California State Polytechnic University, Pomona
Chemical & Materials Engineering
CHE 333L
TRANSPORT LABORATORY II
LABORATORY GUIDE
This manual was prepared from the materials and
information provided by the Cal Poly Pomona
Chemical Engineering Faculty and Staff
Revised December, 2009 by K.H. Pang
TABLE OF CONTENTS
Pre-Laboratory Preparation
Laboratory Rules
Make the Most Out of Your Time in the Laboratory
Collection and Analysis of Experimental Data
Error Analysis of Experimental Data
Linear Regression and Matrix Algebra
Laboratory Notebook
Laboratory Report
Page
3
3
4
5
9
11
16
17
Oral Presentation
23
EXPERIMENTS
Experiment #1 – Gas Absorption Column, Pressure Drop
25
Experiment #2 - Extended Surface Heat Transfer
29
Heat Transfer Along a Cylindrical Fin
Experiment #3 - Gas Membrane Separation
35
Experiment #4 - Double Pipe Heat Exchanger
42
Experiment #5 – Boiling Heat Transfer
47
Experiment #6 – Unsteady State Heat Transfer
54
Experiment #7 – Batch Reactor
58
Appendix A – Newton’s Method for Systems of Nonlinear Algebraic Equations
63
Appendix B – Temperature Measurements with Labview
68
Appendix C – DAC Express Operation Procedure
74
-1-
PARTICIPATION IN CHEMICAL ENGINEERING LABORATORY
The Chemical Engineering Laboratory course has been set up as an open-ended learning
experience rather than the traditional data sheet oriented laboratories you may have had
in other courses. You will normally receive assignments in the form of memos, and you
are expected to respond with reports as might be written if you were working in industry.
Pre-Lab Preparation
Each laboratory experiment has a well-defined objective. This objective will be
represented by a numerical value, or a correlation allowing the calculation of this value,
for the unit operation under study. This objective is accomplished through data taking,
reduction, and analysis. The student should know the desired result before the
experiment is undertaken. Otherwise insufficient data may be taken, the results may be
incorrectly analyzed, or preposterous results may be reported.
Read your current assignment. Familiarize yourself with the theory relevant to the
experiment and the equipment necessary to take the required data. Read the appropriate
sections of your textbook and references. When you are sure you understand the problem,
prepare in writing, a Pre-Lab Plan. This exercise is intended to provide the preparation
necessary to undertake a successful experimental study.
The written plan should include a sketch of the experimental equipment, showing vessels,
interconnecting piping, valves, and relevant instrumentation. Make sure you understand
the purpose and safe operation of each of these equipment items before you start the
experiment. The correct analysis of data, its accuracy, and correction for nonstandard
operating conditions all require a thorough understanding of the instrumentation. The
written plan should discuss the independent and dependent variables and how and over
what range these independent variables will be measured (experimental grid)
The plan should address the experimental procedure and the sequence of operations
undertaken during the experiment. The plan should describe how the data would be
correlated, based on what models and which literature information. This pre-lab must be
completed before coming to lab. Bring the completed plan to the lab and have the
instructor approve your work before undertaking any experimental work. Include the
exercise as an appendix in your laboratory report.
Laboratory Rules
Attendance: All students are to report to the lab at the start of the period. Attendance
in all sessions for the full 2 hours 50 minutes of each period is required, unless you are
excused by the instructor. Unauthorized absences for part or all of any laboratory session
will result in a reduced course grade. Normally work will be performed in the lab. Work
in another area requires prior approval by the instructor.
Appropriate Clothing and Footwear: Good safety practices must be observed at all times
in the laboratory. This practice includes the wearing of proper clothing, footwear, and eye
-2-
protection. Wear shoes that cover the feet. Long pants are required. No sleeveless shirts
or tank tops are permitted. Long sleeve shirts are preferred. Do not wear a hat. Do not
wear long flowing clothes (that includes a tie). Long, loose hair must be restrained.
Safety Glasses must be worn in the laboratory at all times for those sessions in which
experiments are being performed. A face shield and gloves must be worn when required.
Good Housekeeping. All equipment must be safely operated and all chemicals must be
safely handled. Broken or damaged equipment should be reported to the instructor
immediately. You are reminded that all equipment is to be cleaned and returned to its
proper location after you finish the day's work. A clean laboratory is the responsibility of
all group members. Do not leave the lab until it is clean. Refer to “Laboratory Safety
Rules”
Safety Test
Each student must pass a safety test during week 1
Making the most out of your time in the lab
- Good experimental work demands that data and runs be replicated. Since we
cannot duplicate all conditions exactly, we make replicate runs, meaning that the
conditions are almost the same but not necessarily identical. Not only should individual
data be replicated (for instance a second, third, and fourth measurement of a flow rate)
but also the whole run (something from which you can calculate an experimental result)
should be replicated.
- When first doing a new experiment, try different things and become familiar
with the experiment and the equipment. Then determine the widest possible ranges of the
independent variables. In almost all cases you will want to take data over wide ranges of
the independent variables. If the independent variables can easily be changed over a wide
range, it is often good practice to conduct the first three experimental runs at the lowest,
intermediate, and highest levels of the independent variable.
- Summarize and record in your laboratory notebook the information obtained
from automatic data collection (by computer, by recorder, or whatever) as soon as
possible.
- Get in the habit of working up your data as you go. Sometimes you can plot
preliminary data to see trends. Other times you can calculate the experimental values and
see if you are in the ballpark.
- In almost all cases you will be able to compare experimental calculations with
theoretical and/or correlated values. In presenting your data and comparisons plan to use
graphs if at all possible. If you are using tables, aim to make them concise, clear, and
informative.
-3-
- Acquire the habit of clearly identifying your experimental runs. Run 1, then 2,
then 3 is appropriate. Or you can use letters; A. B. C. etc. If a run is a failure (this
sometimes happens) the next run is still given a new number or letter.
- Most of the reference books listed for the experiments, as well as other
reference books, will be available for perusal during the laboratory period.
Collection and Analysis of Experimental Data
The fundamental basis for a good laboratory report is data collection and record
keeping. It is not uncommon that a considerable amount of time elapses between the
data collection phase of an experiment and the eventual presentation of the results. The
data, therefore, must be well defined and recorded accurately in a permanent bound
laboratory notebook. An important requirement is that the notebook, “should be so clear
and complete that any intelligent person familiar with the field to which it relates but
unfamiliar with the specific investigation could, from the notebook alone, write a
satisfactory report on the experimental work”1, 2.
1. Always use your data as you are taking it to make sample calculations of your results,
dimensioning all numbers with their correct units. This simple step will insure that all
the information is being recorded that will be necessary for you to make subsequent
calculations for the report. Graph your results, with units, as the experiment
progresses, not after you have taken all the data. Graph your data in the same way you
intend to present it in your report, although it is not always necessary to make all unit
conversions for an initial plot done in the lab. This plot may then be used to
determine if the current experimental conditions are in the desired range, if the
equipment is being incorrectly operated or is not functioning properly, or if the degree
of experimental scatter is unacceptable. The plot may also be used to determine
experimental conditions for subsequent data points. More data should be taken under
conditions where the dependent variable changes more rapidly and less where the
changes are smaller. The independent variable(s) should be changed sufficiently to
make noticeable changes in the dependent variable.
1
2
Rhodes, F. H., “Technical Report Writing”, Mc Graw-Hill.
Hanesian, D. and Perna A. J., “A Laboratory Manual for Fundamentals of Engineering Design”, NJIT.
-4-
Example:
Pressure
drop P,
Inches of
water
point of fluidization
Log Re
Figure 1. Pressure drop in a bed of particulate solids.
Data can be collected evenly, however the important point of
fluidization should not be lost because the gas flow settings, hence
Reynolds number, were not properly chosen.
2. Always indicate units of quantities that are measured.
3. Never record a calculation, dimension or note on a loose sheet of paper.
4. Sketches of experimental apparatus should be part of notebook. All important
dimensions should be recorded.
5. Data from recorders should be put into a laboratory notebook. Label the data with a
title, data, and description of the data. Prepare your data sheet based on your Pre-Lab
plan. In many experiments you will be taking a series of readings. Record more data
rather than less and, of course, include units with all numerical values. The original
data sheet and any graphs should appear in the appendix of your report, and the data
sheet carbon copy should be turned in to the instructor at the end of each data taking
session. The complete data notebook should be turned in to the instructor at the
end of the course for a grade.
Example:
UNSTEADY STATE HEAT TRANSFER
January 18, 1999
Heating curve for water with aluminum cube
-5-
6. Always record the reading that you actual measure.
Example:
Manometer
L
6 in.
6 in.
R
- 5 in.
²P
11 in.
0
5 in.
Record left and right readings, not only the derived quantity P = 11
in.
Each table should be numbered, have a title and show all units.
Example:
Table 1.
PRESSURE DROP IN PACKED COLUMN
Column diameter: 2 inches
Packed height: 24 inches
Column packing: 1/4 inch Raschig ring
Flow Rate of
Water
kg/m2.s
0
0
0
0
0
0
0.86
0.86
0.86
0.86
0.86
0.86
Flow Rate of
Air
kg/m2.s
Pressure Drop
Inches of water per
foot of packing
0.202
0.279
0.387
0.436
0.558
0.610
0.164
0.199
0.297
0.362
0.501
0.597
0.075
0.157
0.275
0.301
0.403
0.471
0.107
0.159
0.262
0.471
0.785
1.247
-6-
All graphs should have a Figure number, have clearly labeled coordinates and all
parameters labeled. Label symbols should be used for different parameters.
Example:
Pressure Drop in Packed Column
Column Diameter, 2 inches
1.50
Packed Height, 24 inches
1/4 inch Raschig Ring
1.00
Water rate 0
kg/m2.s
Water rate 0.86
kg/m2.s
P (In of water/ft
of packing)
0.50
0.00
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Air flow (kg/m2.s)
Figure 1 Pressure drop in packed column.
Dimensionless numbers should be used if possible. For example: a plot of friction
factor versus Reynolds number is better than a plot of P versus velocity.
7. Notebooks become legal evidence in patent cases. Therefore, always date, sign and
witness.
Example:
Experiment #1
January 18, 1999
Extended Surface Heat Transfer
Signed
Witness (instructor)
____________________ 10/1/02
____________________ 10/1/02
____________________ 10/1/02
____________________ 10/1/02
-7-
8. Notebooks should be neat. Write in ink. Do not erase. If necessary line out with one
line.
Error Analysis of Experimental Data
An error analysis should always be an integral part of your data analysis. It is
important to take sufficient replicate data points, where possible, to enable you to
perform a subsequent error analysis of the results. The ultimate objective of this analysis
is to minimize this error.
The treatment of experimental data does not end when the desired numerical
results have been obtained. An important part of the treatment is the determination of the
uncertainty associated with the numerical results3 . Every measurement of data is subject
to error that can not be determined exactly. If the exact error were known it would be
equivalent to measuring the quantity without error, since correction can be made for any
known error. But it is possible to specify the highest amount by which the quantity might
be in error.
Inaccuracies in measurements can occur due to mistakes and errors2. A mistake is
the recording of a wrong reading (215 recorded as 251). An error can be consistent or
random. A consistent error that usually can be corrected might come from a defect in the
measuring device or the improper use of an instrument. For example: the use of a flow
meter calibrated for air but used for ammonia or the use of a wrong scale on a wet test
meter. Random errors are caused by fluctuations and sensitivity of the instrument or the
inconsistent judgment of the experimenter. An example would be a fluctuating
manometer.
Treatment of random errors.
The more measurements we take the more likely the average will be the most
probable value. Let consider six measurements for the flow rate of a process stream.
Reading
1
2
3
4
5
6
Flow rate F, cm3/s
139.1
142.3
138.4
140.6
139.0
141.5
The estimate mean for the flow rate F is
3
Shoemaker, D. P. et al, “Experiments in Physical Chemistry”, McGraw-Hill, (1981)
-8-
F
1 N
 Fi = 140.15 where N = 6
N i 1
If N is very large (N --> ) then the mean for the flow rate will be the true mean average
F m. The estimate standard deviation is given by
1/ 2
 1 N 2

  Fi  N F 2 
s= 

 N  1  i 1

= 1.5579
Note: The estimate standard deviation can be obtained by the Matlab function std(F)
where
F = [139.1 142.3 138.4 140.6 139.0 141.5].
Since F is an estimated mean from a finite measurement, how confident are we that this
is a true mean? The confidence level, (1 - ) is defined as the probability that the
measured mean for a small sample F lies between a certain confidence interval. A 95
percent confidence means that  = 0.05. The lower confidence interval is
F - c/2
and the upper confidence interval is
F + c/2
t
s
where c/2 =  / 2 and t/2 is given from the Student-t distribution for small, finite
N
sample size (N < 30). Student-t distribution and Student-t statistic were developed by
W.S. Gosset in 1908 who used the pen name of “Student”. Table 1 gives values of t /2
for various confidence levels and N-1.
Table 1. Values of t/2
N-1
1
2
3
4
5
6
7
8
9
10
/2 = .05
6.314
2.920
2.353
2.132
2.015
1.943
1.894
1.860
1.833
1.812
/2 = .025
12.706
4.303
3.182
2.776
2.571
2.447
2.365
2.306
2.262
2.228
-9-
/2 = .01
31.821
6.965
4.541
3.747
3.365
3.143
2.998
2.896
2.821
2.764
In this example, let  = 0.05 which is the normal practice of giving 95 percent confidence
limits for random errors based on small sample. Then
t/2 = 2.571 for N -1 = 5 from Table 1.
Therefore the lower confidence interval is
140.15 - (2.571)*(1.5579)/61/2 = 138.51
and the upper confidence interval is
140.15 + (2.571)*(1.5579)/61/2 = 141.79
Hence,
138.51  F  141.79
and, we are 95 percent confident that the true flow rate mean, F m, lies between 138.51
cm3/s and 141.79 cm3/s and F = 140.15 cm3/s is an estimate of the true mean. It must be
emphasized, however, that systematic errors may be much higher than the random errors
in unfavorable conditions. Therefore the sources of systematic errors must be identified
and eliminated if possible.
Linear Regression
The following section provides you with the background of linear regression. You may
use EXCEL/Tool/Data Analysis/Regression to perform your data analysis.
Error is inherent in data. When data exhibits substantial error rigorous techniques
must be used to fit the "best" curve to the data. Otherwise prediction of intermediate
values, or the derivatives of values, may yield unsatisfactory results.
Visual inspection may be used to fit the "best" line through data points, but this
method is very subjective. Some criterion must be devised as a basis for the fit. One
criterion would be to derive a curve that minimizes the discrepancy between the data
points and the curve. Least-squares regression is one technique for accomplishing this
objective.
It is easiest to interpolate between data points, and to develop correlation, when the
dependent variable is linearly related to the independent variable. While individual
variables may not be linearly related, they may be grouped together or mathematically
manipulated, such as having their log or square root taken, to yield a linear relationship.
Often theory serves as a guide for such manipulations. Since we are mainly interested in
these linear relationships, we will discuss only the technique for linear least-squares
regression.
We wish to fit the "best" straight line to the set of paired data points: (x1,Y1), (x2,Y2), …,
(xi,Yi). The mathematical expression for the calculated values is:
- 10 -
yi = a1 + a2 xi
where yi is the calculated (linear) value approximating the experimental value Yi. The
model error, or residual, ei can be represented as
ei = Yi  a1  a2 xi
where ei is discrepancy between the measured value Yi and the approximated value yi as
predicted by the linear equation and shown in Figure 1.
Yi
yi
ei
xi
Figure 1. Relationship between the model equation and the data
We wish to find values for a1 and a2 to give the "best" fit for all the data. One
strategy is to minimize the sum of the squares of the errors or residuals, between the
measured Yi's and the yi's calculated from the linear model.
MICROSOFT EXCEL provides you with the data analysis tool. Click on Tool/
Data Analysis/Regress and fill in the x-y data. The following example shows you how to
interpret the regression results from EXCEL.
The objective in the example is to find a relationship between pressure drop in a
column and the gas velocity. Table (1) tabulates pressure drop versus gas velocity data.
Table (2) shows results of the regression analysis. The objective is to determine whether
there is a significant correlation between pressure drop and gas velocity. There are many
indicators in Table (2). The simplest indicator is the 95% confidence limits of the slope.
The last two rows of the Table (2) show “Intercept” and “X Variable 1”. Under the
column,”Coefficients”, the first number is the intercept and the second number is the
slope. The column “Standard Error” shows the standard deviation of the intercept and
the slope. If you follow the row “X Variable 1”, you will find the 95% confidence limits
of the slope. If the limits do not change in sign, that is from negative to positive or vice
versa, then the slope is “significantly” different from zero and you can conclude that
there is a significant correlation at the 95% confidence level. You will get the same
conclusion if you compare the “t-stat” of the slope, in this case, 8.2723, with the
tabulated t-value from the student-t table. If the “t-stat” is larger than the tabulated
- 11 -
values, then the correlation is significant. In this latter test the “t-stat” is the ratio of the
absolute value of (slope – 0)/( standard error of slope). You are using the student-t test to
see whether the slope is significantly different from zero.
Figure (1) shows a plot of Pressure Drop versus Gas Velocity and the straight line
relationship.
Table (1) Pressure Drop versus Gas Velocity Data
X
Gas Velocity
ft/sec
1
2
3
4
5
6
7
8
9
10
Y
Pressure Drop
inches water
4
5
7
8
6
9
11
10
14
15
Table (2) Regression Analysis Results
SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.946219042
R Square
0.895330476
Adjusted R
Square
0.882246785
Standard
Error
1.257703535
Observations
10
ANOVA
df
Regression
Residual
Total
Intercept
X Variable 1
1
8
9
SS
108.2454545
12.65454545
120.9
Coefficients
2.6000
1.1455
Standard
Error
0.8592
0.1385
MS
108.245455
1.58181818
F
68.4310345
Significance
F
3.43E-05
t Stat
3.0262
8.2723
P-value
0.0164
0.0000
Lower 95%
0.6187
0.8261
- 12 -
Upper 95%
4.5813
1.4648
Figure 1 Pressure Drop Vs Gas Velocity
16
Pressure Drop, inches water
14
12
10
8
6
4
0
2
4
6
8
10
12
Velocity, ft/sec
Another useful method of data analysis is to determine whether a set of measured data
agree with calculated values. The following example shows how regression analysis can
be used for this determination. Table (3) tabulates measured and calculated pressure
drop. Regression analysis is used to determine the relationship between these two set of
values.. Table (2) shows results of the regression analysis. If the measured values agree
perfectly with the calculated values, the regression would yield a straight line with a
slope equal to 1. If the 95% confidence limits of the slope include the slope of 1, then it
can be concluded that the slope is not significantly different from 1 at the 95%
confidence level and the measured data agree with the calculated values.
- 13 -
Table (3) Measured and Calculated Pressure Drops
Measured
Pressure Drop
inches water
4
5
7
8
6
9
11
10
14
15
Calculated
Pressure Drop
inches water
4
6
8
9
10
11
12
13
14
15
Table (4) Results of Regression Analysis- Example 2
SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.9314
R Square
0.8676
Adjusted R
Square
0.8511
Standard
Error
1.3585
Observations
10
ANOVA
df
MS
96.834
1.845
F
52.467
Significance
F
8.86E-05
Regression
Residual
1
8
SS
96.83
14.76
Total
9
111.6
Coefficients
2.2349
Standard
Error
1.1806
t Stat
1.8930
P-value
0.0950
Lower 95%
-0.4876
Upper 95%
4.9574
0.8950
0.1236
7.2432
0.0001
0.6100
1.1799
Intercept
X Variable 1
- 14 -
Calculated Vs Measured Pressure Drops
Calculated Pressure Drop, inches of water
16
14
12
Series1
10
Linear (Series1)
8
6
4
4
6
8
10
12
14
16
Measured Pressure Drop, inches of water
Figure (2) Calculated versus Measured Pressure Drops
Lab Notebook
Every group must have a lab notebook (with duplicate numbered pages). During each lab
make notes of everything you are doing and every measurement you make. Your
notebook will be evaluated so make sure it is legible and understandable. Each page of
the notebook should be signed by the data taker and witnessed by a group member and
the instructor. Original data sheets should appear in the lab report appendix while the
carbon copies should be given to the instructor at the end of each data taking session. In
your lab notebook:
Write in ink and record all observations directly in the notebook
Do not erase. If necessary line out errors with one line
At the top of each page put the date and the experiment name
When you finish a page, sign and witness your name with date
Never write on a page after you have signed it
- 15 -
Rotate recording among group members
Laboratory Report
Unless given other instructions, students will submit group laboratory reports. Each
group member is responsible for the entire written report. Inclusion of work from
others or non-referenced sources will result in an "F" grade. Reports must be written
according to the format described in the Laboratory Manual. All reports must be doublespaced, typed. A sample of the title page is given.
Laboratory reports are due one week after the scheduled completion of experimental
work, at the beginning of the laboratory period. Late reports will not be accepted.
Reports will be graded both on technical content and on the presentation of the content.
A laboratory report should include the following sections:
Title Page
Executive Summary
Introduction
Objectives
Scope
Procedure
Results and Discussions
Conclusions and Recommendations
Appendix
- 16 -
Title Page
California State Polytechnic University, Pomona
Chemical and Materials Engineering
CHE 333L- TRANSPORT LABORATORY II
WINTER QUARTER, 2010
EXPERIMENT #1
Column Operating Characteristics
INSTRUCTOR:
Lloyd L. Lee
SECTION 10
GROUP #1
MEMBERS: Lau, Lee
McCaffrey, Charles
DUE DATE: January 18, 2010
PRELAB
EXECUTIVE SUMMARY
INTRODUCTION/OBJECTIVES/SCOPE/PROCEDURE
RESULTS & DISCUSSION
a) Recognition and interpretation of
information presented
b) Treatment of data
c) Presentation of relevant information (including results
on graphical, tabular or equation forms)
CONCLUSIONS & RECOMMENDATIONS
APPENDIX
a) Design assignment
b) Original data, sample calculations, other information
GENERAL COMPLETENESS,
CONCISENESS AND NEATNESS
TOTAL
- 17 -
(10) ______
(10) ______
(10) ______
(40) ______
(20) ______
(5) ______
(5) ______
(100) ______
Executive Summary should be written in concise language fitted on a single page. It is
written for an executive who is too busy to read the entire report and yet could make
decisions based on the summary page. See Executive Summary below
Introduction. Research on industrial applications of the experiment and write a
summary of your research.
Objectives. One to two sentences to state why the experiment is performed. For
example, “Determine operating characteristics of columns containing various packings”
Scope. Describe how you intend to accomplish the above objectives. For example,”
Determine pressure drop across the column; determine flooding conditions etc
Procedure. Write a step-by-step procedure that you follow to complete the experiment.
For example, “ 1. Open the valve to allow water to run through the packing at X cc/min.
2. Open the valve slowly to allow air to run through the column making sure that water
does not overflow…”
In your procedure, you must include an experimental grid, a table showing all
experiments you intend to run. For example,
Packing type
Experiments
Raschig Rings
Raschig Rings
Raschig Rings
Raschig Rings
1
2
3
4
Air flow rate
liter/sec
1
1
2
2
Water flow rate
liter/min
2
4
2
4
Results and Discussions. Results are usually presented in Tables and Figures, which
must be numbered and titled such as Table (1) Heat Exchanger Network Summary. All
figures and tables must be referenced in the Discussion Section. If not, they should not be
included. Graphs must be labeled and must have convenient scales on both the x- and yaxis. Hand-drawn graphs are acceptable. In this section you also discuss problems
encountered and how you solve them.
Conclusions and Recommendations. State what conclusions you can draw from this
lab. You can make any recommendations concerning this lab from scope to inaccuracies
of measurements.
Appendix. In this section, you include all data sheets, calculations and any relevant
materials that are too voluminous to be part of the main report. However, you must
reference these contents in your main report. For example, in the Results section of the
main report, you must state ” Data sheets for this experiment can be found in Appendix
A”.
- 18 -
Executive Summaries/Abstracts
(Excerpt from unknown source, CHE Department, Stanford University)
An abstract is a condensation of important information from a report or technical
summary. It is usually one paragraph in length (approximately 200 words). It contains no
equations, figures, tables, or graphs, and rarely contains references. It should be able to
stand on its own, without either the title or the text, and should contain key words for
referencing. An abstract should be written so that the maximum amount of information is
contained in the minimum amount of space. There are two types of abstracts, those which
describe the report and those which describe the work about which the report was written.
The latter type is much more informative and will be used in this class.
An abstract should be written after the report is complete. It should be able to
answer what was done, why it was done, how it was done, the outcome, and the
significance of the results. Several general rules about abstracts are as follows.
1)
2)
3)
4)
5)
Delete any sentence that does not make a positive contribution.
The first sentence should say what was done.
Address the general approach.
Quote the most general results.
State conclusions and significance
The first sentence should inform the reader of what was done, and sometimes why it was
done. Examples of first sentences could be:



A materials balance approach was used to determine the location of the flame
front for an in-situ oil shale retort.
The drag on a sphere in a viscous fluid was measured as a function of sphere
size and flow rate.
The diffusivity of bovine serum albumin (BSA) in K-quark electrophoretic gel
was measured and compared to literature values for BSA diffusivity in the
major competing gels.
The next sentence or two should describe the method that was used to make the
evaluations or comparisons raised in the first sentence. For example:



Off gases from an Occidental Oil (OXY-9) oil shale retort were analyzed by gas
chromatography. The resultant values were used in a computer model that calculated
the mass of oil shale combusted as a function of off-gas production and the location
of the flame front.
Sphere of various sizes were attached to an apparatus designed to measure torque and
placed in a channel of fluid that could be pumped at different rates. The torque
measurements were converted into drag for each of the experiments and compared to
predictions calculated according to the Sangani method.
Concentrated radiolabeled BSA was applied to one side of the gel. Strips of the gel
were removed at hourly intervals. Radiolabel content was analyzed as a function of
- 19 -
distance from the source. The diffusivity was calculated from this information based
on a one-dimensional model.
The next part of the abstract states the results. See the examples below:



The flame front predicted by the off-gas analysis lagged that indicated by the buried
thermocouples.
The experimental results agreed well with the Sangani calculations at low flow rates
(Re < 1) but deviated significantly at higher flow rates (Re > 10).
The measured diffusivity of BSA in K-quark gel was less than half that of the
competing gels.
Finally, the significance of the results is stated:

Later mine analysis showed this to be the result of significant tunneling of the flame
front. Both in-place thermocouples and off-gas analysis gave useful information
about the location of a flame from in an in-situ oil shale retort.
 The Sangani approach is quite effective for the prediction of the drag on a sphere for
creeping flow conditions but must be used carefully at higher Reynold’s number
flow.
Thus the K-quark gels will give better separation of components for lengthy separations
than will the competing gels.
How to put together a laboratory report
1. ORGANIZE !!
2. Get good laboratory data and lots of it. (Read the section: Collection and Analysis of
Experimental Data)
a. What is the error in the measurement of the variables?
b. Identify runs as 1, 2, 3, etc. a different number for each run.
c. Do all of this during the laboratory period.
3. Manipulate laboratory data. Perform calculations in the laboratory.
4. Calculate results; for example Diameter, T, k, Cp.
a. What is the error of a replicated experiment?
b. Do it in laboratory.
5. Note that data and sample calculations go in the Appendix.
6. Correlate experimental results with each other and with the literature or theoretical
values.
a. Graphs are best if appropriate.
b. If not a graph, then a table.
- 20 -
c. Draw a curve through the data points of the graph. Draw the appropriate graph
(straight line or curve) according to what you know about the phenomenon. It is almost
always incorrect to connect the data points by straight line. When drawing a curve, draw
the proper one. If there is no inflection point do not show one.
d. Note that we usually compare experimental results to literature values. These
are different from theoretical or correlated values that are calculated from a (probably
very valid) theoretical or correlated equation.
e. Do as much of this as you can in the laboratory period.
7. Read the prescribed laboratory report format and FOLLOW IT.
8. Reports are prepared backwards!
I) Do the Appendices and the experimental procedure
II) Prepare result graphs or tables
a) Show consistency of experimental runs
b) Compare and correlate experimental results with each other
c) Compare and correlate experimental results with literature data or with
theoretical results.
d) Note that one of the best comparison is % error (be certain to show sign)
III) Discuss results. Place graphs or tables after their discussion.
IV) Draw conclusions and make recommendations
V) Prepare the executive summary.
9. You are writing a technical report on a technical subject for a technical audience.
Don't waste space and your reader's time with simplistic statements.
10. Number pages.
11. Number and title Graphs, Tables, Figures, and Appendix items
12. Aim to be "complete and concise" in the body of the report.
13. Watch significant figures. Usually three or four are appropriate. We are rarely
justified in using more than four!
14. Prepare a Table of Contents.
15. The texts in reports will be read first. So any graph, table, figure or Appendix item
should first be mentioned in the text. Be specific and state; for instance, "see Figure 3 for
∆T vs. time". Figure 3 should then appear on the next possible page.
16. Raw data tables or spreadsheets are generally too voluminous to be included in the
main part of the report and should go to the Appendix.
- 21 -
Oral Presentation:
Each laboratory group will present one oral report (20 minutes) during the quarter. In this
presentation you will discuss your last experimental. The oral report will be graded
according the following criteria:
Equal participation of all group members
Talk within time limit.
Clarity and organization of the talk.
Good speaking voice (clear, loud , well paced) with a dynamic
presentation.
Rapport and interest developed in audience.
Technical accuracy, correctness, and completeness.
Appropriateness of technical level.
Quality of visual aids.
Class Participation
To receive points for class participation, you must ask questions. Each person asking
questions will receive from 1-5 points to maximum of 10 points.
The ability to speak before an audience is an invaluable asset that you must develop.
This development, like writing, is a lifetime endeavor to reach perfection. Each
presentation should be an improvement over the preceding one. A good presentation has
the following structure:
1. Introduce the major points
2. Explain each point in detail
3. Review and summarize the major points
A good presentation requires that you start the preparation ahead of time and:
Produce uncluttered visual aids
Organize the material well so that it is easy and logical to follow
Practice the presentation, if possible in front of an audience
Speak to the entire audience instead of only to key people
Use a conversational speaking style
Suggested content of your presentation:
* Define
your problem. Explain the objective of your investigation. Discuss your
experimental plan.
* Describe your experimental system. Show a drawing (schematic) of your
apparatus and explain how it was operated.
* Describe the difficulties you encountered. Recommend how you would
overcome these difficulties.
* Discuss measurements that were made, or should be taken. Recommend the
best operating range for your independent variables.
- 22 -
* Discuss how the experimental data were, or should have been, analyzed.
* Compare actual with the anticipated results. Discuss your conclusions.
* Make recommendations for the next group performing the experiment
- 23 -
Appendix A
Newton’s Method for Systems of Nonlinear Algebraic Equations
Consider two equations f1(x1, x2) and f2(x1, x2) for which the roots are desired. Let p10 ,
p20 be the guessed values for the roots. f1(x1, x2) and f2(x1, x2) can be expanded about point
( p10 , p20 ) to obtain
f 1
(x1  p10 ) +
x1
f
f2(x1, x2) = f2( p10 , p20 ) + 2 (x1  p10 ) +
x1
f1(x1, x2) = f1( p10 , p20 ) +
f1
(x2  p20 ) = 0
x2
f 2
(x2  p20 ) = 0
x2
Let y10 = (x1  p10 ) and y 20 = (x2  p20 ), the above set can be written in the matrix form
 f1
 x
 1
 f 2
 x1
f1 
x2 

f 2 
x2 
 y10 
 f1 ( p10 , p20 )
=

 0

0
0 
 y2 
 f1 ( p1 , p2 )
or
J(p(0))y(0) =  F(p(0))
In general, the superscript (0) can be replaced by (k1)
J(p(k-1))y(k-1) =  F(p(k-1))
J(p(k-1)) is the Jacobian matrix of the system. The new guessed values x at iteration k are
given by
x = p(k) = p(k-1) + y(k-1)
Example
Use Newton’s method with the initial guess x = [0.1 0.1 0.1] to obtain the solutions to
the following equations2
1
=0
2
f2(x1, x2, x3) = x12  81(x2 + 0.1)2 + sin x3 + 1.06 = 0
f1(x1, x2, x3) = 3x1  cos(x2 x3) 
2
Numerical Analysis by Burden and Faires
- 24 -
f2(x1, x2, x3) = e  x1x2 + 20x3 +
10  3
=0
3
Solution
The following two formulas can be applied to obtain the roots
J(p(k-1))y(k-1) =  F(p(k-1))
J(p(k-1)) is the Jacobian matrix of the system.
 f1
 x
 1
f
J(p(k-1)) =  2
 x1
 f
 3
 x1
f1
x2
f 2
x2
f 3
x2
f1 
x3 
f 2 
x3 
f 3 

x3 
F(p(k-1)) is the column vector of the given functions
 f1 ( x1 , x2 , x3 ) 
F(p(k-1)) =  f 2 ( x1 , x2 , x3 )


 f 3 ( x1 , x2 , x3 ) 
The new guessed values x at iteration k are given by
x = p(k) = p(k-1) + y(k-1)
Table 1 lists the Matlab program to evaluate the roots from the given initial guesses.
Table 1 Matlab program for the example ------------% Newton Method
%
f1='3*x(1)-cos(x(2)*x(3))-.5';
f2='x(1)*x(1)-81*(x(2)+.1)^2+sin(x(3))+1.06';
f3= 'exp(-x(1)*x(2))+20*x(3)+10*pi/3-1' ;
% Initial guess
%
x=[0.1 0.1 -0.1];
for i=1:5
f=[eval(f1) eval(f2) eval(f3)];
Jt=[3
2*x(1)
-x(2)*exp(-x(1)*x(2))
x(3)*sin(x(2)*x(3)) -162*(x(2)+.1) -x(1)*exp(-x(1)*x(2))
x(2)*sin(x(2)*x(3)) cos(x(3))
20]';
- 25 -
%
dx=Jt\f';
x=x-dx';
fprintf('x = ');disp(x)
end
The Matlab program to solve equations (13-16) can be download from T.K. Nguyen
website (http://www.csupomona.edu/~tknguyen/che333/home.htm). Make sure you
understand the program. The system can be solved with measured values of xF, xR, yP, and
r, leaving yi, , *, and KR as unknowns in the solution.
xF = xR( 1  ) + yP
(13)
x R r  yi
yi
= *
(1  x R )r  (1  yi )
1  yi
(14)
yPKR = (1  )*(xr  y)lm
(15)
(1yP) KR = (1  )[(1x)r  (1y))]lm
(16)
% Gas membrane separation calculation
%
Ph=[15 25 35 45 55];
xf=.21;
ypv=[.342 .394 .415 .431 .427;.367 .411 .456 .472 .476;.374 .436 .478 .510
.518];
xrv=[.115 .101 .081 .075 .060;.178 .153 .135 .125 .111;.200 .189 .180 .174 .161];
Kr=2;a=6;yi=0.2;theta=0.5;
dy=.01;
f1='yi*((1-xr)*r-(1-yi))-a*(1-yi)*(xr*r-yi)';
f2='xr*(1-theta)+yp*theta-xf';
dt1='((xf*r-yp)*(xr*r-yi)*(xf*r-yp+xr*r-yi)/2)^(1/3)';
f3='yp*Kr*theta-(1-theta)*a*eval(dt1)';
dt2='(((1-xf)*r-(1-yp))*((1-xr)*r-(1-yi))*((1-xf)*r-(1-yp)+(1-xr)*r-(1-yi))/2)^(1/3)';
f4='(1-yp)*Kr*theta-(1-theta)*eval(dt2)';
%
df1dk=0;df1dt=0;
df2dk=0;df2da=0;df2dy=0;
df4da=0;
for ni=1:3;
- 26 -
for nj=1:5;
xr=xrv(ni,nj);yp=ypv(ni,nj);r=(Ph(nj)+14.7)/14.7;
%
x=[Kr a yi theta];
disp('Guessed values')
fprintf('KR = %8.3f, alfa = %8.3f, yi = %8.3f, theta = %8.3f\n',Kr,a,yi,theta)
for i=1:20
%
f=[eval(f1) eval(f2) eval(f3) eval(f4)];
df1da=-(1-yi)*(xr*r-yi);
df1dy=(1-xr)*r-(1-yi)+yi+a*(xr*r-yi)+a*(1-yi);
df2dt=-xr+yp;
dlm1=eval(dt1);dlm2=eval(dt2);
df3dk=yp*theta;
df3da=-(1-theta)*dlm1;
df3dt=yp*Kr+a*dlm1;
df4dk=(1-yp)*theta;
df4dt=(1-yp)*Kr+dlm2;
yi=yi+dy;
df3dy=(eval(f3)-f(3))/dy;
df4dy=(eval(f4)-f(4))/dy;
yi=yi-dy;
Jt=[df1dk df1da df1dy df1dt;
df2dk df2da df2dy df2dt;
df3dk df3da df3dy df3dt;
df4dk df4da df4dy df4dt;];
dx=Jt\f';
x=x-dx';
Kr=x(1);a=x(2);yi=x(3);theta=x(4);
a_exp=yp*(1-xr)/xr/(1-yp);
if max(abs(dx))<.001, break, end
end
fprintf('For P/p = %8.3f,Calculated values from %g iterations\n',r,i)
fprintf('KR = %8.3f, alfa = %8.3f, alfa exp = %8.3f, yi = %8.3f, theta =
%8.3f\n',Kr,a,a_exp,yi,theta)
disp(' ')
- 27 -
end
end
- 28 -
Appendix B
Temperature Measurements with Labview
Run the program Labview 6.1
box will appears
located on the desktop. The following dialog
Click OK to arrive at this screen
Click “DAQ Solution” to obtain
- 29 -
Click “Next”
Click “Next” to arrive at the following screen
- 30 -
In the dialog box “Gallery Categories”, the highlight should be on Transducer
Measurement. Choose Continuous Thermocouple Measurement in the dialog box
“Common Solutions”. Click “Next” to arrive at the following screen
Click “Open Solution” to open up the following screen
- 31 -
Click the down arrow on the right side of the dialog “Channels” and pick hp1. Next place
the cursor after hp1 and type , hp4, hp5, and hp7 as shown below
- 32 -
Click the right white arrow on the top left of the screen (under “Edit”) to run the program.
You will receive the following display. You should note that the right arrow becomes
black, the graph shows the three thermocouple temperatures with the numerical values
shown on the right (you will likely have different values displayed).
- 33 -
You can right click on the graph to open a dialog box for graphic control. You can choose
“Auto scale Y” so that the temperatures readings will be scaled automatically and
displayed on the graph.
If you choose “Auto scale Y”, the graph should look similar to the above screen.
- 34 -
Appendix C
DAC Express Operation Procedure
1. Go to Start Menu, Program, VT DAC Express, DAC Express. The following screen
should appear.
2. Open the program testtemp in My Documents folder and go to step 5. If you cannot
find testtemp in My Documents or you want to set up the DAC Express yourself then
go to the next step.
3. Enable the channel connected to the board, which are channel 0 – 5. Channel 0 is the
reference channel that uses an on-board thermistor. The channels that are not used
will have to be manually disabled since the DAC program always enables channels 1
thru 31. This is shown in the screen below.
- 35 -
4. Change the Function on Channel 1:0 to Temperature and change Transducer to TCReference Terminal Block (RT1) (122uA source). The EU will automatically change
to Degree C. Change the Function on all other channels enabled to Temperature and
change Transducer to Thermocouple K. The EU will also automatically change to
Degree C.
5. Click on Timebase on the left hand side. Change the Scan Period to 1 second (or any
appropriate time period). The Scan Rate will then change to 1 Scan/s. Fill in the time
needed to record the data at Stop Recording. For example, 10 minutes of data
acquisition equals to 600 seconds of recording.
- 36 -
6. Click on Data Recorder on the left hand side. Click OK on the reminder. The
following screen should appear.
7. Click on Show Display Wizard.
8. Select One Channel per Display and click Next.
9. Select All Current on Tab and click Next.
- 37 -
10. Select all the channels listed and click Next.
11. Select the display type wanted (Readout, Bar Graph, Meter, or Stripchart) and click
Create Displays.
- 38 -
4.
Start Recording the data by clicking on the Record button at the bottom of the
screen.
5.
When data recording is finish, provide the recording name and click OK.
6.
Click on the data name on the left hand side under Data Viewer. The following
screen should appear.
- 39 -
7.
Drag the green line in the bottom box to select all your data. Afterward, right
click on the box and select Export Data.
8.
Export the Data as a text file (*.txt) and click Export. After that, provide a file
name and save it.
- 40 -
9.
Open Microsoft Excel. Click on Data, Import External Data, and Import Data
10.
Select the file saved before and click Next.
11.
After that, the following screen should appear. Click Finish.
- 41 -
12.
Select the cell to place the data and click OK.
13. Spreadsheet of sample run is shown in the screen below.
- 42 -
- 43 -