1

SCALING PARAMETERS FOR PFBC CYCLONE SEPARATOR

SYSTEM ANALYSIS

Antonia Gil, Luis M. Romeo and Cristóbal Cortés

CIRCE, Centro de Investigación del Rendimiento de Centrales Eléctricas

Centro Politécnico Superior. María de Luna, 3.

50015 Zaragoza (Spain)

email: antgilma@posta.unizar.es, luismi@posta.unizar.es, tdyfqdb@posta.unizar.es

ABSTRACT

Laboratory-scale cold flow models have been used extensively to study the behaviour

of many installations. In particular, fluidized bed cold flow models have allowed developing

the knowledge of fluidized bed hydrodynamics. In order for the results of the research to be

relevant to commercial power plants, cold flow models must be properly scaled.

Many efforts have been made to understand the performance of fluidized beds, but up

to now no attention has been paid in developing the knowledge of cyclone separator systems.

CIRCE has worked on the development of scaling parameters to enable laboratory-scale

equipment operating at room temperature to simulate the performance of cyclone separator

systems. This paper presents the simplified scaling parameters and experimental comparison

of a cyclone separator system and a cold flow model constructed and based on those

parameters. The cold flow model has been used to establish the validity of the scaling laws for

cyclone separator systems and permits detailed room temperature studies (determining the

filtration effects of varying operating parameters and cyclone design) to be performed in a

rapid and cost effective manner. This valuable and reliable design tool will contribute to a

more rapid and concise understanding of hot gas filtration systems based on cyclones.

The study of the behaviour of the cold flow model, including observation and

measurements of flow patters in cyclones and diplegs will allow characterising the

performance of the full-scale ash removal system, establishing safe limits of operation and

testing design improvements.

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INTRODUCTION

Hot gas cleaning plays an essential role in the development of new power generation

technologies such as Integrated Gasification Combined Cycle (IGCC) or Fluidized Bed

Combustion (FBC). The removal of solid particles from the combustion flue gases is essential

in order to maintain gas turbine working conditions and particle emissions in safe limits. In

particular, in PFBC power stations the entrainment of bed particles may lead to erosion and

fouling in downstream equipment. Special importance is the damage of gas turbine blades. In

addition, fly ash can also produce corrosion due to metal alkali compounds.

Cyclone separator systems offer nowadays one of the best solution for removing

particles from high temperature high pressure installations. Combustion gases from

pressurized beds are an example of this harsh environment, and cyclones are, nowadays, the

only solution commercially available for these power stations. These systems are simple, low

cost and maintenance with relatively high collection efficiency. Its main disadvantages are the

complex hydraulic behaviour and a efficiency decrease for small particles (below 5 µm). In

Escatrón PFBC power plant, the hot gas filtration equipment is a two-stage process performed

in nine streams between the fluidized bed and the gas turbine. The cyclones are high

efficiency, Van Tongeren´s type, with a tangential inlet, cylindrical body, conical base, and an

axial outlet for clean gases and outlet port for solid particles in the lower part. The solid

extraction bin has been replaced by a dipleg (similar to those found in catalytic cracking) and

a suction nozzle through which collected particles are evacuated along with some amount of

transport gas. In contrast with other devices, such as series of pressure-tight lockhooppers, the

solid extraction by pneumatic conveying improves cyclone efficiency and allows reliable

handling and cooling of ash particles with low cost.

Ash and combustion gases exit the pressurized bed at nearly 800 °C and 11 bar(g). The

gas and solid mass flow rates depend on load, coal and sorbent characteristics and other

operating variables, in particular those related with fluidisation. These parameters have a

strong influence on the separation efficiency of the cyclones, and there are not well

established theories able to achieve an accurate and complete prediction. Operating

experience at Escatrón have shown sintered deposits and unsteadiness in the dipleg and the

suction nozzle that modify cyclone separation efficiency and affect the cyclone performance

and the capacity of ash conveying lines.

The possibility of achieving analyses to establish the influence of different variables in

a real installation is limited due to a non-controlled operating conditions and a lack of data to

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obtain conclusions. Laboratory-scale cold flow models have been used extensively to study

the behaviour of many installations. In particular, fluidized bed cold flow models have

allowed developing the knowledge of fluidized bed hydrodynamics. In order for the results of

these researches to be relevant to commercial power plant, cold flow models have to be

properly scaled. In the present study, scaling parameters have been developed to build a

dipleg and cyclone cold flow model of a PFBC power plant. The cold flow model permits

detailed room temperature studies, such as determining the filtration effects of varying

operating parameters and cyclone designs.

The study of the behaviour of the cold flow model, including observation and

measurements of flow patterns in cyclone and dipleg, will allow characterising the

performance of the full-scale ash removal system, establishing safe limits of operation, testing

design improvements and determining the filtration effects of varying operating parameters.

This paper presents the most relevant scaling parameters for a cyclone separator system and

an experimental comparison of a PFBC cyclone separator system and a cold flow model

constructed based on those parameters.

CYCLONE SCALING PARAMETERS

Collection efficiency and cyclone pressure drop are the most important variables in

cyclone behaviour. Criteria for cyclone scaling parameters, based on maintain collection

efficiency, have been proposed by several researchers (Cheremisinoff and Cheremisisnoff,

1986; Dirgo and Leith, 1986; Svarovsky, 1981, 1986; Leith and Litch, 1972; Abrahanson et

al., 1978). It is generally assumed the necessity of maintain, at least, Stokes number in order

to maintain collection efficiency. Cheremisinoff and Cheremisinoff (1986) developed the

scaling parameters by analysing the forces that influence a particle within the cyclone. They

proposed to maintain Froude, 2invgDFr = , and Reynolds numbers, gsdvRe µρ= , and a

ratio between densities and lengths, equation 1.

=

pg

s

dD

Re,,Frfρρη (1)

For the laminar regime of flow (Re<2), they suggested ignoring the inertia of the medium and

hence they concluded that the main variables affecting collection efficiency were Froude and

Stokes numbers, g

pgD

vdStk µρ= . Svarovsky (1981) has also proposed to maintain Froude

4

and Stokes numbers. He has developed these parameters from the equation for accelerated,

three-dimensional particle motion with the main assumption of Stokes regime, equation 2:

1vd

Reg

rgpp <=

µρ

(2)

Other authors only mention the importance of maintaining Stokes number especially at low

solid concentrations (Dirgo and Leith, 1986), or suggest that is the Stokes number the main

variable in cyclone efficiency (Svarovsky, 1981; Leith and Licht, 1972). Finally, Chao (1982)

for a dilute flow as the freeboard of a PFBC power plant, has suggested as scaling parameters

the Stokes and Froude number and a particle Reynolds number. The last number is necessary

when the flow regime is different from Stokes regime. Although these authors have proposed

different theories for cyclone scaling, none of them has verified their proposals in a real

installation. So, as first approximation cyclone behaviour depends on the following variables,

figure 1

( )in_sinpgsg C,g,D,V,d,,,f 50µρρ (3)

Figure 1. Parameters affecting cyclone behaviour

Where dp50 has been selected as variable to take into account the particle size distribution at

cyclone inlet. Selecting vin, ρg and dp50 as independent variables in order to identify

dimensionless groups:

η

1-η

VinCs

ρs

ρg

µgdp

D

g

∆P

5

s

in_s

g

s

pg

ing

in

C,,

dD

,DV

,VgD

fρρ

ρµ

ρ

502 (4)

where gDVFr in2= is the Froude number. With the approximation of a flow regime with low

relative velocity for the particles in the cyclone and considering the influence of the

aerodynamic forces by means of the Stokes number (which is a combination of three of the

previous numbers, equation 5).

g

inps

g

sp

g

ing

DVd

DdDV

Stkµ

ρρρ

µρ 2

502

50 =

= (5)

Finally, equation (4) is rearranged to read:

s

in_s

g

s C,,StRe,,Frf

ρρρ

(6)

Froude number takes into account the relation between gravitational and inertia forces.

When particle diameter is small, less than 10 µm, some authors neglect this number due to the

fact that gravitational forces are small compared with inertia forces (Mothes and Löffler,

1985). In our case, more than 80% of the particles are bigger than 10 µm so, it seems

necessary to maintain Froude number.

Reynolds number is not considered to analyse cyclone collection efficiency.

Generally, its influence is near negligible due to Reynolds number is high enough. According

to experiments at different temperatures and pressures, from 1 to 6 bars, and from 293 to

1123ºC, Reynolds influence is significant for values from 103 to 105. The tendency observed

is that Reynolds higher than 105 does not influence cyclone behaviour (Morweiser and

Bohnet, 1996).

Most of the authors take into account Stokes number to analyse cyclone collection

efficiency. Stokes number relates the inertia forces with aerodynamic forces in a flow field.

Stokes number and cyclone efficiency are closely related. Generally, researchers consider

laminar flow or assume Stokes´ law (Rep<1) for particle resistance. Also they assume constant

particle diameter and low particle concentration (< 5g/m3) in order to neglect the influence

between particles. There are several problems related with Stokes conservation between real

cyclone and cold flow model. Firstly, there is a particle interaction when solid concentration

is bigger than 5 g/m3. Secondly, there is a particle size distribution (PSD) at real cyclone inlet,

so the maintenance of Stokes is difficult, due to it would be necessary to maintain Stokes for

each particle size and scale the whole PSD. To solve this problem, researchers usually work

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with Stokes number for dp50, but it does not give an exact idea of the PSD conservation. It is

possible to have a wide PSD, and a narrow PSD with the same dp50 and the cyclone behaviour

would be completely different. Finally, from a practical point of view, it is impossible to

achieve a scaled PSD. In Escatrón PFBC less than 1% of particles are smaller than 0.4 µm,

that is the limit for Rep<1. In the scaled model, only 20% of the particles are smaller than

10µm that is the limit for Rep<1 in this case so, not to maintain Stokes number will introduce

a small error for scaling cyclone efficiency. The error comes from the difference between the

scaled and real dp50 in cold flow model, instead of 16.5 µm, it is 23 µm. Moreover, the

influence of this error is smaller due to the high particle concentration (near 300 g/m3). In the

case of high particle concentrations, the assumptions of considering Stokes influence are not

realistic (i.e. isolated particle, Stokes´ law or laminar flow) because of particle interactions so,

its influence is reduced. Also, according Cheremisinoff and Cheremisinoff (1986) the

influence of Stokes is important in laminar regime of flow where the inertia of the medium

may be ignored. In other case, they concluded the influence of Reynolds and a ratio of

densities, equation (1).

Up to now, the cyclone studies have been based on small particle concentrations.

According Abrahamson et al. (1978) for high particle concentration, bigger than 10 g/m3, the

effect of particle agglomeration is dominant. Hoffman et al. (1991 and 1992) studied the

effect of solid concentration, up to 150 g/m3, on cyclone behaviour. They strengthen that there

were no theories that could explain the effect of concentration and they concluded the

influence of solid concentration in collection efficiency and cyclone behaviour. Finally,

Wheeldon and Burnard (1987) in experiments in Grimethorpe (6-12 bar, 640-910ºC) observed

its influence when collection efficiency increased with solid concentration. As a conclusion, it

seems reasonable to consider solid concentration in cyclone behaviour, especially for high

solid loads, due to the interaction between particles and agglomeration, that modify the

theoretical influence. Escatrón PFBC particle concentration at cyclone inlet is 290 g/m3, much

bigger than 10 g/m3 considered as high particle concentration and bigger than 150 g/m3 of

Hoffman et al. (1991 and 1992) tests. For these reasons, it is reasonable to maintain particle

concentration as a scaling parameter. Moreover, the high particle concentration and particle

diameter support the influence of gravitational forces by means of Froude number.

Scaling parameters reduce to Froude number and particle concentration. It could be

also desirable include the Stokes number although scaling particle size distribution could be

impossible to achieve from a practical point of view. Table 1 lists the geometric and operating

7

parameters that were used to calculate the values of the cyclone scaling parameters, and the

dimensions of the 1/5 scaled cyclone. The real cyclone mean particle diameter, dp50, has been

taken from design data, since to it is not possible to obtain a particle sample from the cyclone

inlet. Table 2 shows a comparison between the values of the dimensionless scaling parameters

for the two cyclone systems.

Table 1. Comparison between Escatrón PFBC and laboratory cold flow model parameters of

the cyclone separator system

REAL CYCLONE

SEPARATOR SYSTEM

LABORATORY COLD

FLOW MODEL SYSTEM

D (mm) 1000 200

T (K) 1030 293

P (bar a) 11.14 3.22

µg (kg/m s) 4.25e-5 1.82e-5

ρg (kg/m3) 3.8 3.8

ρs (kg/m3) 2800 2800

dp50 (µm) 40 23

Vin (m/s) 30 13.4

Cs_in (g/m3) 290 290

Mair (kg/s) 10.6 0.19

Mash (g/s) 800 14

Table 2. Comparison of Escatrón PFBC and cold flow dimensionless scaling parameters

REAL CYCLONE

SEPARATOR SYSTEM

LABORATORY COLD

FLOW SYSTEM

Froude number gDvFr 2in= 91.74 91.79

Reynolds numberg

ing DvRe µρ= 2.68 e+6 5.60 e+5

Stokes numberg

inpsD

vdStk µ

ρ 250= 3.16 5.45

Density ratiog

sρ

ρ 736.8 736.8

Solidconcentration s

in_sCρ

104 e-6 104 e-6

8

DIPLEG SCALING PARAMETERS

The collected particles removed from the PFBC cyclone system flow down a dipleg

and are transported by means of pneumatic conveying thought a suction nozzle in the bottom

of the dipleg. There are no specific models of this flow inside the dipleg, so an approximate

analysis, resorting to reasonable and simple models of the physical situation, is appropriate.

Flow patterns inside the dipleg may be expected to possess the following features:

— Particles slid down on the dipleg wall, following a helical path of variable pitch.

— The gas flow generally follows two paths: near the wall, it moves downwards, with

tangential and axial velocity components, whereas it is reversed at the leg core,

forming an upward flow.

As first approximation dipleg behaviour depends on the following variables

( )soltaxdlgsg C,g,V,V,L,D,,,f µρρ (7)

In this case, selecting, L, ρg and Vax as independent variables in order to identify

dimensionless groups and rewriting

µ

ρρρ axg

2ax

t

axsol

g

sdl VL,

gLV

,VV

,C,,L

Df (8)

A 1/5 scaled model has been built for the dipleg. This factor has been chosen to simulate the

whole PFBC cyclone system. First dimensionless group is a ratio between dipleg dimensions

and it is maintained. Particle-solid densities ratio is also conserved since it was also a

dimensionless group in cyclone scaling. Solid concentration as solid- air flow through dipleg

is maintained with the assumption of cyclone efficiency is similar. Velocities ratio

dimensionless number is equal to the tangent of the sliding particle velocity. Particles

tangential velocity is supposed to be proportional to the tangential velocity calculated with

Alexander equation (Alexander, 1949):

cterV nt = (9a)

( )

−−=

3.014.0

dl 283T*D67.011n (9b)

Particle axial velocity is proportional to the gas velocity though the dipleg and could be

estimated as

sng

nozzle_aax A

mV ρ= (10)

9

The conservation of the transport air flow makes the sliding angle to be conserved. This takes

into account the effects of vortex extending due to suction. This effect could modify the

dipleg flow patterns, so it is important to maintain it constant:n

dl

sn

in

air

snn

dl

insng

sn

t

ax

DD

AA

mm

DD

V1

Am

VV

=

=

ρ(11)

The small difference in the values of exponent n in Alexander equation modifies slightly the

sliding angle between PFBC cyclone and cold flow model. This difference could be estimated

as a 1.6 % and can not be reduced since n depends on the temperature. Froude number is

calculated as a relation between axial velocity, dipleg length and gravity. Because of the

conservation of transport air, Froude number is maintained. Finally, Reynolds number could

not be conserved due to gas viscosity is fixed by the cold flow model temperature.

Table 3 lists the dipleg geometric and operating variables. They have been used to

calculate the dipleg scaling parameters and dipleg erection. Table 4 summarised the

dimensionless parameters of the dipleg, the values of the scaling parameters were closely

matched between the cold flow model and the Escatrón PFBC except for Reynolds number.

Table 3. Comparison between Escatrón PFBC and laboratory dipleg cold flow model

parameters

REAL DIPLEG LABORATORY COLD

FLOW MODEL DIPLEG

Ddl (mm) 400 80

L (m) 9.15 1.83

T (K) 1030 293

P (bar a) 11.14 3.22

ρg (kg/m3) 3.8 3.8

ρs (kg/m3) 2800 2800

Mair (kg/s) 10.6 0.19

Mnozzle (g/s) 163 2.9

Mash (g/s) 800 14.0

10

Table 4. Comparison of dipleg Escatrón PFBC and cold flow model dimensionless scaling

parameters

ESCATRON PFBC

REAL DIPLEG

LABORATORY COLD

FLOW MODEL DIPLEG

Dipleg dimensionsdlD

L 22.0 22.0

Density ratiog

sρ

ρ 736.8 736.8

Solid concentrationair

ashsol M

MC = 75 e-3 74 e-3

Velocities ratiot

axV

V 0.568 0.559

Froude number gLVFr 2ax= 105.3 105.4

Reynolds numberµ

ρ axgVLRe = 1.96 e+5 4.08 e+4

CYCLONE AND DIPLEG COLD FLOW MODEL

Figure 1 shows cyclone and dipleg built with the similarity criteria aforementioned

and have linear dimensions which are one-fifth those of the real PFBC dimensions. Figure 2

shows the cold flow model device that is made up of the following components:

- Two air-pressure supplies: main (L1) and a secondary line (L10) for

fluidisation of the particle-discharging hopper.

- Pressurized solid storage tank (T1) and variable speed rotary valve connected

to a Venturi nozzle (L3).

- Primary cyclone inlet (L4), air with a design solid concentration of 290 g/m3.

- Experimental primary cyclone (T2), equipped with a PMMA dipleg (T4).

- Secondary cyclone (T3) with a solids-collecting bin (T7).

- Two sedimentation chambers with fabric filters for complete collection of

particles and cleaning of the exhaust air (T5 and T6).

- Control of airflow by flow meters and valves downstream the sedimentation

chambers (I1 and I2)

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Figure 1. Scaled cyclone dimensions

Dimensionsa/D 0.460b/D 0.203De/D 0.307S/D 0.891h/D 1.310H/D 3.795B/D 0.399L/D 9.022

a

b

h

H

S

D

De

B

L

.

Figure 2. Laboratory cold flow model cyclone separator system

T PP ∆P

∆P

T P F

T P F

controlpressure valve

ashhopper

hopperfluidisation

rotary feeder

primarycyclone

secondarycyclone

filter 2

filter 1

suctionnozzle

clean air

clean air

ash extractiondipleg

Pin= 2.21 bar(g)

Tin= 20 °C

ash flow= 50 kg/h

air flow= 680 kg/h

12

CYCLONE AND DIPLEG EXPERIMENTAL COMPARISON

Experimental scaling verification is based on a comparison of pressure drop. Cyclone

pressure drop has a strong influence on collection efficiency. The impossibility to take data of

collection efficiency at PFBC power station to compare with cold flow model has made us to

validate the scaling parameters based on cyclone pressure drop. For pneumatic transport as in

dipleg, pressure drop plays an essential role in its analysis. Probes have been placed in several

points though dipleg, and partial and total dipleg pressure drop have been obtained for

verification.

The data used in the following scaling comparisons were taken at operating conditions

after a periodic overhaul of the Escatrón PFBC, with cyclones revised and cleaned of sintered

deposits. The data used in the scaling comparison were taken at a single operating condition

and in steady- state operation. The PFBC power plant load was approximately 90% of the full

load with a standard deviation of 1 MW. Cold flow model pressure drop data were taken

using pressure transducers with a range of 0/62 mbar for cyclone pressure drop and –62/+62, -

37/+37, -37/+37 and –5/5 mbar for dipleg. The data from Escatrón PFBC were obtained with

pressure transducer with a range of 0/490 mbar for cyclone pressure drop, ad –98/+98 mbar

for dipleg pressure drop. Data uncertainty is about 0.4% of span.

PFBC cyclone pressure drop transducers are installed in five of the nine cyclones.

Data from pressure drop varies from a maximum of 199.2 mbar to a minimum of 141.0 mbar.

Table 5 shows the PFBC data and its comparison with cold flow model data.

PFBC pressure drop data shows discrepancies between real cyclones. Most probably, a

combination of ashes and gases non-homogeneity at cyclone inlet could cause these

discrepancies. Another cause to explain this effect is cyclone fouling. As it will be proved in a

next paper (Romeo et al., 1999), fouling causes a reduction in cyclone pressure drop. A

different fouling between cyclones could be the cause of discrepancies in real data.

In order to compare and validate the cold flow model, it is necessary to scale down the

Escatrón PFBC cyclone pressure drop data or scale up the cold flow model data. The

dimensionless variable for the pressure drop is

=

s

in_s

g

s2

in

C,,Frf

V21

Pρρ

ρρ

∆ (12)

The right-hand term of the equation (12) is conserved due to the maintenance of

dimensionless numbers that affect cyclone behaviour. So, to scale pressure drop data it is

13

necessary take in account the velocity ratio to the power of two, it means to operate by a

factor of five.

The agreement between Escatrón PFBC pressure drop data and cold flow model data

scaled up is excellent, as indicated in table 5. For the PFBC cyclones, the pressure drop has an

average of 168.0 mbar and a standard deviation of 20.3 mbar, the 99% of the data would be in

the range of 127.4/208.6 mbar. In the cold flow model, the average is 148.5 mbar with a

standard deviation of 9.0 mbar, so the 99% of the data would be in the range of 124.0/166.5

mbar. The latter range of data is approximately inside the former one. This agreement

provides a verification of the scaling proposed above.

Table 5. Comparison between PFBC and cold flow model cyclone pressure drop data

Maximum Minimum Average Standard

deviation

Cyclone 1

Cyclone 3

Cyclone 5

Cyclone 7

Cyclone 9

191.4

199.2

174.9

150.8

145.4

175.7

190.3

167.7

142.9

141.0

182.5

194.7

172.3

147.7

143.1

7.00

3.83

2.95

2.89

1.72

Average of five PFBC

Cyclones194.7 143.1 168.0 20.5

Cold flow Model

Cyclone

34.43 24.06 29.73 1.79

Cold flow Model

Cyclone Scaled data172.2 120.3 148.5 9.0

Tables 6 and 7 show also a comparison between PFBC and cold flow model dipleg

pressure drop data. Three zones are observed in the dipleg, an upper one where the pressure

drops strongly. An intermediate region where the pressure drop is negative and particles are

going down vertically. Finally, the last zone near the suction nozzle where the pressure drops

due to pneumatic transport. These three zones are observed both, in the PFBC and the cold

flow model, so that qualitatively the behaviour or the diplegs are similar, although a

difference in values is also observed. Table 6 shows the data at real and cold flow model

dipleg.

14

Table 6. Comparison between PFBC and cold flow model dipleg pressure drop data

Maximum Minimum Average Standard

deviation

PFBC dipleg pressure drop 1

PFBC dipleg pressure drop 2

PFBC dipleg pressure drop 3

63.2

- 3.44

22.3

60.6

- 4.94

16.3

61.8

- 3.94

18.1

1.02

0.54

2.31

Cold flow model dipleg pressure drop 1

Cold flow model dipleg pressure drop 2

Cold flow model dipleg pressure drop 3

2.50

- 0.18

0.04

In table 7 the scaled data for the cold flow model is compared with real data. Scaling

up has been done in the same manner as cyclone scaling up, i.e. the velocity ratio to the power

of two. In spite of the similar tendencies in pressure drop, the scaling is not as good as the

cyclone scaling. In this case the effect of varying Reynolds number is affecting the agreement.

Taking into account the Reynolds influence and multiplying by 5 (PFBC and cold flow model

Reynolds relation) the agreement of pressure drop in the two upper zones is excellent.

Possibly, a combination of suction and ash deposition is the responsible of discrepancies in

the lower zone pressure drop data. In addition, the effect of fluidisation air in PFBC dipleg

bottom has not been taken into account in the cold flow model constructed, and it could

modify the measurements or the behaviour in this zone. Further studies are necessary to

explain this discrepancy.

Table 7. Comparison between PFBC and cold flow model dipleg pressure drop data

PFBC data Cold flow model

data

Scaled data

Scaled data and

Reynolds

influence

Pressure drop 1

Pressure drop 2

Pressure drop 3

61.8

- 3.94

18.1

2.50

- 0.18

0.04

12.5

- 0.9

0.2

62.5

- 4.5

1.0

15

CONCLUSIONS

A 1/5-scale model of the Escatrón PFBC cyclone system has been constructed based

on scaling parameters. Comparisons of cyclone pressure drop from the cold flow model and

Escatrón PFBC indicates that the cyclone behaviour of the two cyclones is similar. Because of

cyclone pressure drop is one of the most important parameters in collection efficiency, it is

assumed the cyclone efficiency would be maintained in both systems. This point remains

open due to the impossibility to validate the cold flow model results at the real system.

An analysis of the main variables in PFBC cyclone dipleg has been done. This study

has not been addressed before. It has been impossible to maintain all the scaling parameters

that influence dipleg behaviour. Reynolds number has not been maintained due to cyclone

scaling determinate the value of some variables in dipleg behaviour. Reynolds influence has

been taken into account to validate the cold flow model data. Comparison of dipleg pressure

drop from the cold flow model and Escatrón PFBC show a good agreement through the

dipleg. In the suction nozzle some discrepancies has been observed. The reason for these

discrepancies could be the different behaviour of the ash conveying lines in Escatrón PFBC

and the sedimentation chamber in the cold flow model. Further studies are needed to fully

understand fluid flow around suction nozzle.

The cold flow model is revealed as an important tool to optimize and understand the

cyclone system behaviour. It is also useful to know the influence of different operational

variables. At present, these studies are being carried out.

ACKNOWLEDGEMENTS

This research has been fully supported by ENDESA, S.A. Mr Alfonso Ruiz, director

of Escatrón PFBC power station, Dr. Emilio Menéndez, head of the R&D department of

ENDESA, S.A., and Mr. Diego Martínez, head of the R&D department at Escatrón are

gratefully acknowledged for making possible the project and for all the facilities provided.

Escatrón power plant personnel are also acknowledged for their useful assistance.

NOMENCLATURE

Asn suction nozzle area (m2)

Cs_in solid concentration at cyclone inlet (g/m3)

Csol solid concentration at dipleg (g/m3)

D cyclone diameter (m)

16

Ddl dipleg diameter (m)

dp particle diameter (m)

dp50 particle diameter at 50% of the PSD (m)

Fr Froude number

g gravity acceleration (m/s2)

L dipleg length (m)

ma_nozzle air flow through the suction nozzle (g/s)

Mair air flow at cyclone inlet (kg/s)

Mash ash flow at cyclone inlet (kg/s)

P pressure (bar)

Re Reynolds number

Rep particle Reynolds number

Stk Stokes number

T temperature (K)

Vax axial velocity at dipleg (m/s)

Vin inlet cyclone velocity (m/s)

vr relative velocity (m/s)

Vt tangential velocity at dipleg (m/s)

Greek Leters

η cyclone efficiency (%)

ρg gas density (kg/m3)

µg gas viscosity (kg/m s)

ρs solid density (kg/m3)

REFERENCES

Abrahamson J, Martin CG, Wong KK (1978) The Physical Mechanisms of Dust

Collection in a Cyclone. Transactions of the Institute of Chemical Engineers, Vol. 56, pp.168-

177.

Alexander R (1949) Fundamentals of Cyclone Design and Operation. Procedures of

the Australian Institute Min. Metall, nº 152, pp.203-208.

Chao BT (1982) Scaling and Modelling. Handbook of Multiphase Systems. Edited by

Gad Hetsroni, Hemisphere Publishing Co, pp.(3)44-(3)48

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