GPDC Interpolation: Use, Misuse and Updates

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GPDC Interpolation: Use, Misuse

and Updates

By

Henry Z. Kister, Jeffrey Scherffius, Khashayar Afshar,

and Emil Abkar

Fluor, Aliso Viejo, CA, USA

Presented at the Distillation Topical Conference, AIChE Spring

Meeting, Houston, Texas, April, 2007

UNPUBLISHED

Copyright Henry Z. Kister, Jeffrey Scherffius, Khashayar Afshar, and Emil Abkar The AIChE shall not be responsible for statements or opinions contained in its publications

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GPDC Interpolation: Use, Misuse, and Updates

Henry Z. Kister, Jeffrey Scherffius, Khashayar Afshar, and Emil Abkar

Fluor, Aliso Viejo, CA, USA

Summary

For several decades, the Sherwood-Eckert GPDC (Generalized Pressure Drop Correlation) chart has been the standard of the industry for predicting packing flood points and pressure drops. Strigle’s GPDC chart for random packings (Figure 1) and Kister and Gill’s GPDC(SP) chart for structured packing are the “best and latest” versions of the GPDC as discussed in the latest distillation texts. Plotting experimental flood and pressure drop data on the GPDC contours for each packing extended the GPDC into an atlas of accurate and useful interpolation charts. This interpolation procedure desensitized the GPDC to inaccuracies in packing factors and watches out for data-lean regions where uncertainties prevail. This is especially important since deviations from packing pressure drop correlations tend to be systematic rather than random. The use of the GPDC interpolation procedure for tower rating, debottleneck evaluation, analysis of operation, and retrofits is discussed with examples based on actual experiences.

Two major problems have been experienced with the GPDC interpolation procedure: misuse and need for updating. This paper discusses correct and incorrect applications of the procedure. Incorrect calculation of kinematic viscosity, using a packing factor different from that shown on the chart, calculating pressure drops above the flood point, and extrapolation to data-lean regions, have been the main misuses. Updating is needed with new developments in the field. With the last update 12 years ago, and some exciting developments since, the paper presents 22 new interpolation charts. During these 12 years high-capacity structured packings were very successfully introduced to the industry. The paper adds interpolation charts for many popular high-capacity structured packings, for other popular new packings, and for some popular packings for which supplier data had been updated.

Overall, this paper guides engineers on correct and incorrect uses of this GPDC interpolation procedure, and updates the method for today’s new state of the art packings.

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The Generalized Pressure Drop Correlation (GPDC)

For several decades, the Sherwood-Eckert GPDC (Generalized Pressure Drop Correlation) chart has been the standard of the industry for predicting packing flood points and pressure drops. This chart, initially developed by Sherwood et al.(1), and later modified by Lobo et al. (2), contained only a single curve that predicted packing flood points. Leva (3) retained the flood-point curve and added a new family of curves onto the chart to predict packing pressure drop. Copigneaux (4) and Eckert (5,6) proposed further modifications. In a later version, Eckert (7) omitted the flood curve from the chart, retained only the pressure drop curves, and preformed other minor modifications. Finally, Strigle (8) changed the scales of Eckert’s later version from log-log to semi-log to make interpolation between adjacent pressure drop curves easier. Strigle’s chart (Figure 1) is the “best and latest” and preferred version of the GPDC as discussed in the latest distillation texts (8-10).

All the versions of the GPDC discussed above were based on random packing only. For structured packings, Kister and Gill (11) produced a modified chart [GPDC (SP), where SP stands for Structured Packings, Figure 2] that empirically gave better fit to a large database of published structured packing data

The GPDC chart ordinate is the capacity parameter, given by:

CP = Capacity parameter = 0.5_ν0.05

P SF

C (1)

In Eq. (1), v is the kinematic viscosity of the liquid [NOTE: the kinematic viscosity (centistokes)

is obtained by dividing the dynamic viscosity (centipoises) by the specific gravity, not by the

liquid density in English units]. FP is the packing factor, which is an empirical factor

characteristic of the packing size and shape. The packing factor for each GPDC chart is always listed on the GPDC chart. An atlas of GPDC interpolation charts, as well as an early update, are presented elsewhere (10, 18).

CS is the C-factor, i.e., the superficial gas velocity US corrected for vapor and liquid densities (ρ V and ρ L), given by Eq. (2):

CS = US G L G ρ ρ ρ − (2)

The GPDC chart ordinate describes the balance between the vapor momentum force, which acts to entrain swarms of liquid droplets, and the gravity force, which resists the upward entrainment.

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tray columns (12).

The GPDC chart abscissa is the flow parameter, Flv, given by:

Flv = 5 . 0       L G G L ρ ρ (3)

The flow parameter [Eq. (3)] represents the ratio of liquid kinetic energy to vapor kinetic energy. High flow parameters are typical of high liquid rates (the L term) and high pressures (the vapor density term). Conversely, low flow parameters are typical of vacuum and low liquid rate operation.

Removal of the flood curve from recent versions of the GPDC curtailed its capability to predict flood. This capability was reinstated by a simple correlation by Kister and Gill (13).

7 . 0 1 0.12 p F = F ∆Ρ (4)

Equation (4) expresses the pressure drop at the flood point as a function of the packing factor alone. Once this pressure drop is known, the flood velocity can be calculated from the GPDC (or any other good pressure drop prediction method). Equation 4 states that the pressure drop at the flood point decreases as the packing capacity increases, as observed earlier by Zenz (15), Strigle and Rukovena (16), and Mackowiak (17). The numerical constant originally proposed by Kister and Gill was 0.115. Strigle (8) endorsed this equation, but with the upward rounded coefficient of 0.12 in equation 4.

Strigle (8) and Kister and Gill (11, 13) compared predictions from the latest version of the GPDC (Fig. 1 and 2) to thousands of packing pressure drop measurements. The GPDC correlation was shown to give good predictions for most pressure drop data. It generally works well for the air-water system for flow parameters as low as 0.01 and as high as 1 (8). For nonaqueous systems, it works well for flow parameters of 0.03 to 0.3 (typical of atmospheric distillation).

The GPDC correlation was shown (11, 13) to be optimistic for flow parameters greater than 0.3 (typical of pressure distillation and/or high liquid rate applications). Strigle (8) attributes these optimistic predictions to enhanced liquid frothiness at higher pressure. Robbins (14) identified another limitation at low liquid rates (flow parameters <0.03) where liquid properties have a much lesser effect on pressure drop than the GPDC predicts.

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GPDC Interpolation

There were two other issues that have been problematic to the GPDC. First, predictions from the GPDC correlation are sensitive to the packing factor. Strigle (8) and Kister and Gill (13) found that most packing factors reported in the literature are satisfactory. However, for a few packings, the packing factors gave poor fit to experimental pressure drop data. Also, for some packings, the dependence of pressure drop on vapor and liquid loads was not adequately predicted by the GPDC correlation.

An interlinked issue identified in our analysis (13) is that deviations from the correlation tend to be systematic rather than random. Further, some regions where the correlation tended to provide poor pressure drop predictions are those of great commercial interest. It was stressed that an excellent fit to experimental data is insufficient to render a packing pressure drop correlation suitable for design. In addition, the correlation limitations must be fully explored. This message extends beyond the GPDC to any other packing pressure drop correlation.

These limitations were overcome by GPDC interpolation.

Superimposing experimental data points (for a given packing) on the curves of the GPDC chart converts the GPDC into an interpolation chart (for the packing). Every chart in the Appendix is a GPDC interpolation chart. Pressure drops are calculated by interpolating the plotted pressure-drop data. The correlation curves solely help guide the interpolation. An entire atlas of interpolation charts and an application procedure are available elsewhere (10). An early addendum updating this atlas has also been published (18).

Charts 10.2502 through 10.2514 in the Appendix are random packing interpolation charts, and the other charts in the Appendix are structured packing interpolation charts. For random and grid packings, the curves on the interpolation charts are those of the Strigle version of the Eckert GPDC (Fig. 1). For structured packings, the curves on these interpolation charts are those of the Kister and Gill GPDC (SP) (Fig. 2). For all charts (random, structured or grid packings), the abscissa of the correlation is the flow parameter, given by Eq. (3), and the ordinate is the capacity parameter, given by Eq. (1).

Flood and maximum operational capacity (MOC) data are also plotted on the GPDC interpolation charts, and the charts are invaluable for interpolating these. The MOC (also referred to as the maximum efficient capacity) is defined as (8) “Maximum vapor rate that

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provides normal efficiency of a packing”. Where flood data are absent, Eqs. (4) and (5), respectively, can be used for inferring flood points and MOCs from pressure-drop data on the charts.

US,MOC = 0.95 US,F1 (5)

Kister and Gill (11,13) compared flood-point predictions from Eq. (4) to their massive data bank for modern random and structured packing. Pressure drops were calculated using the GPDC interpolation charts. They showed that Eq. (4) predicted all the flood points in their data bank to within + 15 percent and most to within + 10 percent. It was also shown (10) that this procedure is insensitive to reasonable errors in packing factors.

The suitability of the GPDC interpolation charts as a basis for interpolation is not accidental. Packing pressure drops correlate extremely well with GPDC coordinates, i.e., the flow parameter and the capacity parameter. The dependence does not always follow the correlation contours, but always appears to exist. Further, the correlation coordinates are essentially a “performance diagram,” i.e., a plot of a vapor load against liquid load, a tool commonly used for charting column hydraulic performance.

The conversion of the GPDC into interpolation charts overcomes the multitude of correlation limitations. The GPDC interpolation charts readily identify any regions where data veer off the correlation curves and give unreliable estimates (by data interpolation) in these regions. Packing factors, often criticized for being inaccurate and inconsistent, cease to be critical variables. Inaccuracies in packing factors merely cause data to veer off the curves, and have no effect on the interpolation.

It may be argued that the interpolation procedure breaks down when data are absent. The counter-argument is that the GPDC correlation curves are always there to fall back on and to get a prediction, but now there is also a tool to warn that there are no data in this region and that uncertainty is involved.

A shortcoming of the GPDC interpolation data chart procedure is that it replaces a single correlation chart by an atlas. The interpolation charts consume more storage space in the design manual or on the computer and require a greater updating effort.

Updates

As stated, the GPDC interpolation procedure does require updating. The last update was issued in 1995 (18). Much happened in packing technology since, and this is addressed by this update.

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The updated charts for 22 packings are in the Appendix.

1) A recent development followed the realization that liquid drainage in structured packings

was restricted at the element-to-element transition rather than inside elements. This means that the liquid accumulation leading to flood initiates at the element transition region. A fourth generation of structured packing evolved, in which the main body of each element has layers inclined at 45 degree, but the ends of each element are rounded or vertical to promote drainage at this end region. These high-capacity structured packings offer more capacity compared to equivalent 45 degree inclined packings with efficiency the same with some (19-22) and slightly lower with others (23). Charts 10.6801 through 10.7104 are for these packings.

2) Inside each element of a structured packing, corrugated sheets are most commonly

inclined at about 45 degrees to the vertical (typically indicated by the letter “Y” following the packing size). This angle is large enough for good drainage of liquid, avoiding stagnant pockets and regions of liquid accumulation, and small enough to prevent gas from bypassing the metal surfaces. In some packings, the inclination angle to the vertical is steepened to 30 degrees (typically indicated by the letter “X” following the packing size). This improves drainage, and therefore capacity, but at the expense of reduced gas-liquid contact, and therefore, efficiency. Many new “X” type packing were added after the last update of our charts. Charts 10.6152 through 10.6156 are for these packings.

3) For one line of popular structured packing, Flexipac® 1, 2, 3 and 4Y, the original GPDC

interpolation charts (10) were based on pressure drop data measured in an extensive air-water test program by Koch Engineering in 1982 (24). Recent publications by the same vendor appear to have shifted support to the vendor’s new air-water data (21, 26) which show significantly more pressure drop under equivalent conditions. Further discussion in Example 3 below. Charts 10.6102R1 through 10.6108R1 are revised charts for these packings based on the vendor’s latest data

4) The Raschig Super-Ring® high-capacity random packing has become available and

gained popularity. Charts 10.2502 through 10.2514 are new GPDC charts for various sizes of this packing.

5) Data and GPDC charts for Hyperfil® Knitted Mesh Tower Packing were recently

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Use and Misuse

All the examples below are based on actual experiences. Some details could have been changed in order to make it difficult to recognize where the experience occurred.

EXAMPLE 1. TYPICAL FLOOD & PRESSURE DROP CALCULATION AND APPLICATION TO A POSSIBLE RETROFIT

A 6’-0” chemical vacuum tower contains a 20-ft bed of #1.5 metal Raschig Super-Ring® packing. The tower is to be retrofitted for the following flow rates:

Vapor flow rate = 40,000 lb/h., vapor density = 0.036 lb/ft3 Liquid flow rate = 32,000 lb/h., liquid density = 48 lb/ft3 Liquid viscosity = 0.60 CP

(i) Would the packing achieve these flow rates?

(ii) If the packing is to be replaced by Mellapak Plus® 252Y or Flexipac® HC® 2Y

structured packing, can a pressure drop reduction be achieved?

SOLUTION

1) The flow parameter is calculated from equation 3.

Flv = 0.022 48 036 . 0 000 , 40 000 , 32 0.5 ₌      

2) The C-factor is calculated from equation 2.

AT = Tower area = 62 28.27 .2 4 = ft π Vapor velocity, US = 40,000 / (3600 0.036 28.27) = 10.9 ft/s C-factor (eq. 2) = 10.9 0.299ft/s 036 . 0 48 036 . 0 ₌ −

3) Calculate the kinematic viscosity in cS. This is obtained by dividing the dynamic

viscosity in cP by the liquid density in g/cm3_{. Centistokes, centipoises and g/cm}3_{are all}

units in the CGS system, and are consistent. An easy way to remember is that kinematic viscosity cS is the dynamic viscosity in cP divided by the specific gravity (SG).

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No. 1 MISUSE

υ = 0.60 / 48 = 0.0125 cS IS

WRONG!

The 48 is the density in English units (lb/ ft3), which are inconsistent with the units of viscosity (cP). In the authors’ experience, mixing units in kinematic viscosity calculation has been the top cause of getting incorrect answers out of GPDC. What makes it worse is that the kinematic viscosity is raised to the power of 0.05 in the calculation (equation 1). The conversion factor between the English units of lb/ft3 and the CGS units of g/cm3 is 62.4. When 62.4 is raised to the 0.05, it produces an error of 23%, which makes a large difference to the final answer, yet the wrong answer makes sense, making the error difficult to identify.

Correct kinematic viscosity calculation:

Liquid density = 48 / 62.4 = 0.769 g/cm3

υ = 0.60 / 0.769 = 0.78 cS

4) Calculate the capacity parameter.

Chart 10.2503 gives a packing factor of 18 for # 1.5(M) Raschig Super-Ring ®. Eq. 1 gives

CP = 0.299 18 0.5 0.78 0.05 = 1.25

5) Calculate the flood point.

Chart 10.2503 does not contain flood data, so equation 4 is used to give ∆Pflood = 0.12 18 0.7 = 0.91 inch water/ft of packing

The flood capacity parameter is the ordinate at the flood pressure drop and at the flow parameter of 0.022, about 1.73. Therefore,

Percent flood = 1.25 x 100 / 1.73 = 72%

Therefore, the existing packing (# 1.5 (M) Raschig Super-Ring®) will comfortably achieve the retrofit flow rates.

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6) Calculate the pressure drop. Locate a point on the chart whose abscissa is the flow parameter (0.022) and whose ordinate is the capacity parameter (1.25). At that point, the pressure drop is about 0.35 inches of water per foot of packing. For a 20-ft bed, the total pressure drop is 0.35 x 20 = 7 inches of water.

7) Structured packing retrofit. For this calculation, steps 1-3 are as above. Step 4 to 6 need

to be recalculated based on charts 10.6904 and 10.6804.

Flexipac® 2Y HC ® Mellapak Plus® 252Y

Fp (Charts 10.6804 and 10.6904) 13 12

CP (Eq. 1) 1.065 1.023

Flood ∆P (Eq. 4) 0.72 0.68

Flood CP (from Flv & Flood ∆P) 1.62 (Note 2) 1.57 (Note 1)

% Flood 66% 65%

Actual pressure drop (from Flv, CP)

inch water / ft 0.25 (Note 2) 0.22 (Note 3)

Notes:

1) Here there are actual flood data, so there is no need to use equation 4. The flood point is a direct interpolation of flood data, so it is predicted with a high degree of confidence.

2) Here limited extrapolation is needed, but it is quite straight forward and involves low risk. 3) As per Note 1, here the data permit a high degree of confidence in the pressure drop prediction.

8) Comparing the pressure drop in Steps 6 and 7, the pressure drop reduction that can be

expected is 0.10 – 0.13 inches of water per ft of packing. This will save about 2 to 2.5 inch of water over the 20 ft bed.

This small pressure drop reduction is unlikely to be beneficial enough to justify the cost of a structured packing retrofit in this tower. However, if the structured packings can also offer a significant efficiency improvement, such a retrofit may be justified.

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EXAMPLE 2. IS IT IMPORTANT WHAT PACKING FACTOR IS USED?

Suppose that the packing factor in Example 1 was grossly excessive. Figure 3 shows a chart with a grossly excessive packing factor of 27 for the same packing as in Example 1 (the correct chart shows a packing factor of 18).

What impact would this have on the calculation?

SOLUTION

Steps 1 through 3 are the same as in Example 1. Steps 4 on are different and based on Figure 3. Figure 3 (a variation of Chart 10.2503 in which an excessive packing factor of 27 is used with the same data for # 1.5(M) Raschig Super-Ring ® that are on Chart 10.2503).

4) Calculate the capacity parameter.

Eq. 1 gives

CP = 0.299 27 0.5_0.780.05_{= 1.53}

5) Calculate the flood point.

Chart 10.2503 does not contain flood data, so equation 4 is used to give ∆Pflood = 0.12 27 0.7 = 1.21 inch water/ft of packing

The flood capacity parameter is the ordinate at the flood pressure drop and at the flow parameter of 0.022, about 2.27. Therefore,

Percent flood = 1.53 x 100 / 2.27 = 67%

So a packing factor increase of 50% changes the calculated flood point only by 7%. This change is entirely due to the effect of packing factor on the flood point per Eq. 4. The flood point would not have been impacted had flood data been present on the chart.

6) Calculate the pressure drop. Locate a point on the chart whose abscissa is the flow

parameter (0.022) and whose ordinate is the capacity parameter (1.53). At that point, the pressure drop is about 0.35 inches of water per foot of packing. For a 20-ft bed, the total pressure drop is 0.35 x 20 = 7 inches of water. This is the same as the value calculated with the correct packing factor of 18.

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No. 2 MISUSE

MIXING PACKING FACTORS FROM DIFFERENT SOURCES IS

WRONG!

GPDC interpolation charts are simple plots of measured C-factors against flow parameters at constant pressure drops. Due to the low power there is little impact of the kinematic viscosity. The packing factors play the sole role of moving the data points up or down relative to the curves, but what is being interpolated is the data, not the curves. For a given packing, the packing factor is simply a constant on the ordinate. As long as the packing factor used in the calculation is the same as that used in the chart (as in Examples 1 and 2 above), it plays no role in the pressure drop calculation. If Eq. 4 is used, the packing factor plays a small role in the flood calculation.

In preparing the charts, we took care to pick packing factors that move the data closest to the curves. This minimizes errors in the use of equation 4. For the pressure drop interpolation, the closer the data match the curves, the better the guide that the curves can provide for the interpolation. For the pressure drop interpolation, we could have picked any packing factor (within reason) and obtained the same pressure drop result as per Example 2 above.

EXAMPLE 3 - PRESSURE DROP CALCULATION BEYOND FLOOD

No. 3 MISUSE

PRESSURE DROP CALCULATION ABOVE THE FLOOD POINT IS

INVALID

!

The GPDC interpolation charts are excellent predictors of pressure drop when the column is unflooded. However, once flooded, the variation of pressure drop becomes totally unpredictable. Often, flood is accompanied by a sharp rise in pressure drop, yet in other cases packing flood occurs with no sharp change in pressure drop (28). So any attempt to predict pressure drop of a flooded tower is wrong.

Figure 4, based on reference 27, is a classic example of this misuse. For this packing (Flexipac® 2Y), there were quite a few flood data points plotted on the GPDC chart in the relevant region (10), measured by the Separation Research Program (SRP). Interpolation of these flood data would give a flood point vapor rate 9.5% higher than the experimental flood point, yet the calculation displayed on Figure 4 (27) extended to more than 30% above the measured flood point! The portion of the graph between 9.5% and 32% above the GPDC flood point is totally

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invalid.

The difference between the valid portion of the calculated curve and the experimental curve in Figure 4 is addressed in Example 4 below.

EXAMPLE 4 – GPDC INTERPOLATION CAN ONLY AS GOOD AS THE DATA IT INTERPOLATES

There is nothing magic about GPDC interpolation. The charts are simple plots of C-factors vs. flow parameters at constant pressure drops. As stated above, the kinematic viscosity and packing factors play minor, if any, roles. What is being interpolated is the measured data. Therefore, if GPDC interpolation starts giving unsatisfactory predictions, the data should be high up on the troubleshooting list.

The 1982 curve on Figure 5 shows a sample of the pressure drop data that were used to derive the GPDC chart for this packing (Flexipac® 2Y). These data were taken from the measurements obtained in a very extensive test program published by Koch Engineering (24) and used in their catalogues for over a decade (25). Recent Koch-Glitsch publications (21, 26) substituted the 1982 data by new data, some from the same test unit, showing significantly higher pressure drops for each packing from the same family. Figure 5 illustrates the differences. It is not clear why the pressure drop of these packings has risen in the last decade or so. However, it is clear that charts based on the 1982 data are too optimistic to predict the “best and latest” pressure drops measurement supported by the vendor for the same packings. The vendor’s quarterly newsletter correctly stated that the existing GPDC charts for the packing do not adequately reflect the new data (27). They cannot, they are based on the old data. For this reason, Charts 10.6102R1 through 10.6108R1 (R1 stands for Revision 1) in the Appendix are revised charts for the Flexipac® 1, 2, 3 and 4Y based on the revised data.

It is important to note that unlike the changed pressure drop calculation, the flood prediction of the same superseded GPDC interpolation chart for Flexipac® 2Y is quite close to the measured flood point (within 10%). This is because the flood point interpolation is based on measured flood point data by SRP that were not affected by the pressure drop data substitution.

It is therefore most important to be alert to data changes and reliability. Fortunately, data changes for a given packing do not happen too often.

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EXAMPLE 5. FLOOD OR NO FLOOD?

A refinery crude tower is 14-ft ID, but has a packed stripping section contained in a 5 ft ID cylinder (“can”). The packed bed is 10 ft tall. The plant is measuring a pressure drop of 13-20 inches water across the bed. Evaluation by others using proprietary software concluded that the bed should be operating at 87% of flood with a pressure drop of 8 inches of water. The vapor and liquid loading are highest at the top of the bed, and gradually diminish as one descends. At the bottom of the bed the vapor loads are about half those at the top. Operating conditions at the top of the bed are:

V = 77,000 lb/h ρ V = 0.45 lb/ft3

L = 580,000 lb/h ρL = 41 lb/ft3

L

µ = 3 cP

SOLUTION

1) The flow parameter is calculated by Eq. 3

Flv = 0.79 41 45 . 0 000 , 77 000 , 580 0.5 =      

2) The C-factor is calculated from Eq. 2

Tower area = ₅2 ₁₉_.₆₄ 2 4 = ft π Vapor velocity, US = 77,000 / (3600 0.45 19.64) = 2.42 ft/s CS = 2.42 0.255ft/s 45 . 0 41 45 . 0 ₌ − 3) Kinematic viscosity = 3 / (41 / 62.4) = 4.57 cS

4) Calculate the capacity parameter, based on a packing factor of 10 as shown in Figure 5.

CP = 0.255 4.57 0.05 10 0.5 = 0.87

5) A point with the abscissa of the flow parameter and the ordinate of the capacity

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tower falls in a region where the flow parameter is higher than the range at which data is available for this packing. Extrapolation is required, and uncertainty exists. It is quite possible that the vendor has little data in this zone, and any proprietary predictions are likely to be uncertain. The strength of the GPDC is that it does give this warning to the user whereas the proprietary program does not.

Fortunately, flood data (these were measured by the packing vendor) are available all the way to a flow parameter of 0.56, and from there to 0.79 the extrapolation only needs to travel a short path. Also, the flood data appear to trend well, and should give a

reasonable prediction, despite the uncertainty. The flood data extrapolate to a capacity parameter of about 0.8 at a flow parameter of 0.79. From this

% Flood = 100 x 0.87 / 0.8 = 109%

6) Unlike the proprietary method, the GPDC interpolation procedure predicted flooding at

the operating conditions. Considering that the high loads were only at the top of the bed, the entire pressure drop of unflooded packing in this service should have been less than 3-5 inches of water, as can be calculated from Figure 6 and integrated over the bed. The actual measured pressure drop was about 4 times higher.

7) In this case, the GPDC interpolation calculation also invalidated a revamp proposal with

a more open packing. While the proposal estimated that the new packing will operate at 88% of flood, the GPDC interpolation chart for the proposed packing showed that although the more open packing will satisfactorily handle current conditions, it will experience flooding at the revamp loads. On this basis, the stripping section cylinder (can) was replaced by a larger one, and trouble-free operation was re-instated.

EXAMPLE 6. Further to Example 4, would a retrofit with Flexipac® 3X permit current operation without flooding?

SOLUTION

1) The Flv, CS and kinematic viscosity are the same as in Example 4. For Flexipac® 3X, the

packing factor is much lower, at 5, so the capacity parameter is CP = 0.255 4.57 0.05 5 0.5 = 0.615

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A point (0.79, 0.619) is plotted on Chart 10.6156.

In the absence of flood data, eq. 4 is used for the flood pressure drop ∆Pflood = 0.12 5 0.7 = 0.37 inch water / ft.

The closest data points for this pressure drop are at flow parameters of 0.3 – 0.4, much lower than the 0.79 in the tower. The operating point is well outside the available data range for Flexipac® 3X. This interpolation chart is therefore unable to tell where the flood point is at a flow parameter of 0.79. Therefore, the interpolation chart cannot tell whether Flexipac® 3X will permit operation without flooding at the current loads.

No. 4 MISUSE

EXTRAPOLATION TO DATA-LEAN REGIONS

Any extrapolation must be performed with good engineering judgment. In Example 5, the extrapolation was to a close-by region, there were well-defined flood data, and the data trends were clear. Although there was some uncertainty, extrapolation here could be expected to yield a reasonable estimate.

The converse occurred with Example 6. Here there were no flood data, the operating point was quite far from the pressure drop data points, and the data trends were not completely clear at the higher flow parameter. Under these circumstances, extrapolation will be unreliable and must be avoided.

EXAMPLE 7. This example presents a number of experiences in which vendor and simulator predictions for a packed tower were optimistic. In each one of these, the Kister and Gill equation (eq. 4) gave excellent prediction for the maximum capacity.

TOWER A This chemical tower, equipped with wire-mesh structured packing with a packing factor of 21, ran completely smoothly until reaching a pressure drop of 1 inch of water per foot of packing. It would then rapidly lose efficiency, exactly as predicted from equation 4.

Simulation prediction (both vendor and general options) predicted a much higher capacity.

TOWER B This chemical tower, equipped with random packing with a packing factor of 18, would rapidly lose efficiency when the pressure drop increased above 0.67 inch of water per foot of packing. This compares to a flood pressure drop of 0.9 from equation 4. The measurement

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was slightly lower than the prediction because the vapor load was high only near the top of the packings, so much of the bed operated at lower pressure drop. Simulation prediction (various options) predicted a much higher capacity. The plant initially theorized that the shortfall in capacity was due to vapor maldistribution.

TOWER C This chemical absorber was equipped with random packing with a packing factor of 18. The highest pressure drop at which operation was stable was 0.8 inch of water per foot of packing. Above this, the pressure drop would rapidly rise. This compares to a flood pressure drop of 0.9 from equation 4. Simulation predictions (both vendor and general options) were of a 20 percent higher capacity.

TOWER D Random packing installed in a chemical tower fell short of achieving design capacity. The vendor method predicted flooding at a pressure drop of 1.5 inch of water per foot of packing. With a packing factor of 18, equation 4 predicted that the packing would flood significantly earlier, at a pressure drop of 0.9 inches of water per foot of packing. The packing flooded exactly at that pressure drop.

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Nomenclature

AT Tower cross section area, ft2

CS C-factor based on tower superficial velocity, defined by Eq. 2, ft/s

CP Capacity parameter, defined by Eq. 1

Flv Flow parameter, defined by Eq. 3

FP Packing factor, characteristic of packing geometry, ft-1

∆P Pressure drop, inch water/ft of packing

G Gas mass flow rate, lb/h ft2

L Liquid mass flow rate, lb/h ft2

US Superficial vapor velocity, ft/s

Greek Letters

ρ Density, lb/ ft3

L

µ Liquid viscosity

υ Kinematic viscosity, centistokes

Subscripts

Fl At flood

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References

1. Sherwood, T. K., G. H. Shipley, and F. A. L. Holloway, Ind. Eng. Chem. 30(7), p. 765, 1938.

2. Lobo, W. E., L. Friend, F. Hashmall, and F. A. Zenz, Trans. Am. Inst. Chem. Engrs. 41, p.

693, 1945.

3. Leva, M., Chem. Eng. Prog. Symp. Ser. 50(10), p. 51, 1954.

4. Copigneaux, P., Hydrocarb. Proc. 60(2), p. 99, 1981.

5. Eckert, J. S., Chem. Eng. Prog. 59(5), p. 76, 1963.

6. Eckert, J. S., Chem. Eng. Prog., 66(3), p. 39, 1970.

7. Eckert, J. S., Chem. Eng., p. 70, April 14, 1975.

8. Strigle, R. F., Jr., “Packed Tower Design and Applications”, 2nd Ed., Gulf Publishing,

Houston, TX , 1994 (1st Ed. was in 1987).

9. Perry, R. H., and D. Green, “Chemical Engineers’ Handbook”, 8th Ed., McGraw-Hill, NY, to

be published in 2007.

10.Kister, H. Z., “Distillation Design”, McGraw-Hill, NY, 1992.

11.Kister, H. Z., and D. R. Gill, IChemE Symp. Ser. 128, p. A109, 1992.

12.Souders, M. Jr., and G. G. Brown, Ind. Eng. Chem. 26(1), p. 98, 1934.

13.Kister, H. Z., and D. R. Gill, “Predict Flood Points and Pressure Drop for Modern Random

Packings” Chem. Eng. Prog., 87(2), p. 32, 1991.

14.Robbins, L. A., Chem. Eng. Prog., May, p. 87, 1991.

15.Zenz, F. A., Chem. Eng., August, p. 176, 1953.

16.Strigle, R. F., Jr., and F. Rukovena, Jr., Chem. Eng. Progr. 75(3), p. 86, 1979.

17.Maćkowiak, J., Fluiddynamik von Kolonnen mit Modernen Fullkörpern und Packungen für

Gas/Flüssigkeitssysteme, Otto Salle Verlag, Frankfurt am Main, und Verlag Sauerländer, Aarau, Frankfurt am Main, 1991.

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18.Kister, H. Z., K. F. Larson, and D. R. Gill “More Interpolation Charts for Predicting Packing Flood and Pressure Drop”, presented at the AIChE Spring National Meeting, Houston, Texas, March 19-23, 1995.

19.Lockett, M. J., R. A. Victor, and J. F. Billingham, “Structured Packing Flooding: Its

Measurement and Prediction”, IChemE Symp. Ser. 152, p. 400, 2006.

20.Pilling, M. and Haas, Distillation Topical Conference Proceedings, p. 132, AIChE Spring

Meeting, March 10-14, New Orleans, LA, 2002.

21.McNulty, K. and R. A. Sommerfeldt, “New Twist Adds Capacity to Flexipac® Structured

Packings”, in “Distillation: Horizons for the New Millennium”, Topical Conference Proceedings, p. 89, AIChE Spring Meeting, Houston, TX, March 1999.

22.Schultes, M., and S. Chamber “How to Surpass Conventional and High Capacity Structured

Packings with Raschig Super-Pak”, Chem. Eng. Res. And Des., Vol. 85, No. A1, p. 118, January 2007.

23.Olujic, Z., A. F. Seibert, B. Kaibel, H. Jansen, T. Rietfort, and E. Zich, Chem. Eng. & Proc.,

42, 55-60, 2003.

24.McNulty, K. and C. L. Hsieh, “Hydraulic Performance and Efficiency of Koch Flexipac®

Structured Packings”, paper presented at the 1982 Annual Meeting of the AIChE, Los Angeles, CA., Nov 14-19, 1982.

25.Koch Engineering Company Inc., “Flexipac® Structured Packing”, Bulletin KFP-3, Wichita,

Kansas, 1989.

26.Koch-Glitsch LP, Bulletin, “Flexipac® Structured Packing”, Bulletin KFP-5, Wichita,

Kansas, 1997.

27.Koch-Glitsch “KG-TOWER® - Reliability Predicting Packed Tower Pressure Capacity and

Pressure Drop”, Wichita, Kansas, 4th Quarter, 2006.

28.Kister, H. Z., “Distillation Troubleshooting” John Wiley and Sons, Inc, NJ, 2006.

29.Cooling, M., and M. Neuman, “Hyperfil Knitted Mesh Tower Packing – A High efficiency

Leader for the Future”, in “Distillation 2005: Learning from the Past and Advancing the Future”, Topical Conference Proceedings, p. 389, AIChE Spring Meeting, Atlanta, GA, April 10 – 13, 2005.

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FIGURE 2

KISTER & GILL'S GPDC (SP) FOR

STRUCTURED PACKING

2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0

FLOW PARAMETER

C

A

PA

CITY PA

RA

METE

R

LEGEND DATA POINTS

∆P curves from top to bottom represent 1.5, 1.0, 0.50, 0.25, 0.10 inches H2O/ft

Symbol ∆P, inches H2O/ft Symbol

1.5 1.0 0.5 0.25 0.10

*

FLOOD MOC

(23)

FIGURE 3

GPDC CHART FOR THE SAME PACKING AS CHART 10.2503,

BUT WITH A GROSSLY EXCESSIVE PACKING FACTOR

0.005 0.01 0.05 0.10 0.50 1.00 5.00 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0

FLOW PARAMETER

CAPACITY PARAME

T

E

R

Basis: Fp = 27

Pressure drop measured in inches H2O/ft

Large symbols represent non-aqueous data

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol

1.5 1.0 0.5 0.25 0.10

*

FLOOD MOC

(24)

FIGURE 4

INCORRECT APPLICATION OF GPDC

BEYOND THE FLOOD POINT

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 0.50 0.60 0.70 0.80 0.90 1.00 1.10 1.20 1.30 1.40

FRACTION OF MEASURED FLOOD

PRESSURE DRO

P

(inches H2O/ft)

GPDC

Vendor New Test Data

GPDC FLOOD POINT

(25)

FLEXIPAC

®

1Y Metal Structured Packing

Pressure Drop vs. C-Factor

Air-Water, 10 gpm/ft

2

, KOCH/KOCH GLITSCH Data

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 0 0.1 0.2 0.3 0.4 Cs, ft/sec

∆

P,in

ch

es

H

2

O/

ft

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 ∆ P,inches H 2 O/ft

McNulty & Hsieh

McNutly & Sommesfeldt

(26)

FLEXIPAC

®

2Y Metal Structured Packing

Pressure Drop vs. C-Factor

Air-Water, 10 gpm/ft

2

, KOCH/KOCH GLITSCH Data

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 0.1 0.2 0.3 0.4 0.5

Cs, ft/sec

∆

P,in

ch

es

H

2

O/ft

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60

∆

P,inches H

2

O/

ft

McNulty & Hsieh KFP-5

(27)

(28)

(29)

TABLE 1 DATA USED IN CHARTS

Test Column Chart Packing FP FP Source (ref. number) Data Source

(ref. number) System Pressure

Flow Parameter Dia. In Packed Ht. Feet No. of Data Points

10.2502 #1 (M) Raschig Super-Ring® 25 This work A1 (Ruhr Uni, Bochum) Air – Water Atm 0.05 – 1.2 17 6.6 29 A2 (Ruhr Uni, Bochum) Air – Water Atm 0.04 – 0.35 11 6.4 17 10.2503 #1.5 (M) Raschig Super-Ring® 18 This work A1 (Ruhr Uni,, Bochum) Air – Water Atm 0.02 – 0.28 11 6.6 20

10.2504 #2 (M) Raschig Super-Ring® 15 This work A1 (Ruhr Uni, Bochum) Air – Water Atm 0.05 – 1.7 30 9.8 39 A3 (Raschig) Air – Water Atm 0.02 – 0.24 11 4.6 16

A1 (FRI) C6 – C7 24 psia 0.09 48 12 5

A1 (FRI) iC4 – nC4 100 psia 0.18 48 12 4

A1 (FRI) iC4 – nC4 165 psia 0.24 48 12 4

10.2506 #3 (M) Raschig Super-Ring® 11 This work A1 (Ruhr Uni, Bochum) Air – Water Atm 0.02 – 0.81 17 6.6 32

10.2514 #2 (P) Raschig Super-Ring® 15 This work A1 (Ruhr Uni, Bochum) Air – Water Atm 0.02 – 0.23 11 6.6 20

10.6102R1 Flexipac® 1Y 30 This work A4 (Koch-Glitsch) Air – Water Atm 0.041 – 0.95 36 20

A5 (Koch) Air – Water Atm 0.10, 0.29 36 2 2

10.6103 Flexipac® 1.6Y 18 This work A6 (Koch-Glitsch) Air – Water Atm 0.03 – 0.58 36 20

10.6104R1 Flexipac® 2Y 15 This work A6 (Koch-Glitsch) Air – Water Atm 0.03 – 0.49 36 20 A5 (Koch) Air – Water Atm 0.067, 0.15 36 2 2

A7 (SRP) C6 – C7 5 – 60 psia 0.04 – 0.15 18 10 3

A5 (Koch) Air – Water Atm 0.05 – 0.19 36 3 3

10.6152 Flexipac® 1 16 This work A6 (Koch-Glitsch) Air – Water Atm 0.033 – 0.52 36 20 10.6153 Flexipac® 1.6X 10 This work A6 (Koch-Glitsch) Air – Water Atm 0.024 – 0.44 36 20

10.6154 Flexipac® 2X 7 This work A6 (Koch-Glitsch) Air – Water Atm 0.020 – 0.32 36 20

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TABLE 1 DATA USED IN CHARTS

Test Column Chart Packing FP FP Source (ref. number) Data Source

(ref. number) System Pressure

Flow Parameter Dia. In Packed Ht. Feet No. of Data Points 10.6801 Mellapak Plus® 752Y 40 This work A8 (Sulzer) Chlorobenzene – Ethylbenzene 100-960 mbar 0.020 – 0.060 39 18

10.6802 Mellapak Plux® 452Y 21 This work A8 (Sulzer) Chlorobenzene – Ethylbenzene 100-960 mbar 0.020 – 0.060 39 16

10.6804 Mellapak Plus® 252Y 12 This work A8 (Sulzer) Chlorobenzene – Ethylbenzene 100-960 mbar 0.020 – 0.060 39 18 A9 (FRI) p-o Xylene 100 mmHg 0.022 48 7

A9 (FRI) C6 – C7 5, 24 psia 0.041, 0.087 48 14

10.6901 Flexipac® HC® 700Y 68 This work A10 (Koch-Glitsch) Air – Water Atm 0.015 – 0.66 36 33

10.6902 Flexipac® HC® 1Y 25 This work A4, A10 (Koch-Glitsch) Air – Water Atm 0.03 – 0.93 36 20 10.6903 Flexipac® HC® 1.6Y 17 This work A11 (Koch-Glitsch) p-o Xylene 75,200 mmHg 0.022 – 0.35 16 10 10 A11 (FRI) p-o Xylene 75,175 mmHg 0.022 – 0.032 48 11.4 10

10.6904 Flexipac® HC® 2Y 13 A10 (Koch-Glitsch) Air – Water Atm 0.020 – 0.75 36 20 10.7104 Montz B1-250M® 13 This work A12 (Montz) Air – Water Atm 0.006 – 0.71 18

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Data References

A1 Schultes, M. “Raschig Super-Ring A New Fourth Generation Packing”, in “Distillation 2001: Frontiers in a New Millennium”, Topical Conference Proceedings, p. 498, AIChE Spring National Meeting, Houston, Texas, 2001. A2 Schultes, M. “A Modern Packing Gives Excellent Performance Data”, in

“Separation Science and Technologies”, Preprints of the Topical Conference, p. 63, The AIChE Annual Meeting, Los Angeles, CA., Nov 17-19, 1997.

A3 Raschig AG “Raschig – Super-Ring®” VR-5900-500-III/1996-ST, Ludwigshafen, Germany.

A4 McNulty, K. and R. A. Sommerfeldt, “New Twist Adds Capacity to Flexipac® Structured Packings”, in “Distillation: Horizons for the New Millennium”, Topical Conference Proceedings, p. 89, AIChE Spring Meeting, Houston, TX, March 1999.

A5 McNulty, K. and C. L. Hsieh, “Hydraulic Performance and Efficiency of Koch Flexipac® Structured Packings”, paper presented at the 1982 Annual Meeting of the AIChE, Los Angeles, CA., Nov 14-19, 1982.

A6 Koch-Glitsch “Flexipac® Structured Packing”, Bulletin KFP-5, Wichita, KS., 1997.

A7 Fair, J. R. and J. L. Bravo, Chem. Eng. Progr.. 86(1), p. 19, 1990.

A8 Sulzer ChemTech “Structured Packings for Distillation and Absorption”, Winterthur, Switzerland

A9 Pilling, M., and L. Spiegel “Design Characteristics and Test Validation of High-Performance Structured Packing”, paper presented at the AIChE Fall Meeting, Distillation Symposium Honoring John Kunesh, Reno, Nevada, November 2001.

A10 Koch-Glitsch “Structured Packing Flexipac® HC®”, www.koch-glitsch.com/koch/products/fleixpac_hc.asp, 4/5/2007.

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A11 Hausch, G. W., R. Sommerfeldt, and I. Nieuwoudt “Advances in Styrene Fractionation with INTALOX PACKED TOWER SYSTEMS® Technology, Part 2 - Flexipac® HC® Structured Packing”, in “Distillation 2005: Learning from the Past and Advancing the Future”, p. 401, Topical Conference Proceedings, AIChE Spring National Meeting, Atlanta, GA., April 10-13, 2005.

A12 Julius Montz, GmbH, “Montz-Pack Type B1-350M”, and “Montz-Pak Type B1-250M”, www.montz.de/pics/service/download.htm # Type M, Hilden, Germany, 4/11/2007.

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CHART 10.2502 #1 (M) RASCHIG SUPER-RING® PRESSURE DROP 5.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CIT Y P A R A M E T E R Basis: Fp = 25

Pressure drop measured in inches H2O/ft Large symbols represent non-aqueous data

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.2503 #1.5 (M) RASCHIG SUPER-RING® PRESSURE DROP 5.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CIT Y P A R A M E T E R Basis: Fp = 18

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC

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CHART 10.2504

#2 (M) RASCHIG SUPER-RING®

FLOOD & PRESSURE DROP

5.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 15

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.2506 #3 (M) RASCHIG SUPER-RING® PRESSURE DROP 5.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CIT Y P A R A M E T E R Basis: Fp = 11

LEGEND

DATA POINTS

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CHART 10.2514 #2 (P) RASCHIG SUPER-RING® PRESSURE DROP 5.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CIT Y P A R A M E T E R Basis: Fp = 15

LEGEND

DATA POINTS

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CHART 10.6102R1

FLEXIPAC® 1Y

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6103 FLEXIPAC® 1.6Y PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 18

LEGEND

DATA POINTS

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CHART 10.6104R1

FLEXIPAC® 2Y

0.005 0.01 0.05 0.10 0.50 1.00 2.00 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CAPA C ITY PA RAMETE R Basis: Fp = 15

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6106R1 FLEXIPAC® 3Y

0.005 0.01 0.05 0.10 0.50 1.00 2.00 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CAPA C ITY PA RAMETE R Basis: Fp = 9

LEGEND

DATA POINTS

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CHART 10.6108R1 FLEXIPAC® 4Y PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 7

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6152 FLEXIPAC® 1X PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 16

LEGEND

DATA POINTS

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CHART 10.6153 FLEXIPAC® 1.6X PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 10

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6154 FLEXIPAC® 2X PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 7

LEGEND

DATA POINTS

(40)

CHART 10.6156 FLEXIPAC® 3X PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 5

LEGEND

DATA POINTS

(41)

CHART 10.6801

MELLAPAK PLUS® 752Y

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6802

LEGEND

DATA POINTS

(42)

CHART 10.6804

LEGEND

DATA POINTS

(43)

CHART 10.6901

FLEXIPAC® HC® 700

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6902 FLEXIPAC® HC® 1Y PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 25

LEGEND

DATA POINTS

(44)

CHART 10.6903

FLEXIPAC® HC® 1.6Y

LEGEND

DATA POINTS

Symbol ∆P, inches H2O/ft Symbol 1.5 1.0 0.5 0.25 0.10 * FLOODMOC CHART 10.6904 FLEXIPAC® HC® 2Y PRESSURE DROP 2.00 1.00 0.50 0.10 0.05 0.01 0.005 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 2.6 2.8 3.0 FLOW PARAMETER CA P A CI T Y P A RA M E T E R Basis: Fp = 13

LEGEND

DATA POINTS

(45)

CHART 10.7104

MONTZ® B1-250M®

LEGEND

DATA POINTS