Analysis of operational filtration data part I. Ideal candle filter behavior

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POWDER TECHNO ELSEVIER

Powder Technology 94 ( 1997 ) 15-21

Analysis of operational filtration data Part I. Ideal candle filter behavior Duane H. Smith ..I, Victor Powell, Goodarz Ahmadi, Essam Ibrahim US Department of Energy. Federal Energy Tedmology CePtter, PO Bo.r 880, 3610 Collins P'err3."Road, Morgantown. WV 26507-0880. USA Received 1 November 1996: revised 17 April 1997: accepted 22 April 1997

Abstract

Operating data for the hot-gns filtration system of the Integrated Gasification and Cleanup Facility (IGCF) at the Federal Energy Technology Center are carefully analyzed. A model for candle filters is developed and used to describe the ideal filtration process. The parameters of the model are evaluated with a least-square error fit procedure. It is shown that the model predicts the time variation of the pressure drop with reasonable accuracy. The model is used to evaluate the buildup of filter-cake thickness and the filter-cake permeability. © 1997 Elsevier Science S.A. Keyword.v: Filtration: Gas cleaning: Candle lilters; Integrated gasification combined cycle technology

I. Introduction

The use of cylindrical candle filters to remove fine ( ',- 0.005 mln ) particles from hot ( ~ 500-900°C ) gas streams is currently being developed for applications in advanced pressurized fluidized bed combustion (PFBC) and integrated gasitication combined cycle (IGCC) technologies. Successfully deployed with hot-gas liltration, PFBC and IGCC technologies will allow the conversion of coal to electrical energy by direct passage of the filtered gases into nonruggedized turbines and thus provide substantially greater conversion efliciencies with reduced environmental impacts

III. In the usual approach, one or more clusters of candle filters are suspended from a tubesheet in a pressurized ( P < I MPa) vessel into which hot gases and suspended particles enter, the gases pass through the walls of the cylindrical filters, and the filtered particles tbrm a cake on the outside of each filter 1241. The cake is then removed periodically (typically. one to three times per hour}, by a backpulse of compressed air from inside the lilter, which passes through the filter wall and filter cake. In various development or demonstration sy:~tems the thickness of the filter cake has proved to be an important, but unknown, process parameter. For example, the distance * Corresponding author. Also at Department of Physics. West Virginia University. Morgantow~, WV. USA. (1032-5910/97/$17.00 © 1997 Elsevier Science S.A. All rights reserved PIIS0032-5910(97)03273-7

between adjacent filters typically is on the order of 5 cm. If the filter-cake thickness should reach 2.5 cm, 'bridging" of cake between adjacent filters would occur, leaving little space between the filters into which the incoming gases and particles could flow. Bridging might eventually occur if the removal of cake at each cleaning were not quite complete, or if a fraction of the particles removed were re-entrained and reliltered after each cleaning backpulse. The accumulation of particulates around and among filters is not just a hypothetical concern. Operational experience with the Tidd PFBC demonstration plant revealed that under some conditions the buildup of large masses of particulates among the filters can. indeed, be an important problem, producing excessive pressure drops within the filter vessel and perhaps even filter breakage 15 ]. Because of the high temperatures and pressures, the geometries of the filter clusters and mechanical supports, and other lechnical problems, on-line measurement of cake thicknesses during lilte,'-system operation has not been feasible in most systems. However, when the pressure drop across the filter tubesheet, the gas flow rate, and the particle concentration in the incoming gases are measured, these data can be used to calculate the mass of filter cake on each filter. If filter-cake samples cap, be obtained (e.g. from the filter-vessel hopper or during shut-down ) so that the filter-cake porosity can be measured, then the filter-cake thickness can be estimated during plant operation as well. In a typical filter system, the required flow data are logged and the cake thickness can be

16

D,H. Smith et aL / Powder Technology 94 (1997) 15-21

estimated several times per minute, so that the filter system need not be operated 'blindly', without knowledge of the extent of cake buildup. The following section describes a physical model for cake and pressure buildups on candle filters between cleaning backpulses. When combined with operating data and laboratory measurements of the cake porosity, the model may be used to calculate the filter-cake thickness and permeability. When used under a variety of operating conditions (e.g. different coals, sorbents, temperatures, etc.), the model may eventually provide useful information on how the filter-cake properties depend on the various operating parameters. In this study, filtration data for the filter vessel of the Federal Energy Technology Center (FETC) Integrated Gasification and Cleanup Facility (IGCF) are analyzed. It is shown that a simple model may be used to describe the filter-cake buildup and the time variation of pressure drop across the candle filters. This "ideal' model (described below) omits several effects that are sometimes thought to be significant by various researchers, including ourselves. However, we found that until the basic behavior had been described and its ability to fit actual operating data had been quantified, it was premature to consider secondary effects. Effects analogous to some of those discussed in this paper have long been encountered in bag filtration and in filtration of liquids [6,7]. However, substantial differences occur in filtration of hot gases with candle filters, because of the different filter shapes and rigidities, fluid properties, and other operating conditions.

2. Ideal filter operation model

( 1)

All n filters (and their cakes) operate in parallel and are subjected to the same pressure drop. Thus their effective resistance R is

where v is the velocity vector, P is the pressure, and k is the permeability. To simplify the model, the small area at the bottom of the filter (about 1% of the total filter surface), for which the gas flow rate differs significantly from the rest of the filter, is ignored in the subsequent analysis. Under assumptions ( i ) (iii), iRf and iR~ are the same for all n filters, and Eq. (3) reduces to

R,= (l/n)(Rr+R~) +Ro

(5)

Because of the cylindrical geometry of the filters and filter cakes, Darcy's law is solved in polar coordinates. Assuming that the pressure varies only radially, the resulting pressure drop across each clean candle filter (in the absence of filter cake) is [8] APf= (1/2rrkf)lt(Q/nh) In(b/a)

(6)

where Q is the vessel (volumetric) gas flow rate, kf is the filter permeability, h is the filter length, and a and b are the inside and outside radii of the filter wall, respectively. At constant gas flow rate into the filter vessel, Q, and constant volume fraction of particles in the incoming gas, F, the volume of filtered particles per filter that arrives in the filter vessel during time interval t is

V(t) = FQt/n( I - (b)

(7)

(3)

where Ro is the passage resistance.Itshould be noted thatthe passage resistanceis,in general, a function of flow rate.

(8)

where ~b is the porosity of the cake. The outer radius of the filter cake, B(t), at time t is then given by

B(t) = b [ 1 + FQt/Tmh( 1 - ~ ) b 2] i/:

(9)

The increase in the pressure drop across the filter cakes over the time interval from t = 0 to time t is AP~(t) = ( 1/4zrk¢)l.L(Q/nh ) In[ 1 + FQt/nhrr( 1 - $)b 2] (lO)

(2)

The net, measured pressure drop is the sum of the pressure drop across filtersand filtercakes and the pressure drop through other flow paths in the filtrationsystem. Therefore, the net vessel resistance R, is

R,,--R+Ro

(4)

The corresponding volume of each filter cake is

Consider a filter vessel with n candle filters. For each filter, the gas flows through the filter cake, then through the filter wall, so that the ith filter and the corresponding filter cake constitute two resistances in series:

IIR=~,(II'Rp)

v = (kilt) VP

V = FQtln

2. I. Pressure drop from filters and filter cakes

iRp = iRe+ ire

The model used here makes the following assumptions: (i) all n filters have the same permeability; (ii) essentially all particles that enter the filter vessel are deposited on the filters; (iii) the particles are distributed uniformly among the filters and on each filter surface; and (iv) the filter cakes (as well as the filters) obey Darcy's law,

where k~ is the filter-cake permeability. Typically, the filters are cleaned periodically after interval t' (t',,, 20--60 min) with a hackpulse of compressed air of about 0.2 s duration. In Eq. (10), t is the time measured after the backpulse,

2.2. Ideal operation In the simplest case, cleaning of the filters by the backpulse is complete and no 're-entrainment' (i.e. refiltration) of any

D.H. Smith et al. /Powder Technology94 (1997) 15-21 of the cake occurs. At time t = 0 the filter-cake thickness is zero, and the pressure drop A P - A P o arises only from the clean filters: A P - A P , , = (1/27rkf)#(Q/nh) ln(b/a)

( 11 )

where AP is the total pressure drop (across the tubesheet) and APo is the system pressure drop in the absence of the filters. Over the time interval t = 0 to t = t' filtration occurs, and A P - AP,, = Iz( Q/27mh ) { ( 1/kf) In(b/a) + (1/2k~) In[l+FQt/nhqr(i-dp)bZ]}

and particles enter through a pipe which extends from the bottom of the tank to near the top of the filter vessel. The resvlts of a series of tests were reported by Rockey et al. [9]. In this study, a segment of the data for test No. 94FBG08 from 12:50 pm, 20 July 1994 to 4:50 am, 21 July 1994 is analyzed. For this case, Montana # 6 coal was used in the gasifier. The average gas flow rate to the filter vessel was 0.0156 m3/s at a temperature of 830 K. There were two ceramic filters of length 0.5 m installed in the vessel during these tests. Every hour a backpulse pressure of 3.13 MPa for a duration of about 0.2 s was used to clean the candle filters.

(12)

At t = t' the backpulse occurs, and A P - A Po becomes negative for a fraction of a second. Because cake removal is complete and no re-entrainment occurs, after the backpulse the pressure drop returns to the initial value for the clean filters:

AP(t=t') -AP,,=AP(t=O) -AP,,

17

~ 13)

where A P ( t = 0 ) - A P , , is given by Eq. (11). During the second cycle and all subsequent cycles, the cake buildup, pressure buildup, and cleaning of the first cycle are simply repeated. From on-line measurements of F and Q (and of the temperature, to get p,), and from laboratory measurements of the filter dimensions (a, b, h) and cake porosity (~), fits of Eq. (12) to the experimental data yield the filter-cake permeabilit) (k,.). (For the gas viscosity/z, see Appendix A.) The time variation of the thickness of the filter cake is given as

~( t) =B( t~ - b = b { [ I + FQtl mih( I -tb)b2] t/-'- I} (14) where it is assumed that the volume fraction of solids in the incoming gas is a constant.

3. Integrated Gasification and Cleanup Facility A schematic diagram of the Morgantown Energy Technology Center's Integrated Gasification and Cleanup Facility (IGCF) is shown in Fig. 1. The gasification system is composed of a three-stage refractory-lined gasifier, coal feeder, and batch hoppers, and two cyclones. The candle filter vessel and a desulfurization unit form the main part of the cleanup facility. Pulverized coal is pneumatically supplied to the gasifier along with steam and preheated air. The product gases are passed through the cyclone separators before entering the candle filter vessel. The gasifier operates at 2.93 MPa (about 29 atm), and the pressure at the inlet of the candle filter vessel is reduced to about 2 MPa (20 atm). There is a pressure drop of about 35 kPa across the filter vessel. The IGCF filter vessel can accommodate up to four candle filters. Fig. 2 shows a cross-section of the filter vessel. Gases

4. Results 4.1. Operating data Figs. 3 and 4 show the variation of the ratio of pressure drop to flow rate versus time for three and fifteen one-hour cycles, respectively, of operation of the filter vessel of the IGCF unit. The corresponding time variation of the volurv ~tric flow rate through the vessel is shown in Fig. 5. (The pressure drop AP is in MPa, the flow rate Q in m3/s, and the time t in s.) "Ine roughly linear buildup of pressure drop after each backpulse is clearly observed from Figs. 3 and 4. The flow rate appears to be steady with some random variations. At about 15 000 s, there is a step change of about 10% in the mean flow rate. For t < 15000 s, a portion of the gas from the gasification unit was sampled for particle concentration measurements, while for larger times the entire flow passed through the filter .,essel. During the transition, some adjustment of the operation was also required. As a result, the pressure variation in the fifth cycle exhibits abnormal behavior.

4.2. Ideal operation If only a few filtration/cleaning cycles are monitored, the operation of the filtration system may appear ideal upon casual inspection. Fig. 3 clearly illustrates the details of the pressure drop buildup and its sharp reduction during the backpulse for three cycles of the filter vessel of the IGCF (gasification) unit. The apparent constancy of the baseline values seems to indicate that no major incomplete cleaning or dust cake re-entrainment occurred, From laboratory measurements of ~band operating data for F it was estimated that F / ( I - ~ b ) = 1.2× l0 -s. A leastsquare error fit of the ideal operation model (Eq. (12)) to the data for the fifteen cycles (54 000 s) plotted in Fig. 4 yielded

ApJQ=O.O0~35 +0.003097 In( 1 +3.67 × 10-8Qt) (15) where t is measured from the baekpulse of the previous cycle and all parameters are in SI units. The filters had been in use

18

D.H, Smith et aL / Powder Teclmoh)gy 94 ~1997J 15-21

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/'or many hours before the data that we analyzed were collected; hence, we assume (and the data indicate) that any 'filter conditioning' (i.e. changes in the effective permeability of the filter) had reached a steady state. Because the A P,, term and the filter permeability term in Eq. (12) were both independent of time over the data interval analyzed, the first term in Eq. (15) includes both of these effects. The predictions of Eq. (15) for the three-cycle and fifteencycle operating periods (Figs. 3 and 4) are plotted in Figs. 6 and 7, respectively. Comparisonof Figs. 3 and 4 with Figs. 6 and 7 makes it readily apparent that the ideal operation model provides a reasonable fit to the data. Inclusion of the time variations in the flow rate and pressure drop even made it

possible to predict some of the 'noise' in the operating data. The statistical RZ-value for Eq. (15) and Fig. 7 was 0.78 (which indicates that roughly 78~ of the data are explained by the ideal model). A more detailed check on the statistical fit of the model is provided by Fig. 8. This figure illustrates the statistical residual (measured value minus value calculated from the fit) for each of the individual measured values. The small residuals indicate that the statistical fit is quite good. The very largest residuals correspond to the sporadic fluctuations in the detectors and/or other system 'noise'. It also appears from Fig. 8 that the residuals for the first 15 000 s are positive, while those for the larger times are

D.H. Smith et al. / Powder Technology 94 (1997) 15-21

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negative. At this time, measurement of F was discontinued, and the average value of Q also changed. The change in the residuals at this time indicates that the operational changes affected not only the volume flow ratq.= Q, as shown in Fig. 5 (and included in the fit), but also other parameters ~uch as solids volume fraction F as well. There is also a high level of

D.H. Smith et al, / Powder Technology 94 (1997) 15-21

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provide a useful procedure for estimating the filter-cake thickness during the operation of the filter vessel. The analyses of IGCF data indicate the importance of simultaneously measuring particle concentrations as well as gas flow rates and tubesheet pressure drops. The analyses also suggest that computer control of cleaning backpulses may be important to maintain accurate reproducibility and measurement of the length of the filtration cycle. The results also seem to suggest that particle re-entrainment and/or incomplete cleaning may be important and may need to be included in the analysis. These aspects, however, are to be studied in the subsequent parts of this research. With such improvements, physical models of filter-vessel operation and their fits to operating data may prove to be useful in analyzing and improving the performance of filtration systems.

3.0

6. List of symbols E E

2.0

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0,0

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¢._u

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2000

4000

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Fig, 9. Time variation of tilter-cake thickness as calculated from Eq, ( 14L

APr

residuals lbr the filth cycle, which is as expected from the operational changes made at that time, During the filtration process the cake thickness gradually increases with time until the backpulse occurs. The ideal filtration model may be used to estimate the cake thickness. The buildup of cake thickness as a function of time as predicted by Eq. (14) is shown in Fig. 9. It is estimated that the cake thickness reached about 3.5 mm just before the backpulses occurred. The coefficient of the logarithm term in Eq. (15) is related to the cake permeability. From the fit of the model, the cake permeability is estimated to be about 10- ~z m2, which is in the expected range.

AP,,

O R l

inside filter radius (m) outside filter radius (m) outside filter-cake radius (m) volume fraction of particulates in incoming gas/ particle stream filter length (m) filter-cake permeability (m-') filter permeability (m-') number of filters total pressure drop across tubesheet (MPa) increase of pressure drop across cake during one cycle (MPa) pressure drop across (clean) filter (MPa) total pressure drop minus pressure drop across filters and filter cakes (MPa) (volumetric) gas flow rate (m3/s) resistance to gas flow (MPa s/m 3) time ( measured from time of backpulse ) (s)

Greek letters 8 #

cake thickness (m) gas viscosity ( Pa s) filter-cake porosity (voidage)

Acknowledgements

5. Conclusions The results presented here indicate that the simple ideal filtration model together with appropriate statistical fits may be used to capture the main features of the IGCF filter vessel pressure drop variations. The results may also be used to estimate the filter-cake permeability. Such information could

The authors would like to thank John Rockey of the Federal Energy Technology Center for providing the IGCF filtration data and for his many helpful discussions. V. Powell and E. Ibrahim were Faculty Participants under the Oak Ridge Institute for Science and Education (ORISE) program; G. Ahmadi was a Senior Associate under the National Research Council (NRC) program. This work was wholly funded by the Office of Fossil Energy, US Department of Energy.

19.1-1. Smith et al. / Powder Technology 94 (1997) 15-21

Appendix A Estimation of the filter-cake permeability k,. and thickness t~from Eqs. (12), (14), and (15) requires that the gas viscosity p, be known. The latter quantity was calculated from the measured gas composition, temperature, and pressure by means of the corresponding-states method of Lucas, as described by Reid et al. [ 101. The gas contained 0.4 mole%, or greater~ of (in increasing order) argon, oxygen, methane, carbon monoxide, hydrogen, carbon dioxide, water, and nitrogen, as follows: 0.41, 0.47, 3.65, 5.81, 12.44, 13.36, 17.02, and 46.57 mole%. The calculated viscosity was /x=0.358× 10 -5 Pa s.

References [ 1] M.J. Mudd and D.A. Bauer, in J.P. Mustonen ~ed. ), Proc. 9th Int. Conf. Fluidized Bed Combustion, 1987, ASME. New York, pp. 256260.

21

[2] R. Clift and J.P.K. Seville, Gas Cleaning at High Temperatures, Blackie, New York, 1993. 13l K.V. Thambimuthu, Gas Cleaning for Advanced Coal-Based Power Generation, IEACR/53, lEA Coal Research, London, 1993. [41 W.C. Yang, R.A. Newby, T.E. Lippert and D.C. Cicerco, Cold flow studies of a novel fluidized bed emissions clean-up concept, Powder Technol., 63 (1990) 55-68. [ 51 T.E. Lippen, G.J, Bruck, Z,N. Sanjana and R.A, Newby, Westinghouse Advanced Particle Filler System, Proc. Advanced Coal-Fired Power Systems, Morgantown Energy Technology Center. US Dep~"lment of Energy, Morgantown, WV, 1995, pp. 123-139. [6] F.A.L. Dullien, Introduction to Industrial Gas Cleaning, Pe~amon, Oxford, 1989. [7] N.P. Cheremisionoff and D.S. Azbel. Liquid Filtration, Ann Arbor Science, Woburn, MA, 1983. [ 8 ] J.P.K. Seville, R. Clift, C.J. Wither and W. Keidel, Rigid ceramic media for filtering hot gases, Filtr. Sep., 26 (1989) 265-271. 191 J.M. Rockey et al., High Temperature High Pressure Filtration and Sorbent Test Program, METC/Shell Cooperative Agreement, CRADA 93-01 I, Morgantown Energy Technology Center, US Department of Energy, Morgantown, WV, 1995. [ 10] R.C. Reid, LM. Prausnitz and B.E. Poling, The Properties of Gases and Liquids, McGraw-Hill, New York, 4th edn., 1987, p. 41 I.