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How to Process Distillation Test Data

Here we will explain you how we make our comparisons with distillation test data with mass transfer coefficient (MTC) correlations in ChemSep. We'll use data on Sulzer BX packing as an example. It was published in an article in Chemical Engineering Progress of January 1998 (p.60), by Mike Lockett. The data originated from the Fractionation Research Institute FRI. In the article Lockett also compared the data with the mass transfer model of Bravo, Rocha, and Fair (Hydrocarbon Processing, January 1985, p. 91), which we abbreviate with BRF85.

The process consists of two steps:

How to Extract and Plot Experimental Data
How to Compare MTC predictions with Distillation Test Data

For making the plots you can use either ChemSep LITE or the full version of ChemSep, but for making comparisons of HETP's from simulations with MTC models you will need either the CACHE or the full version of ChemSep that includes the nonequilibrium simulator.

How to Extract and Plot Experimental Data

Lockett's article features "measured" HETP's which are plotted as a function of the packing F-factor, at four different pressures, in his figure 1. It is important to note that these HETP's are not measured as such but they are computed by simulating the distillation tests with an equilibrium stage simulator while matching measured bottoms and tops compositions. To get a good match one stage is to be taken to have a fractional stage efficiency (between 0 and 1). The HETP is then resulting from the bed height divided by the number of stages in the simulation (of course, excluding condenser and reboiler. If the vapor velocity in the bed changes it is important to use the location with the highest flows for computing the F-factor. For the example here we will use a scan for Lockett's plot of HETP's for the o/p-Xylene system at 1 atmosphere, Figure 1a.

We could read the values from this graph by hand but to get a little more precise numbers we use the tool ScanIt to obtain the datapoints. ScanIt lets you pick the origin and two axis end points of the Figure to determine the scale of the scan. After this you can select each point with the mouse and ScanIt will mark it and compute the x,y values of the original datapoint.

Using ScanIt to obtain the data points in the Figure.

With the "Copy data" button we can copy the data to the clipboard. We open a Notepad text editing window and paste the data in there. We also add some descriptions in this file:

# fullref=   Chemical Engineering Progress, January 1998, p. 60, Fig. 1a
# author=    Michael J. Lockett
# title=     Easily predict structured-packing HETP
# url=       http://www.aiche.org/CEP/Issues/1998-01/
# fileref=   cep/cep1998-01p60.pdf
# subref=    fig1a
# type=      structured
# vendor=    Sulzer
# name=      BX
# system=    xylenes
# pressure=  96 [kPa]
# location=  FRI
# diameter=  1.22 [m]
# bedheight= 3 [m]
# xbot_ave=  0.3
# data_y=    ave.HETP [m]
# data_x=    F-factor [(Pa.s)^0.5]
# data_type= experiments
# copyleft=  Harry Kooijman, ChemSep.org

this basically gives a complete reference to the article. If possible, we refer to the publishers URL of the paper. Note that this is not always possible, as in this case, as CEP does not have an electronic versions of their older publications. In this case we make a link in the same way as it works for the current publication of the journal. Important to realize is that any datalines starting with a "#" is not a data line. All these entries are providing meta information about the data that follows. Does the data represent experimental values or model predictions? What was measured as a function of what, in what units? What chemical system was used, at what pressure, and in how large a column? What was the (average) molefraction in the bottom of the column of the more volatile compound?

We can add a title and a label with:

# plottitle=Sulzer BX o/p-Xylene 730 Torr @ FRI (1.22m ID) CEPjan1998p60fig1a
# plotstage=Vertical
# plotcommands=set label "ChemSep" at 3,0.3 right

The title gives packing type, test system and pressure, column ID, and reference. The label is just an example of text which is right alligned. There is also another ways of making labels, as we will see later. We can now also define the X- and Y-axis with

# x1-title=F-factor
# x1-start=0
# x1-end=3
# x1-ticint=1
# x1-stics=4
# x1-log=Off
# y1-title=Average HETP (m)
# y1-start=0
# y1-end=0.3
# y1-ticint=0.05
# y1-stics=4
# y1-log=Off

Note that ChemSep can draw 4 axii, and that the default x- and y-axis are x1 and y1. This is the notation used by GNUplot, the tool ChemSep uses to make its plots.

To make define the color and style of the datapoints we can use:

# label= exp.
# x-axis=1
# y-axis=1
# x-units=
# y-units=
# color=1
# style=1
# thick=1
# point=6
# flipp=0

which defines the datapoints as red filled circles labeled as "experimental" points. Next we paste the content of the buffer with the data collected by ScanIt:

0.242 0.145
0.306 0.0955
0.345 0.1
0.385 0.115
0.398 0.168
0.444 0.126
0.512 0.126
0.581 0.155
0.659 0.158
0.707 0.155
0.765 0.15
0.825 0.172
0.97 0.178
0.989 0.163
1.12 0.219
1.15 0.173
1.26 0.176
1.3 0.176
1.45 0.199
1.45 0.229
1.45 0.183
1.52 0.175
1.55 0.188
1.78 0.191
1.87 0.206
2.03 0.216
2.13 0.219
2.22 0.222
2.41 0.194

We save this as a text file with a descriptive name, for example Structured/Sulzer/BX/cep1998janp60Fig1a.txt . We chose a naming that is a reference using an abbreviated journal name, followed by the volume number, a small "p" for page, and then the page number. This usually generates an unique name. When the journal does not use volume numbers but year and month instead, we use those, with the month as three small letters. For conferences we use an abreviated conference name, year, and a session number or a page number of the proceedings.

The resulting text file can directly be plotted with ChemSep using the "Plot data file" menu-item under Analysis. The plot can be made to ave the same axii as it was originally published with as well as labels in the plot. When multiple experimental data sets are shown in one graph it is better to separate them into separate files and call them for example fig1a, fig1b, fig1c etc. This will allow them to be used separately in model comparison studies as we will see below. You can always combine them into one figure by adding another text file, for example as "fig1", by appended the files into that file. Make sure you give each set a different label and color/point-type so that they remain distinguable! Our example will look like:

Showing the distillation test data with the "Plot data file".

How to Compare MTC predictions with Distillation Test Data

To make this comparison you need to setup a simulation of the distillation tests in ChemSep for the system in question. We like to use the same filename as the dataset and add to it the model name (abbreviation), for example for the BRF85 model Structured/Sulzer/BX/cep1998janp60Fig1a_BRF85.sep . The easiest way to get this done is by searching our online database for a simulation (sep) file with the same distillation test mixture (and pressure) and adapt it for the right packing, bed height, and MTC model.

Setting up the o/p-xylene simulation with the BRF'85 MTC model.

When we have a converged simulation and verified it is correct we need to simulate it at various flow rates. For this we use parametric study option (under "Analysis") in ChemSep. We vary the reflux flow to the column to simulate the tests at different vapor loadings. You might need to play a little with the liquid reflux rates to obtain the right range for the test data. Note that we chose to plot the average HETP, by using AHETP1. This computes an average HETP over the whole bed of section number 1. We plotted it as function of the F-factor on stage 35, which resides in the middle of our bed.

Using Parametetric Study to simulate the column at different vapor loadings (and hence F factors) and calculating the average HETP.

Then plot the data points again with the "Plot data file" menu item and switch on the "Graph settings". This will allow you to add a data-set wth the "Add set" button. Here we plot the second and third column in the Parametric Study, by using the identifiers PS2 and PS3, on axii x1 and y1 for the 6 points generated in the Parametric Study (adapt this if you use a different number and indices for the variables).

Use "graph settings" to add the BRF'85 prediction next to the experimental data.

When we now click the "Display" button we obtain the experimental HETP and the model predicted HETP in one graph. We see that there is quite a good agreement with Lockett's publicated model predictions for the BRF'85 model. Deviations stem from using the average HETP, different physical properties and the use of a full nonequilibrium model. It is important that we use a sufficient number of stages to integrate the packed bed and the correct flow models are chosen in the simulation, of course.

The BRF'85 prediction with the FRI experimental data for Sulzer BX packing with o/p-Xyelene at 1 atm shows a good agreement.

To compare varous MTC models we need to be able to also compute the standard deviations in this plot. It would also be nice if we can visualize the model deviations. We can! Simply click the "Calc Dev's" button and these deviations will be computed for all data points. Note that the range of the parametric study must be large enough for this to work. ChemSep uses rational inter- and extra-polation to compute the model HETP's for each data point. The overall standard deviation in HETP and relative HETP is also added as label to the graph. This is all written to a new data file which includes the deviations as individual line pieces, and ChemSep asks you to specify a new name for this file. Typicaly we append a digit for the text file, for example: Structured/Sulzer/BX/cep1998janp60Fig1a1.txt . When you inspect this file you see also that ChemSep appends a label with the deviation and the relative error:

# string 0 0.3 s=0.024 r=0.143 b=+0.012

This allows you to further add other labels to the graph. The label may contain spaces but special characters might not print properly.

The BRF'85 model shows a relative standard deviation of 14 per cent or 24mm on an HETP that increases from 120mm at low vapor loadings to 200mm at high vapor loadings. Note that the bias is positive (+12mm), meaning that the BRF'85 model is 7 per cent optimistic in its prediction of the HETP!

We are now ready to compare the results for different models and select the best MTC model for this packing (and distillation system). We welcome anybody to contribute to our online database of distillation tests. We try to cover all industrially relevant packings. Obviously, this only works if the vendor makes its test data available or someone publishes measured distillation tests on the packings.

This page is under construction. Submissions are welcome.