p ρ g ) 3 η g 2 E16

An alternative way of finding vt for spherical particles uses analytical expressions for the drag coefficient Cx (Kunii & Levenspiel, 1991).

C x = 24 Re p     f o r     R e p   0 , 4 E17
C x = 10 Re p     f o r       0 , 4   R e p 500 E18
C x = 0 , 43     f o r       500 R e p 200000 E19

But still no simple expression can represent the experimental findings for the entire range of Reynolds numbers, so by replacing these values Cx in equation (16) we obtain:

v t = ( ρ p ρ g ) g D p 2 18 η g E20

for Rep< 0,4

v t = 4 225 ( ρ p ρ g ) 2 g 2 η g ρ g 3 D p E21

for 0,4 < Rep< 500

v t = 3 , 1 D p g ( ρ p ρ g ) ρ g E22

for 500 < Rep< 200000.

3.4. Determining density

In the pilot plant we will have multiple gas mixtures at different temperatures due to chemical reactions. For our calculations the density for these mixtures will be determined by the following equation (Oman et al., 2006 ):

ρ g = ( i w i ρ i ) 1 E23

To calculate the density of the gas mixture at an arbitrary temperature and an arbitrary pressure the density under normal condition must be calculated according to equation (24), with the obtained value being converted to density at the required parameters:

ρ g , a r = ρ g p g , a r p n T n T g , a r E24

3.5. Pressure drops

With increased gas velocity of the small solid particles across the bed a characteristic state occurs. Pressure drop starts to increase, reaching its maximum value Δpmf at minimum fluidization velocity vmf. At this point only part of the bed is fluidized. When the bed is fully fluidized (at vmff), the pressure drop is reduced to Δpmff and is almost constant until gas reaches terminal velocity. If the velocity is still increasing, the particles start transporting pneumatically and pressure drop reduces rapidly to 0. By rearranging equation (8), we obtain the following expression (Kunii & Levenspiel, 1991):

Δ p m f = ( 1 ε m f ) ( ρ s ρ g ) g L m f E25

The expression can also be extended to the fully fluidized state (Kaewklum & Kuprianov, 2008):

Δ p m f f = ( 1 ε m f f ) ( ρ s ρ g ) g L m f f E26

Figure 7.

The change in pressure drop relative to gas velocity for Not-too-Small Uniformly Sized Particles (Kunii & Levenspiel, 1991)

A somewhat different differential pressure characteristic occurs with a wide size distribution of particles, which are usually present in industrial processes. When the gas velocity increases through the bed of solids, the smaller particles start to fluidize and slip into the void spaces between the larger particles, while the larger particles remain stationary (Kunii & Levenspiel, 1991) (see Fig. 8). However, after a full fluidization of bed material (vg>vmff), with increasing air velocity, pressure drop mainly remains constant.

Figure 8.

The change in pressure drop relative to gas velocity for Wide Size Distribution of Particles (Kunii & Levenspiel, 1991)

3.6. Mass flows and conservation of mass

For a regular flow process we have to ensure proper gas flows at the inlets. Through defining minimal fluidizing and terminal velocities, we can estimate the mass flow of the air reactor and riser by applying the following relations:

φ m _ g = ρ g v g π D t u b e 2 4 E27
φ V _ g = φ m _ g ρ g E28

It is extremely important to ensure that there are no mass losses between the ventilator and the reactor. It can be assumed:

v g D g a s , 2 2 π 4 = v g , r e f D t u b e 2 π 4 E29

4. Calculation analyses

On the basis of the previously-mentioned equations, we can make an estimation of flow conditions in the reactor and riser. We have made a tabular comparison of physical properties between the laboratory unit and pilot plant in tables 2 and 3. The comparison is based on the established equality of Reynolds numbers. As mentioned in chapter 3.1. “In order for two flows to be similar they must have the same geometry and equal Reynolds numbers”. In the laboratory unit, flows will be made with upward-blowing air at room temperature whereas in the pilot plant the fluid bed will be made with inlet of superheated steam and pneumatic transport with hot air blowing at 550º C.

Laboratory unit Pilot plant
Gas Air Steam / Syngas
T [°C] 30 550 / 800
Dp [μm] 200 600
ρp [kg/m3] 8250 3025
ρg [kg/m3] 1,204 0,288 / 0,192
ηg [Pas] 1,8·10-5 3,1·10-5 / 4,6∙10-5
vRe<20 [m/s] 0,11 0,21 / 0,14
vRe"/1000 [m/s] 0,75 1,58 / 1,95
Φm [kg/h] 6,4 158,9
ΦV [m3/h] 5,4 548,5
Rep 9,8 9,0 /4,9

Table 2.

Physical properties of gas in Reactor

In the meantime endothermic chemical reactions of pyrolisys, a water-gas-shift reaction will take place in the reactor while exothermic combustion occurs in the riser. Flue gases will have a the temperature of around 1000º C on exiting the combustor and syngas a temperature of approximately 800º C at the reactor’s point of exit. Gases in the pilot plant will have lower densities and higher viscosities than the air in the laboratory unit. The bed material will be Olivine with Dp = 600 μm. In order to establish similar conditions, we have to use smaller and denser particles. We have chosen brass particles with Dp = 200 μm. Simulation will also be tested with quartz sand and olivine.

Laboratory unit Pilot plant
Gas Air Air / Flue gas
Tg [°C] 30 550 / 1000
Dp [μm] 200 600
ρp [kg/m3] 8250 3025
ρg [kg/m3] 1,204 0,61/0,294
ηg [Pas] 1,8·10-5 3,8·10-5/4,7·10-5
vRe<0.4 [m/s] 10,1 15,7/12,6
v0.4<Re<500 [m/s] 3,6 5,3/6,2
v500<Re<200000 [m/s] 6,6 9,6/13,7
Φm [kg/h] 47,7 154,2
ΦV [m3/h] 39,6 524,5
Rep 46,6 50,8 / 23,3

Table 3.

Physical properties of gas in Riser

On the basis of studied flow velocities, mass flows, as well as pressure drops through air distributors and fluid beds at different points of the laboratory unit, we may anticipate the similar results in the pilot plant.


5. Experimental work

Firstly, we have to establish the fluidized bed in the reactor. The particles will fill the chute and the lower part of the riser. The chute is installed at the bottom of the reactor and riser and has an inclination angle. The fluidizing of the particles in the chute will then be started, along with the simultaneous initialization of the pneumatic transport of the particles. When sufficient material has been gathered in the siphon, the particles must be transported back to the reactor with the help of the first auxiliary inlet. The particles are now at their starting point. We must achieve a pressure at the bottom of the fluidized bed p2 which is larger than that at the point where the chute connects to the riser p6. The gas flow direction will be from the reactor to the riser, pushing the particles in the desired direction. At the top of the fluidized bed we have pressure p4 which has to be lower than p7, so the particles can now travel back to the reactor. But there has to be enough material in the siphon at all times in order to prevent the mixing of gases between the zones. Therefore, the siphon has to serve as seal gap for gases but not for material. The more gas goes through the siphon the lower the caloric value of the gas will be. Experiments will show how pressures are distributed across the system. Fig. 9 shows which measured pressures are of greatest interest for our purposes.

Figure 9.

Measuring scheme

By way of example, we will look at the experiment with quartz sand. The size of the particles used for simulation is shown in fig. 13. The particles have an average diameter of about 200 μm. A series of measurements were made and pressure drops at different bed heights taken. Fig. 10 represents a comparison of pressure drop across the bed in the reactor with the gas velocity for different bed heights.

Figure 10.

Pressure drops over fluidized bed

In lower beds less aggregative bubbling occurs and results closer to calculated values are obtained. Nevertheless, still there is a lot of deviation between them. In addition, there is some leakage of gas from the reactor through chute to the riser and as the Pitot tubes are placed in front of gas entering each zone those velocities do not represent the real situation, although the mass flow of air blown through unit is quite as predicted. However, gas velocity is almost impossible to measure within the laboratory unit because attempts to do so would inevitably lead to bed material clogging the measure openings in the device. Having said that, our assessment and purpose is to define and achieve a stationary process on the basis of the measuring system. The measured quantities are presented in table 4.

Symbol Value [unit]
p1 34.4 mbar
p2 11.3 mbar
p3 0.2 mbar
p4 0.1 mbar
p5 6.2 mbar
p6 3.9 mbar
p7 3.2 mbar
vgas 5.1 m/s
vcomb 9 m/s

Table 4.

Measurements results

Comparisons of error between calculations and experimental results of pressure drops are presented in fig. 11 and 12. Through the application of the mathematical models we find that pressure drops can be predicted within a 20 % error margin. For example let us compare results between calculated and experimental values of pressure drop across 100 mm bed of quartz sand at minimum fluidization conditions. Calculating pressure drop according to equation 23 gives us 12.5 mbar, where physical properties are as follows: ρp = 2650 kg/m3, ρg = 1.204 kg/m3, εmf = 0.55, Lmf = 110 mm ang g = 9,81 m/s2. Bed height increases for 10 mm and so does consecutive voidage. A series of measurements gives us the average value for pressure drop which is p2,3 = 11.4 mbar. As follows from this, the error of our prediction was 8.8 %.

Figure 11.

The comparison of experimental and calculated Δpmf for 200 μm quartz sand

For calculating pressure drops across fully fluidized bed we use equation 26. The only difference comes with a little higher bed and voidage, which remain almost constant with increasing gas velocity to terminal velocity. So if we consider that Lmff = 115 mm and εmff = 0.62 than pressure drop equals 11.4 mbar. With the comparison to the experimental value, which is 10.8 mbar, a 5.2 % error of prediction occurs. Error highly increases in aggregative and slugging mode of fluidization.

Figure 12.

Comparison of experimental and calculated Δpmff for 200 μm quartz sand

Relative pressures were measured at a stationary state. One of the experiments was made when testing the process with quartz sand where the average particle diameter was about 200 μm. The stationary bed height in the reactor was 100 mm and the mass of sand used at simulation was 4.25 kg. When minimum fluidization conditions were obtained, the bed height increased by approximately 15 mm. A series of repeated measuring were carried out

Figure 13.

The size of the particles used for simulation

and the average relative pressure at the bottom of the fluid bed was p2 = 11.3 mbar, with p3 = 0.2 mbar the average value at the top. As follows from this, the pressure drop across fluidized bed was p2,3 = 11.1 mbar. Air flow had an average temperature of 25º C. Inlet gas velocity was about 5.1 m/s in the reactor and 9 m/s in the riser. We found a higher gas velocity for fluidization than calculated, due to a certain amount of air passing through the chute to the riser. This also provides the explanation as to why the measured terminal velocity in the riser was a little lower than anticipated, as the loss of air from the reactor helped increase the air speed in the riser – resulting in the aforementioned lower value.


6. Comparison to the previously used methods

Modern gasification is occurring in fluidized beds. Its advantage is using most fuels (wood, peat and coal) including agriculture “waste” such as straw, corn stover and manure. It has a potential to use municipal waste, such as garbage, it is quicker in response and it has shorter start up time. It lends itself to complete combustion applications which would allow it to use liquid wastes, such as used engine oil, non-recyclable plastics, junk mail & old shoes and garbage for the generation of heat. However, there is a problem of complex design. Still, nowadays most research efforts are being made on fluidization bed technology.

We tested a system very similar to the one tested by G. Löffler, S. Kaiser, K. Bosch, H. Hofbauer (Kaiser S. et al., 2003) with a minor difference. Our reactor had an eccentric diffuser which proved not to be a successful idea (Mele, J. et al., 2010). That is why in future research we are planning to test a reactor with a conical bed similar to those used by Kaewklum and Kuprianov. Our mathematical model is based on the derivation of Ergun’s equation (Kunii & Levenspiel, 1991). L. Glicksman pointed out that for designing an accurate scale model of a given bed all of the independent non-dimensional parameters must be identical, such as considering the case where fluidized bed is operated at an elevated temperature of flue gas or at arbitrary conditions with air (Glicksman, 1982). Our work is also based on attaining similar non-dimensional parameters such as Reynolds and Euler numbers. The Freude number based on the minimum velocity, (vmf/dpg) has been proposed as the parameter to characterize the boundary between particulate and aggregative fluidization and the Archimedes number has been used to correlate a wide array of phenomena (Zabrodsky, 1966).


7. Conclusions

By observing the CFB processes in a three-times smaller laboratory unit with air flow the size and density of particles has been determined. The preferred option was to use brass powder with an average particle diameter of 200 μm. The assumption of particle flow similarity is based on a direct comparison of Reynolds numbers. In this case the Rep are 9.8 and 9.0 in reactor and 46.6 and 50.8 in the riser. There is a 10 % difference between Rep in both cases. Chemical reactions cause variations in temperature, density, and dynamic viscosity all of which affect Rep. If we compare Rep 9.8 and 4.9 at the reactor exit 46.6 and 23.3 at the top of the riser exit, we can see that Rep changes by 50 % and the similarity at this point is actually questioned. By way of example, the experiment carried out with quartz sand was presented. When the process is stabilized and a smooth circulation is established, then pressure drops are as follows: p2,3 = 11.2 mbar, p6,7 = 0.7 mbar, p2,6 = 7.4 mbar and p4,7 = -3.1 mbar. This result set can be characterized as p2> p6 and p4< p7. Pressures are as expected and gas flows are in the appropriate directions. Through the application of the mathematical models we have, pressure drops can be predicted to within a 20% error margin. The experiments highlighted one major problem, namely that the cylindrical tube and asymmetric enlargement of the tube didn’t prove to be a successful construction for the reactor. With beds higher than 13 cm fluidized beds are in aggregative or bubbling fluidization states. In turn, at bed heights over 30 cm even a slugging state is attained. The solution at this point is a conical bed design in accordance with Kaewklum and Kuprianov, 2008.


8. Symbols

Ap Cross-section of particle [m2]
At Tube cross-section [m2]
Bcyc Width of rectangular cyclone inlet dutch [m]
Cx Drag coefficient
D cyc Characteristic cyclone diameter [m]
Dcomb Riser diameter [mm]
Dgas,1 Diameter of reactor upper segment [mm]
Dgas,2 Diameter of reactor lower segment [mm]
Dp Diameter of particle [μm]
Dp,50 Particle diameter at which 50% of particles are collected by cyclone [μm]
Dtube Inside tube diameter [mm]
Fg_p Gravity of particle [N]
g Gravity acceleration [9,81 m/s2]
gc Conversion factor [9,81gm m/s2 wt]
Hcomb Riser height [mm]
i Natural number
j Natural number
L Stationary bed height [m]
Lmf Bed height at minimum fluidization condition [m]
Lmff Bed height at minimum fully fluidized state [m]
Ns Number of turns made by gas stream in a cyclone separator
p Pressure [Pa]
pg,ar Pressure at arbitrary conditions [Pa]
pi Relative pressure in point i [Pa]
pi,j Differential pressure between points i and j [Pa]
pj Relative pressure in point j [Pa]
pn Pressure at normal conditions [Pa]
Rep Particle Reynolds number
Tg,ar Temperature at arbitrary conditions [°C]
Tn Temperature at normal conditions [°C]
vcomb Gas velocity in riser [m/s]
vg Gas velocity [m/s]
vg,ref Gas velocity measured with pitot tube or orifice in tube before gas entering reactor [m/s]
vgas Gas velocity in gasification zone [m/s]
vmf Minimal fluidization velocity [m/s]
vmff Minimal velocity of full fluidization [m/s]
vt Terminal velocity [m/s]
Δp differential pressure [Pa]
Δpmf differential pressure at minimum fluidization [Pa]
Δpmff differential pressure at full fluidization [Pa]
ε Bed voidage
εmf Bed voidage at minimum fluidization
εmff Bed voidage at full fluidization
ηg Dynamical viscosity of gas [Pa∙s]
ηg,ar Dynamical viscosity of gas at arbitrary conditions [Pa∙s]
ηn Dynamical viscosity of gas at normal conditions [Pa∙s]
ρg Density of gas [kg/m3]
ρp Density of particle [kg/m3]
Φm Mass flow [kg/h]
Φm_g Mass flow of gas [kg/h]
ΦV Volume flow [m3/h]
ΦV_g Volume flow of gas [m3/h]

Table 5.




Figure 14.

“Investing in your future”- Operation Part Financed By The European Union – European Social Fund


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Written By

Jernej Mele

Submitted: 12 October 2010 Published: 27 July 2011