Data Analysis
New Tasks for Spring 2013
Floc sedimentation velocity vs coagulant dose
Excerpt |
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Process the data from Karen Swetland’s research to extract the average floc sedimentation velocity as a function of coagulant dosage. It should be possible to assess which coagulant, PACl or alum, produces flocs with a higher sedimentation velocity given the same aluminum concentration. This task does not require any additional laboratory work. It will require writing code to streamline the data extraction process. Think carefully about the best way to measure the time at which the turbidity is at 50% of the flocculated water turbidity. Some data smoothing or line fitting may be needed to get a reasonable estimate of the time. Create graphs of mean floc size as a function of coagulant dose for each of the turbidities that are available. Determine if the ratio of mass of coagulant per mass of clay is a good predictor of floc sedimentation velocity. Analyze the results using the insights from our new flocculation model that emphasizes the role of fractional surface coverage. Determine if equilibrium floc size can be predicted from the fractional surface coverage or if a more complex analysis is required. Make sure to take into account that for low turbidity samples more of the coagulant ends up on the flocculator walls. |
Past Research
Overview
During each experiment,data are automatically recorded in an Excel file (see example). The address for the excel file is recorded into the Meta file which is a spreadsheet with all the directories of the experimental data that will be/has been analyzed. Process Controller will be referring to the Meta file in order to acquire appropriate information on the experiment being analyzed; the Meta file will be an address book for Data Processor to efficiently access data.
The first graphs produced by the Mathcad file are the plots of the raw turbidity data vs. time and raw turbidity vs. settling velocity. The settling velocity (Vs) is calculated by dividing the distance between the ball valve and the zone illuminated by the infrared LED (z) of FRETA by the time elapsed(t).
Latex |
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Wiki Markup |
h1. Data Analysis h2. Overview During each experiment,data are automatically recorded in an Excel file (see example). The address for the excel file is recorded into the Meta file which is a spreadsheet with all the directories of the experimental data that will be/has been analyzed. Process Controller will be referring to the Meta file in order to acquire appropriate information on the experiment being analyzed; the Meta file will be an address book for Data Processor to efficiently access data. The first graphs produced by the Mathcad file are the plots of the raw turbidity data vs. time and raw turbidity vs. settling velocity. The settling velocity (Vs) is calculated by dividing the distance between the ball valve and the zone illuminated by the infrared LED (z) of FRETA by the time elapsed(t). {latex} \large $$ V_s = {z \over t} $$ {latex} |
For
...
experiments
...
involving
...
varying
...
alum
...
dosage,
...
another
...
graph
...
was
...
produced
...
to
...
obtain
...
the
...
residual
...
turbidity
...
vs.
...
settling
...
velocity.
...
Residual
...
turbidity
...
is
...
the
...
turbidity
...
resulting
...
from
...
the
...
flocs
...
that
...
failed
...
to
...
reach
...
the
...
capture
...
velocity,
...
which
...
is
...
0.12
...
mm/s
...
for
...
the
...
sedimentation
...
tanks
...
of
...
the
...
AguaClara
...
plants.
...
From
...
this,
...
we
...
can
...
get
...
the
...
mean
...
residual
...
turbidity
...
for
...
each
...
variation
...
of
...
alum
...
dose.
...
The
...
mean
...
residual
...
turbidity
...
is
...
the
...
mean
...
of
...
all
...
the
...
raw
...
turbidity
...
measured
...
after
...
a
...
time
...
of
...
approximately
...
22
...
min
...
till
...
the
...
end
...
of
...
the
...
sedimentation
...
state.
...
It
...
corresponds to
...
a
...
range
...
of
...
sedimentation
...
velocities
...
from
...
0.12
...
mm/s
...
to
...
0.089
...
mm/s.
...
See
...
example
...
of
...
the
...
residual
...
turbidity
...
graph:
...
...
...
...
...
.
...
TThen
...
data
...
smoothing
...
and
...
normalization
...
are
...
performed
...
on
...
the
...
raw
...
turbidity
...
data.
...
The
...
smoothing
...
allows
...
us
...
to
...
exclude
...
outlying
...
data
...
points
...
caused
...
by
...
really
...
large
...
flocs
...
passing
...
in
...
front
...
of
...
the
...
light
...
sensor
...
of
...
FRETA,
...
which
...
create
...
turbidity
...
fluctuations.
...
The
...
normalization
...
allows
...
us
...
to
...
compare
...
data
...
sets
...
with
...
varying
...
influent
...
turbidities.
...
The
...
plot
...
of
...
normalized
...
turbidity
...
vs.
...
Vs
...
(settling
...
velocity)
...
can
...
be
...
interpreted
...
as
...
a
...
cumulative
...
distribution
...
function
...
(CFD)
...
of
...
turbidity
...
with
...
respect
...
to
...
Vs.
...
A
...
CFD
...
describes
...
the
...
probability
...
that
...
a
...
variable
...
is
...
less
...
than
...
or
...
equal
...
to
...
some
...
value.
...
To
...
make
...
the
...
analysis
...
more
...
robust,
...
the
...
experimental
...
data
...
was
...
fit
...
to
...
a
...
gamma
...
distribution.
...
Then
...
a
...
derivative
...
of
...
the
...
CFD
...
of
...
the
...
gamma
...
distribution
...
gives
...
a
...
probability
...
distribution
...
of
...
the
...
particle
...
population
...
with
...
respect
...
to
...
Vs.
...
From
...
the
...
fitted
...
data,
...
the
...
data
...
processor
...
retrieves
...
the
...
mean
...
sedimentation
...
velocity
...
for
...
each
...
alum
...
dose
...
as
...
well
...
as
...
the
...
coefficient
...
of
...
variation
...
of
...
the
...
distribution.
...
The
...
coefficient
...
of
...
variation
...
is
...
the
...
standard
...
deviation
...
of
...
the
...
distribution
...
divided
...
by
...
the
...
mean.
...
It
...
is
...
an
...
indication
...
of
...
the
...
width
...
of
...
the
...
sedimentation
...
velocity
...
distribution.
...
For
...
more
...
discussion
...
of
...
the
...
data
...
analysis,
...
see
...
Ian
...
Tse's
...
...
(Chapter
...
I,
...
data
...
analysis).
...
See
...
an
...
example
...
of
...
the
...
gamma
...
...
graph:
...
...
...
...
...
...
...
.
...
Analysis
...
Process
...
The
...
data
...
analysis
...
process
...
of
...
the
...
current
...
project
...
emphasizes
...
organization
...
and
...
accuracy.
...
The
...
following
...
is
...
a
...
step-by-step
...
guide
...
for
...
the
...
analysis
...
process.
...
1.
...
Go
...
to
...
the
...
file
...
containing
...
the
...
desired
...
experimental
...
data
...
2.
...
Skim
...
through
...
the
...
datalog
...
(excel
...
sheet
...
with
...
experimental
...
data)
...
to
...
check
...
for
...
any
...
apparent
...
error.
...
(Wrong
...
influent
...
turbidity,
...
no
...
variation
...
in
...
alum
...
dose...)
...
3.
...
If
...
no
...
apparent
...
error
...
is
...
found,
...
open
...
the
...
Meta
...
file
...
and
...
record
...
the
...
appropriate
...
information*
...
*
...
-------------------------------------------------------------------------------------------
...
-
...
**Meta
...
File
...
Information
...
-The
...
Meta
...
File
...
is
...
like
...
as
...
an
...
address
...
book
...
for
...
the
...
datalogs.
...
It
...
is
...
important
...
to
...
update
...
this
...
file
...
after
...
an
...
experiment
...
for
...
the
...
Data
...
Processor
...
to
...
access.
...
The
...
steps
...
following
...
will
...
show
...
how
...
information
...
is
...
recorded
...
into
...
the
...
Meta
...
File:
...
a.
...
Put
...
the
...
appropriate
...
ID
...
Tag
...
number
...
in
...
the
...
A
...
column
...
b.
...
If
...
the
...
duration
...
of
...
the
...
experiment
...
was
...
three
...
days,
...
put
...
the
...
first
...
day
...
in
...
the
...
B
...
column,
...
the
...
second
...
day
...
in
...
the
...
C
...
column,
...
and
...
the
...
third
...
day
...
in
...
the
...
D
...
column;
...
if
...
the
...
experiment
...
only
...
lasted
...
for
...
2
...
days,
...
C
...
column
...
will
...
be
...
left
...
as
...
zero,
...
and
...
the
...
following
...
will
...
be
...
applied
...
for
...
an
...
experiment
...
with
...
a
...
one
...
day
...
duration-only
...
the
...
B
...
column
...
will
...
be
...
filled.
...
c.
...
Record
...
the
...
appropriate
...
directory
...
and
...
flocculator
...
length
...
in
...
column
...
F
...
and
...
G
...
d.
...
Column
...
J
...
will
...
be
...
adjusted
...
according
...
to
...
the
...
datalog;
...
it
...
will
...
be
...
the
...
first
...
row
...
in
...
the
...
datalog
...
where
...
the
...
settle
...
state
...
has
...
been
...
activated.
...
**Note,
...
for
...
most
...
experiments,
...
start
...
row
...
is
...
not
...
adjusted
...
e.
...
Comment
...
on
...
the
...
experiment
...
the
...
datalog
...
is
...
referring
...
to
...
(eg.
...
influent
...
turbidity,
...
alum
...
dose,
...
etc.)
...
Remember
...
to
...
save
...
the
...
Meta
...
file.
...
If
...
not,
...
the
...
Data
...
Processor
...
won't
...
be
...
able
...
to
...
access
...
the
...
data
...
!
...
---------------------------------------------------------------------------------------------
...
-
...
4.
...
Open
...
Data
...
Processor
...
on
...
MathCad
...
5.
...
Change
...
the
...
directory
...
Data
...
Processor
...
is
...
referring
...
to
...
for
...
data
...
(Enter
...
the
...
ID
...
tag)
...
*
...
*
...
**Reference
...
address
...
will
...
be
...
located
...
at
...
the
...
top
...
of
...
Data
...
Processor,
...
and
...
only
...
the
...
last
...
portion
...
of
...
the
...
directory
...
will
...
need
...
to
...
be
...
changed-which
...
is
...
the
...
ID
...
tag
...
appearing
...
on
...
the
...
Meta
...
file.
...
To
...
see
...
where
...
to
...
put
...
the
...
MetaID,
...
see
...
figure
...
1
Figure 1: MetaID location in Data Processor
6. Run the Data Processor; this program will automatically give graphic forms of the data and calculate needed values.
7. In the data processor you will need to change a value. FirstFittedcolumn.
The Data processor cannot fit the data for alum dose too low. This will enable you to eliminate the data that would not be fitted from the data vector. To see where to put the fixed FirstFittedcolumn see figure 2.
Figure 2: FirstFittedColumn location in Data Processor