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\begin_body

\begin_layout Title
Tube Flocculator Team Final Research Report
\end_layout

\begin_layout Author
Team Member: Patience Ruijia Li
\end_layout

\begin_layout Date
December 6, 2012
\end_layout

\begin_layout Abstract
According to the predictive flocculation model proposed by Swetland et.
 al., 2012, large flocs do not significantly contribute to turbidity removal
 -- only small colloids can collide effectively and aggregate to a size
 that will be removed by sedimentation.
 Based on the hypothesis that 
\begin_inset Quotes eld
\end_inset

large flocs are useless
\begin_inset Quotes erd
\end_inset

, a floc breakup procedure was devised.
 Results obtained using a coiled tube flocculator and flocculation residual
 turbidity analyzer (FReTA) shows that higher turbidity removal was achieved
 after breaking the flocs, comparing to results using the same method but
 without floc breakup.
 Therefore breaking flocs at regular intervals to maintain continuous growth
 will promote better performance of flocculation.
 This research finding provided a good reference for future hydraulic flocculato
r design.
\end_layout

\begin_layout Subparagraph*
Key words: Tube flocculator, FReTA, flocs breakup, flocculation, coagulant
 dose, residual turbidity
\end_layout

\begin_layout Part
Introduction
\end_layout

\begin_layout Paragraph*
Mechanical flocculators are not economically and ecologically sustainable
 in terms of energy consumption, financial cost and carbon footprint.
 Gravitational or hydraulic flocculators, compared with Mechanical ones,
 are more cost-effective, reliable and energy efficient.
 However, for over a hundred years, hydraulic flocculators have been used
 less widely than mechanical flocculators due to marketing constraints and
 the impression that hydraulic flocculators are not flexible in their operation.
 The process of hydraulic flocculation has also not been well understood
 and the fundamental mechanisms that govern the performance of this process
 need to be further studied to improve design.
 Hydraulic flocculators can be divided into two types: Horizontal flow flocculat
ors and Vertical flow flocculators.
 Horizontal flow is usually applied in small scale water treatment plants
 and is easy to drain.
 
\color black
Vertical flow flocculators are suitable for m
\color inherit
edium to large scale treatment plants.
 
\end_layout

\begin_layout Paragraph*
Basically, the flocculation process is the coalescing of colloids or suspended
 particles to form flocs that can be removed by sedimentation.
 The goal of flocculation is to minimize residual turbidity or maximize
 turbidity removal.
 To improve the performance of flocculators, we need to research the design
 and operational parameters that affect the aggregation and setting velocity
 of the flocs.
 These parameters include energy dissipation rate, hydraulic residence time,
 sedimentation velocity, coagulant dose, influent turbidity, etc.

\color blue
 
\color black
Dead zones at the edge of baffles create regions where little or no collisions
 of particles occur.
 Thus, an ideal flocculator would have a uniformly distributed energy dissipatio
n.

\color inherit
 Because of drag and shear forces, large flocs are more subject to breakup.
 The energy dissipation rate 
\color black
(
\begin_inset Formula $\varepsilon$
\end_inset

)
\color inherit
 determines the maximum size of flocs because large flocs experience the
 greatest breakage at the maximum 
\begin_inset Formula $\varepsilon$
\end_inset

.
 One option to allow flocs to grow larger is to reduce 
\begin_inset Formula $\varepsilon$
\end_inset

 by adjusting the spacing between the baffles
\color black
.
 Variation in baffle spacing is called tapered flocculation.
 In tapered flocculation, a high energy dissipation rate is used initially
 to enhance collisions and low 
\begin_inset Formula $\varepsilon$
\end_inset

 used later to prevent shear of large flocs.
\end_layout

\begin_layout Paragraph*
In laminar flow, velocity gradient (G) is a function of 
\begin_inset Formula $\varepsilon$
\end_inset

and viscosity (
\begin_inset Formula $\upsilon$
\end_inset

).
 [5]
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Quote
\begin_inset Formula $G=\sqrt{\frac{\varepsilon}{\nu}}$
\end_inset

 
\end_layout

\begin_layout Quote
G=velocity gradient, the difference in velocity between adjacent layers
 of fluids
\end_layout

\begin_layout Quote
\begin_inset Formula $\varepsilon$
\end_inset

=energy dissipation rate, a measure of mixing intensity
\end_layout

\begin_layout Quote
\begin_inset Formula $\upsilon$
\end_inset

= viscosity of water
\end_layout

\begin_layout Paragraph*
Besides velocity gradient, the extent of flocculation is also related to
 how long the colloids are given to collide (i.e.
 hydraulic residence time ( 
\begin_inset Formula $\theta$
\end_inset

), fractional coverage of colloid surface by coagulant (
\begin_inset Formula $\Gamma$
\end_inset

), and fraction of the total volume occupied by flocs (
\begin_inset Formula $\phi$
\end_inset

).
 The composite variable ( G
\begin_inset Formula $\theta\Gamma\phi^{2/3}$
\end_inset

 ) has been used by Swetland [1] to measure the collision potential (
\begin_inset Formula $\Psi$
\end_inset

), which controls the extent of flocculation.
 Lower residual turbidity can be achieved by increasing the collision 
\color black
potential.
 
\end_layout

\begin_layout Paragraph*
The sedimentation velocity of flocs determines the design of sedimentation
 clarifiers and plate settlers.
 High sedimentation velocity is an indicator of effective flocculation.
 
\end_layout

\begin_layout Paragraph*
Theoretically, more collisions will occur in high turbidity water so the
 turbidity removal efficiency is higher when influent turbidity is higher.
\end_layout

\begin_layout Part
Literature Review
\end_layout

\begin_layout Section
Flocculation Model
\end_layout

\begin_layout Paragraph*
The current design of flocculators is primarily based on empiricism and
 the fundamental understanding of flocculation mechanisms is insufficient.
 A predictive model that would show the relationships between the flocculation
 and dependent variables is expected to guide the design and operation of
 hydraulic flocculators.
 [3] The aggregation of small colloids into flocs is a first-order reaction
 with respect to the concentration of small colloids.
 [4]
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Quote

\size largest
\begin_inset Formula $\frac{d_{Colloids}}{d(Gt\Gamma\phi^{2/3})}=-kC_{Colloids}$
\end_inset


\end_layout

\begin_layout Quote
C
\begin_inset Formula $_{Colloids}$
\end_inset

= the concentration of colloids that can not be captured in the sedimentation
 tank
\end_layout

\begin_layout Quote
G = mean velocity gradient
\end_layout

\begin_layout Quote
\begin_inset Formula $\theta$
\end_inset

=hydraulic residence time
\end_layout

\begin_layout Quote
\begin_inset Formula $\Gamma$
\end_inset

= fractional coverage of colloids by coagulant
\end_layout

\begin_layout Quote
\begin_inset Formula $\phi$
\end_inset

= floc volume fraction
\end_layout

\begin_layout Paragraph*
Swetland et.
 al.
 2012 proposed a laminar flocculation model which is governed by the following
 equations.
\end_layout

\begin_layout Standard

\color white
w
\end_layout

\begin_layout Quote
pC
\begin_inset Formula $^{*}$
\end_inset

= - 
\begin_inset Formula $\log$
\end_inset


\begin_inset Formula $\left(C^{*}\right)$
\end_inset

 = 
\begin_inset Formula $\log\left(G\theta\Gamma\phi^{2/3}\right)$
\end_inset

= 
\begin_inset Formula $\log\left[\frac{1}{\beta}\ln\left(\frac{C_{Colloids0}}{C_{Colloids}}\right)\right]$
\end_inset


\end_layout

\begin_layout Quote
where: 
\end_layout

\begin_layout Quote
\begin_inset Formula $G$
\end_inset

 = mean velocity gradient
\end_layout

\begin_layout Quote
\begin_inset Formula $\theta$
\end_inset

=hydraulic residence time
\end_layout

\begin_layout Quote
\begin_inset Formula $\Gamma$
\end_inset

= fractional coverage of colloids by coagulant
\end_layout

\begin_layout Quote
\begin_inset Formula $\phi$
\end_inset

= floc volume fraction
\end_layout

\begin_layout Quote
pC
\begin_inset Formula $^{*}$
\end_inset

= turbidity removal and C
\begin_inset Formula $^{*}$
\end_inset

= residual turbidity divided by influent turbidity
\end_layout

\begin_layout Quote
\begin_inset Formula $\beta$
\end_inset

= 
\begin_inset Formula $\frac{\eta}{V_{Capture}}$
\end_inset

, where
\begin_inset Formula $\eta$
\end_inset

 is a fitted parameter, and V
\begin_inset Formula $_{Capture}$
\end_inset

= capture velocity 
\end_layout

\begin_layout Quote
\begin_inset Formula $C_{Colloids0}$
\end_inset

 = the original concentration of colloids
\end_layout

\begin_layout Quote
\begin_inset Formula $C_{Colloids}$
\end_inset

 = the concentration of colloids that can not be captured in the sedimentation
 tank
\end_layout

\begin_layout Paragraph*
The log linear equation proposed by Swetland demonstrated the connection
 between colloidal particle properties, coagulant size and dose, flocculator
 design and sedimentation tank design.
 Fits to data using the assumption of first order removal of small colloids
 with respect to collision potential are shown below and agree well with
  experimental results (Figure 1).
 [1]
\end_layout

\begin_layout Standard

\color white
Yes
\end_layout

\begin_layout Standard
\begin_inset Graphics
	filename turbidity.png
	lyxscale 40
	width 12cm

\end_inset


\end_layout

\begin_layout Quote
Figure 1 Model fit for pC
\begin_inset Formula $^{*}$
\end_inset

 as a function of effective collision potential for V
\begin_inset Formula $_{Capture}$
\end_inset

= 0.12 mm/s
\end_layout

\begin_layout Section
Coagulation Mechanism
\end_layout

\begin_layout Paragraph*

\color black
Coagulation is the process of coagulants (e.g.
 PACl, alum) attaching to clay particles.
 Conventional theory states that positively charged coagulants neutralize
 the negative charges on the particles to prevent particles from repelling
 each other.
 This assumes that when the repulsion between particles is reduced, the
 colloids can attach to each other and it does not consider that water may
 compete with coagulants to attach to colloids.
 Some research [2] also indicates that distinct mechanisms govern the behavior
 of common coagulants: alum and PACl.
 For PACl, the major mechanisms include electrostatic patch and bridge-aggregati
on and charge neutralization.
 In contrast, alum is believed to interact with clay particles mainly through
 charge-neutralization and sweep-flocculation.
 Since the experiment results based on alternative theories yield very similar
 trends in residual turbidity verses coagulant dose (Figure 1), the distinct
 coagulation mechanism is difficult to discern.
 Experiments conducted by Swetland [3] showed that residual turbidity was
 decreased by a large amount with a slight increase of the coagulant dose
 and at high coagulant dose, no increase of residual turbidity was observed,
 as would be expected with charge reversal.
 An alternative hypothesis [4] involving adhesion of coagulant aggregates
 to colloids has provided a better explanation of coagulation.
 In this theory, the attachment force of adhesive aggregates produced by
 coagulants is stronger than the hydrogen bond between water molecules.
 Thus, these adhesive aggregates displace water to attach to the clay particles.
 
\end_layout

\begin_layout Section
Apparatus
\end_layout

\begin_layout Paragraph*

\color black
The complete experimental assembly consists of synthetic raw water (SRW)
 and coagulant metering system, rapid mix and tube flocculator, and flocculation
 residual turbidity analyzer (FReTA).
 (Figure 2) The turbidimeter with a feedback loop is used to measure the
 influent turbidity and the turbidimeter of FReTA measures the effluent
 turbidity.
 
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard

\color black
\begin_inset Graphics
	filename assembly.png
	lyxscale 30
	width 12cm

\end_inset


\end_layout

\begin_layout Quote

\color black
Figure 2 Schematic of the complete experimental assembly.
 (Updated from Ian Tse's MS thesis, Aug.
 2009)
\end_layout

\begin_layout Subsection

\color black
SRW and coagulant metering system
\end_layout

\begin_layout Paragraph*

\color black
The SRW and coagulant metering system includes a reservoir of clay suspension
 (10g/L), a reservoir of tap water and three pumps (Figure 3).
 The clay suspension is added to the tap water periodically by the regulation
 of a solenoid pinch valve.
 Both alum stock and raw water (with added clay suspension) are drawn by
 the pumps to mix together.
 A portion of raw water is pumped into a turbidimeter for the measurement
 of influent turbidity and then flows back into the raw water feedstock
 to maintain a constant volume.
 A flow accumulator connected to the pump dampens the periodic pulses caused
 by the pump rollers.
 
\end_layout

\begin_layout Standard

\color white
y
\end_layout

\begin_layout Standard

\color black
\begin_inset Graphics
	filename SRW.png
	lyxscale 30
	width 12cm

\end_inset


\end_layout

\begin_layout Standard

\color black
Figure 3 Synthetic Raw Water (SRW) and coagulant metering system.
 (Updated from Ian Tse's MS thesis, Aug.
 2009)
\end_layout

\begin_layout Subsection
Rapid Mix and Tube Flocculator
\end_layout

\begin_layout Paragraph*

\color black
After the flow of the raw water and alum is merged, they enter into a spiral
 
\begin_inset Quotes eld
\end_inset

rapid mix coil 
\begin_inset Quotes erd
\end_inset

 to accelerate their blending.
 The mixture then flows through the laminar tubular flocculator.
 The tube flocculator is comprised of three spiral tubing units (3/8
\begin_inset Quotes erd
\end_inset

 ) wrapped in a figure eight around six parallel support cylinders (two
 cylinders per unit, see figure 4).
 The tubes are arranged in a helical coil because the flocs would stay at
 the bottom in a straight tubing system, restricting the growth of the flocs.
 A calibrated in-line pH probe is inserted at the beginning of the flocculator
 tube and provides a readout of the mixed suspension's hydrogen ion activity.

\color blue
 
\color black
A pressure sensor is also connected to the tubing to protect the system.
 Velocity gradients in the tubular flocculator cause particles to collide
 and form flocs.
 For coiled tube flocculators, velocity gradient is a function of the flow
 rate and the inner diameter of the tube.
 [5]
\end_layout

\begin_layout Standard

\color white
ser
\end_layout

\begin_layout Standard

\size larger
\color black
\begin_inset Formula $G=\frac{8Q}{3\pi r^{3}}$
\end_inset


\end_layout

\begin_layout Standard

\color black
G = velocity gradient
\end_layout

\begin_layout Standard

\color black
Q = volumetric flow rate
\end_layout

\begin_layout Standard

\color black
r = inner diameter of tube
\end_layout

\begin_layout Standard

\color black
\begin_inset Graphics
	filename tube floc.png
	lyxscale 40
	width 10cm

\end_inset


\end_layout

\begin_layout Standard

\color black
Figure 4 Tube flocculator.
 (Updated from Ian Tse's MS thesis, Aug.
 2009)
\end_layout

\begin_layout Subsection
FReTA
\end_layout

\begin_layout Paragraph*

\color black
FReTA is an apparatus for measuring the sedimentation velocity and the effluent
 residual turbidity from the flocculator ( Figure 5).
 There are basically three components of FReTA: an inline turbidimeter,
 a settling column, and an computer-actuated ball valve.
 The plastic housing of the HF Scientific MicroTOL 2 IR inline nephelometric
 turbidimeter was changed in our apparatus to allow a glass column to fit
 through the entire housing and through the measurement area.
 Before use, FReTA is carefully calibrated using a HF Scientific, Inc.
 Primetime Calibration Standards kit.
 
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard

\color black
\begin_inset Graphics
	filename FReTA.png
	lyxscale 60
	width 6cm

\end_inset


\end_layout

\begin_layout Standard

\color black
Figure 5 FReTA.
 (From Karen Swetland's dissertation, Aug.
 2012)
\end_layout

\begin_layout Paragraph*

\color black
The glass settling column serves as a chamber for floc settling without
 affecting the structure of flocs.
 Before measurement of floc settling velocity, it is important to minimize
 the movement of fluid inside the column.
 This is accomplished by ramping the flow to a stop and closing the valve
 at the top of the tube.
 
\end_layout

\begin_layout Paragraph*

\color black
The function of the electrically actuated ball valve (Gemini Valve model
 630) was to prevent flocs in the tube flocculator from falling into the
 settling column once the measurements begin and to hydraulically isolate
 the water in the tube.
 The distance between the bottom of the ball valve and the center of the
 LED zone of the turbidimeter is used to calculate floc settling velocities.
 The equation for sedimentation velocity of flocs is given below.
 [1]
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard

\series bold
\color black
\begin_inset Formula $Vs=\frac{Z}{t}$
\end_inset


\end_layout

\begin_layout Standard

\series bold
\color black
Vs = sedimentation velocity
\end_layout

\begin_layout Standard

\series bold
\color black
Z = distance between the bottom of the ball valve and the center of the
 LED zone of the turbidimeter
\end_layout

\begin_layout Standard

\series bold
\color black
t = settling time
\end_layout

\begin_layout Part
Tube Flocculator Research
\end_layout

\begin_layout Paragraph*
The goal of Tube Flocculator Research is to develop flocculation models
 in laminar flow and to determine different parameters that affect the flocculat
or performance in order to achieve the lowest effluent residual turbidity.
 The first step for research in Fall 2012 was to repeat Dr.
 Karen Swetland's flocculator experiment with alum to get a baseline curve
 of turbidity versus dose for comparison to subsequent experiments.
 In this baseline data the residual turbidity will be measured over a range
 of chemical doses for a spectrum of sedimentation capture velocities.
 In subsequent experiments the residual turbidity will be measured under
 the same experimental conditions but with breakup of large flocs at regular
 intervals.
 [6]
\end_layout

\begin_layout Section
Hypotheses
\end_layout

\begin_layout Paragraph*
1.
 Only laminar flow occurs in tube flocculators.
 
\end_layout

\begin_layout Paragraph*
2.
 Colloids cannot attach to large flocs at maximum size thus we need to break
 those flocs to maintain continuous growth.
\end_layout

\begin_layout Paragraph*
3.
 At low coagulant doses, the residual turbidity is relatively high because
 the attachment efficiency is not big enough to allow flocs to form.
 With the increase of coagulant dose, attachment efficiency rises so the
 residual turbidity is lowered.
 
\end_layout

\begin_layout Paragraph*

\color black
4.
 Discrete settling is assumed in analysis of data since the distance Z is
 much less than the 0.5m interval between sampling ports used in conventional
 flocculant settling tests.
 [5]
\end_layout

\begin_layout Paragraph*
5.
 Flocs will collide and grow when they travel from one breakup position
 to another.
\end_layout

\begin_layout Paragraph*
6.
 Broken flocs can aggregate with small colloids with the same attachment
 efficiency.
\end_layout

\begin_layout Part
Methods and Materials
\end_layout

\begin_layout Section

\color black
Methods
\end_layout

\begin_layout Subsection
Process Controller
\end_layout

\begin_layout Paragraph*

\color black
Experiments were conducted by the apparatus described above.
 The apparatus assembly is managed by Process Controller, a software program
 written in LabVIEW to automatically control the whole experiment.
 There are six operational states regulated by Process Controller to run
 the experiment.
 Each of these states consists of a different set of inputs, rules and set
 points.
 The description of each state is provided in Table 1.
 This table provides a reference for operators to check if the rules and
 states are set correctly and what set points to search when they meet problems.
 At 
\begin_inset Quotes eld
\end_inset

automatic operation
\begin_inset Quotes erd
\end_inset

 mode, the experiment proceeds continuously from the first stage to the
 last state and then jumps back to the first state for the next cycle.
 The number of cycles is set by the operator at the set point 
\begin_inset Quotes eld
\end_inset

 Max reps
\begin_inset Quotes erd
\end_inset

.
 According to the rules for the settling state, when the number of reps
 is bigger than the Max reps, then the experiment will stop.
 The collected data is recorded and processed on a spreadsheet in a MathCAD
 program called Data Processor.
\end_layout

\begin_layout Labeling
\labelwidthstring 00.00.0000

\color black
Table 1.
 Process Controller Operational States
\end_layout

\begin_layout Standard
\begin_inset Graphics
	filename table 1.png
	lyxscale 40
	width 15cm

\end_inset


\end_layout

\begin_layout Subsection
Experimental Method
\end_layout

\begin_layout Paragraph*
All experiments conducted are using the same method recorded in AguaClara's
 archive with the following directory: N://files.cornell.edu/EN/aguaclara/RESEARCH
/Tube Floc/Spring 2012/Experiments/6-29-2012.
 The specific description of this method is provided below.
 
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard
Table 2 Experimental Method Fall 2012 
\end_layout

\begin_layout Standard

\color white
u
\end_layout

\begin_layout Standard
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Set Point
\end_layout

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Value
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Target influent turbidity max
\end_layout

\end_inset
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\begin_inset Text

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100 NTU
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Target influent turbidity min
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\end_inset
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99.7 NTU
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Raw water flow rate
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5.5 mL/s
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\begin_inset Text

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Length of tube
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\begin_inset Text

\begin_layout Plain Layout
83.88 m
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\begin_inset Text

\begin_layout Plain Layout
Alum base
\end_layout

\end_inset
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\begin_inset Text

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1.3
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alum coefficient
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\begin_layout Plain Layout
1.5
\end_layout

\end_inset
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<row>
<cell alignment="center" valignment="top" topline="true" leftline="true" usebox="none">
\begin_inset Text

\begin_layout Plain Layout
Max reps
\end_layout

\end_inset
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\begin_inset Text

\begin_layout Plain Layout
15
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Alum stock conc.
\end_layout

\end_inset
</cell>
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\begin_layout Plain Layout
700 mg/L
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</cell>
</row>
</lyxtabular>

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\end_layout

\begin_layout Description
Note: 
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A power law relationship is used to set a range of alum dose to spread out
 the residual turbidity vs.
 dose curve.
 This equation shows how we set the dose of alum:
\end_layout

\begin_layout Standard

\size normal
\color black
Alum dose = 
\begin_inset Formula $coefficient\times(base)^{maxreps}$
\end_inset

 
\end_layout

\begin_layout Standard

\size normal
\color black
Where max reps means the number of experimental cycles, which is set by
 operators.
 [8]
\end_layout

\begin_layout Section

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Material List
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\begin_layout Paragraph*

\color black
Raw water: Dayton Motor (Grainger #3M290); Bucket; Cylindrical Polypropylene
 Float (Robert Manufacturing Company); Tubing inlet/outlet for influent
 turbidimeter (1/4”); Tubing outlet for system (3/8”); valve;
\end_layout

\begin_layout Paragraph*

\color black
Clay water: 10 g/L clay solution; Bucket Tubing outlet to raw water (1/16”);
 Farmington pinch valve; Stand (made of 1”X1” 80/20);
\end_layout

\begin_layout Paragraph*

\color black
Alum water: 2.5 g/L aluminum sulfate solution; Tubing outlet for alum dosage
 (1/4”); valve
\end_layout

\begin_layout Paragraph*

\color black
Alum pump: L/S Peristaltic pump (Cole-Parmer); Tubing to alum water: 1/4”
 flexible; Tubing to system: 1/4” rigid
\end_layout

\begin_layout Paragraph*

\color black
Influent turbidimeter pump: L/S Peristaltic pump (Cole-Parmer); Tubing:
 1/4” rigid
\end_layout

\begin_layout Paragraph*

\color black
System pumps: L/S Peristaltic pump (Cole-Parmer) – four channels Tubing:
 3/8” rigid 
\end_layout

\begin_layout Paragraph*

\color black
Influent Turbidimeter: Wooden stand MicroTol Online 2 Turbidimeter (#20053)
\end_layout

\begin_layout Paragraph*

\color black
Input to system: 1/4" T combining alum and raw water to enter system; plastic
 bottle, drilled for tubing to act as actuator; 3/8” – 1/4" reducers; Pipe
 thread valve (Farmington); Rapid mixing: rigid tubing (1/4”); wrapped around
 a 2.5” diameter cylinder; 1/4"-3/8” expander; 3/8”-1/2” expander; 1/2" T
 (1 end has valve to dislodge bubbles); Pipe thread valve (Farmington)
\end_layout

\begin_layout Paragraph*

\color black
System: ~9000 cm flexible 1/2" tubing; Ball valve (Gemini #630); MicroTol
 Online 2 Turbidimeter (#20053); Glass column (12” length, 1” od, 0.82” id);
 Brass elbow; Rigid tubing to sink / backwash (3/8”); 3/8” T to sink / backwash;
 2 Pipe thread valves (Farmington), sink / backwash; Water source for backwash.
 [7]
\end_layout

\begin_layout Part
Results and Analysis
\end_layout

\begin_layout Section
Control Experiments
\end_layout

\begin_layout Paragraph*

\color black
The control experiments were replicated using the method described in Section
 5.1.
 Figure 11 shows that the mean influent turbidity stayed around 100 NTU
 with a increased concentration of alum, while the mean effluent turbidity
 during loading state had an upward trend with escalation of alum dose.
 This may mean that alum and flocs are accumulating on the walls of the
 flocculator over time and that the concentration in the flow gradually
 increases as the available wall surface gets covered.
 The effluent turbidity jumps from a background value of around 0.3 NTU,
 to about 70 NTU.
 Figure 12 reveals that the residual turbidity decreased from about 55 NTU
 to 10 NTU with alum dose increasing from 0--8 mg/L.
 The increase of residual turbidity at the third cycle and the last cycle
 might be caused by the movement of some tiny flocs at the measuring region
 of turbidimeter, which makes the number vary a little.
 As time goes on, the residual turbidity generally declines but it's hard
 to tell the difference of removal efficiency with 0.1 mm/s capture velocity
 changing gradually to 0.5 mm/s (Figure 13).
\end_layout

\begin_layout Standard

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yes
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\begin_layout Standard
\begin_inset Graphics
	filename Picture3.png
	lyxscale 60
	width 8cm

\end_inset


\end_layout

\begin_layout Standard
Figure 11 Influent and effluent turbidity vs.
 alum dose at loading state for each experiment cycle
\end_layout

\begin_layout Standard

\color white
Yes
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\begin_layout Paragraph*
\begin_inset Graphics
	filename Picture2.png
	lyxscale 60
	width 8cm

\end_inset


\end_layout

\begin_layout Standard

\color white
Yes
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\begin_layout Standard
Figure 12 Residual turbidity vs.
 alum dose
\end_layout

\begin_layout Standard

\color white
YEs
\end_layout

\begin_layout Standard
\begin_inset Graphics
	filename turbidity capture velocity.png
	lyxscale 40
	width 8cm

\end_inset


\end_layout

\begin_layout Standard

\color black
Figure 13 Residual turbidity vs.
 time for 0.1 mm/s to 0.5 mm/s capture velocities
\end_layout

\begin_layout Standard

\color white
YEs
\end_layout

\begin_layout Section
Experiments with floc breakup
\end_layout

\begin_layout Paragraph*
A floc breakup procedure was devised according to the calculations of energy
 dissipation rate, capture velocity, collision time.
 Six hose clamps were evenly placed onto tube flocculator (2 on each unit,
 see figure 14).
 The inner diameter of clamps are calculated based on the maximum energy
 dissipation rate.
 After the floc breakup device were set up, the flocculator were cleaned
 using a tiny sponge to remove the clay that sticked to the walls of flocculator.
 Then a complete experiment with the same method as the control experiment
 was conducted.
 
\end_layout

\begin_layout Standard

\color white
Yes
\end_layout

\begin_layout Paragraph*
\begin_inset Graphics
	filename clamps.png
	lyxscale 20
	width 6cm

\end_inset


\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard
Figure 14 Floc breakup installation
\end_layout

\begin_layout Paragraph*
Figure 15 demonstrates the compared results of residual turbidity with floc
 breakup and without floc breakup.
 Obviously, the residual turbidity is lower after floc breakup device was
 installed.
 At the alum dose 4, 4.6 and 5.2 mg/L, the difference of residual turbidity
 curve reaches 10 NTU.
 Both curve seems to fit into the logarithmic trend line.
 These two trend lines are consistent with the predictive model in Chapter
 1.
 The results indicate that our hypothesis 
\begin_inset Quotes eld
\end_inset

large flocs are useless
\begin_inset Quotes erd
\end_inset

 may be correct and offers  insight into improving AguaClara's current flocculat
or design.
 
\end_layout

\begin_layout Standard

\color white
yes
\end_layout

\begin_layout Standard

\color white
yse
\end_layout

\begin_layout Standard
\begin_inset Graphics
	filename turb vs dose after floc breakup.png
	lyxscale 30
	width 12cm

\end_inset


\end_layout

\begin_layout Standard
Figure 15 Comparative results of resitual turbidity vs.
 alum dose 
\end_layout

\begin_layout Paragraph*
The Predictive model is supposed to be updated based on the experimental
 data after floc breakup device was installed.
 An approach to update existing model is to insert trend line to our existing
 experimental data and pick the best relationship for turbidity removal
 versus alum dose curve.
 Next we need to check how variables are changed after installation of floc
 breakup.
\end_layout

\begin_layout Part
Conclusions
\end_layout

\begin_layout Section
Breaking flocs and flocculator design
\end_layout

\begin_layout Paragraph*
The capacity of flocculator is based on it's ability to cause collisions
 between particles.
 Breaking large flocs that allow more collisions to happen may be helpful
 to achieve higher turbidity removal.
 Thus, for laboratory experiments, we need to design a component that can
 break up flocs at regular intervals.
 This special component can be an orifice, or a wire mesh set at a size
 that correlates with a desired energy dissipation rate.
\end_layout

\begin_layout Section

\color black
Problems and Solutions
\end_layout

\begin_layout Subsection

\color black
Problems with tubing and connectors
\end_layout

\begin_layout Paragraph

\color black
1.
 When the connections of tubes are leaking, you should check the tubes to
 make sure they are fully plugged into the connectors-- the tube can not
 be easily pulled out if it is fully inserted.
 To ensure no leaking, you need to verify each connection is robust before
 beginning the experiment.
 If there is a leak at the top of the settling column, stop any experiment
 and drain the column.
 You may need to remove the turbidimeter to adjust the connection.
\end_layout

\begin_layout Subsection

\color black
Problems with apparatus
\end_layout

\begin_layout Paragraph

\color black
1.
 If the apparatus is not on when you turn on the switch, that is because
 the power strip sometimes trips the GFI protection.
 When you meet this problem, press the GFI reset button which is on the
 outlet behind the water tank.
 
\end_layout

\begin_layout Paragraph*

\color black
2.
 If raw water pump is not running at loading state, check the direction
 of flow at that pump (should be towards the rapid mix) and the mode (should
 be on mA).
 
\end_layout

\begin_layout Paragraph*

\color black
3.
 If influent turbidity is too high (meaning it is at least 10 NTU more than
 the target turbidity max), use a 1L plastic container to scoop up some
 water from the raw water bucket.
 This water will be replaced by clean tap water to keep the volume constant
 and you should seethe turbidity go down.
 The influent turbidity should decrease by at least 15 NTU after you remove
 1L of dirty water.
 The water in the raw water bucket gets dirtier and dirtier with clay addition.
 It is hard to insert another tube to drain the water so water that is too
 turbid must be removed manually before an experiment is started.
 
\end_layout

\begin_layout Paragraph*

\color black
4.
 If the alum pump is not running at loading state, first ask yourself if
 this is the first cycle.
 If it is the first cycle, then this is normal because the alum dose is
 set to be zero at the first replication.
 If it's not the first cycle, go to settling state and then click loading
 state to see if the alum dose has an increment.
 If there is an increment, then the valve (between the rapid mixer and raw
 water pump) may be mistakenly closed.
 If it is not, then check if the set points are set correctly by locating
 the set points at rule editor to ensure the variables match the code.Process
 Controller Set Points used to control the experimental apparatus.
 Variables are listed with their virtual instrument code (.vi) and can all
 be found in the folders located at the following directory path: 
\backslash

\backslash
Enviro
\backslash
enviro
\backslash
Software
\backslash
Process Controller methods
\backslash
 
\end_layout

\begin_layout Paragraph*

\color black
5.
 If water is filling up the flow accumulator, check the cap of the accumulator
 to make sure it's tight.
 
\end_layout

\begin_layout Subsection

\color black
Problems with Process Controller
\end_layout

\begin_layout Paragraph*

\color black
1.
 If you turn on all the switches, and none of the green indicator lights
 on Process Controller are on, that means you are not connecting with the
 right server or the server may have crashed.
 Check the main server to make sure it is functioning properly and check
 the data server on Process Controller (should be 
\begin_inset Quotes eld
\end_inset

aguadata.cee.Cornell.edu
\begin_inset Quotes erd
\end_inset

).
\end_layout

\begin_layout Paragraph*

\color black
2.
 When you're operating from one state, sometimes nothing is shown on the
 
\begin_inset Quotes eld
\end_inset

current state
\begin_inset Quotes erd
\end_inset

 and the 
\begin_inset Quotes eld
\end_inset

state list
\begin_inset Quotes erd
\end_inset

 is not shown at 
\begin_inset Quotes eld
\end_inset

rules and states
\begin_inset Quotes erd
\end_inset

 at the next state.
 When this happens you need to reload the method file and save it in your
 experiment folder.
 
\end_layout

\begin_layout Subsection

\color black
Problems with Data Processor
\end_layout

\begin_layout Paragraph*

\color black
1.
 If you're having trouble loading the data from Metafile of Data Processor,
 first you need to check the directory to make sure it's on the right track
 to locate the Metafile (an excel spreadsheet in the 
\begin_inset Quotes eld
\end_inset

data processor
\begin_inset Quotes erd
\end_inset

 folder).
 Second check all of the information for a certain MetID ( the one retrieves
 your experiment).
 Pay attention to the dates and duration (if your experiments span 2 days,
 you need to put in the both dates and a duration of 2).
 
\end_layout

\begin_layout Paragraph*

\color black
2.
 Sometimes the graph on the MathCAD file of Date Processor is not shown
 due to memory loss, then you may have to restart the computer to reload
 the data.
 
\end_layout

\begin_layout Part
Future Work
\end_layout

\begin_layout Paragraph*
1.
 Because 
\color black
alum and flocs are accumulating on the walls of the flocculator
\color inherit
 and backwash with tap water is not enough to get rid of all of them.
 We need a way to remove the alum to eliminate the possibility that alum
 sticked on the tube walls causes the residual turbidity to go down.
 Add a new state to rinse the flocculator with a dilute acid to dissolve
 the coagulant to ensure all of the experiments have the same starting point
 with a clean flocculator tube.
 Then carefully repeat this semester's experiments to see if the results
 have any change.
\end_layout

\begin_layout Paragraph*
2.
 Try different floc breakup intervals to determine optimal spacing of orifices
 or clamps.
\end_layout

\begin_layout Paragraph*
3.
 Test tapered flocculation which is realized by reducing the energy dissipation
 rate gradually so that the flocs are able to grow.
\end_layout

\begin_layout Part*
Reference
\end_layout

\begin_layout Paragraph*

\color black
1.
 Karen A.
 Swetland, From stock to floc: an investigation into the physical/chemical
 processes controlling aluminum sulfate and polyaluminum chloride behavior
 in a gravity powered drinking water treatment plant, Ph.D.
 dissertation, School of Civil and Environmental Engineering, Cornell University
, Aug.
 2012, pp.119.
\end_layout

\begin_layout Paragraph*

\color black
2.
 Xiaohong Wu et.
 al.
 , Distinct coagulation mechanism and model between alum and high Al13-PACl,
 Colloids and surfaces A, 305, 2007, pp.
 89-96.
\end_layout

\begin_layout Paragraph*

\color black
3.
 Karen A.
 Swetland, Monroe L.
 Weber-Shirk, Leonard W.
 Lion, Predictive performance model for hydraulic flocculator design with
 polyaluminum chloride and aluminum sulfate coagulants, School of Civil
 and Environmental Engineering, Cornell University, 2012.
\end_layout

\begin_layout Paragraph*

\color black
4.
 Monroe L.
 Weber-Shirk, Class notes, CEE 4540 Sustainable Municipal Drinking Water
 Treatment, School of Civil and Environmental Engineering, Cornell University,
 Oct.
 2012.
\end_layout

\begin_layout Paragraph*

\color black
5.
 Ian Tse, fluid shear influences on hydraulic flocculation systems characterized
 using a newly developed method for quantitative analysis of flocculation
 performance
\color inherit
 
\color black
Master of Science thesis, School of Civil and Environmental Engineering,
 Cornell University, Aug.
 2009, pp.92.
\end_layout

\begin_layout Paragraph*

\color black
6.
 Flocculation with FReTA, Design Challenge for Tube Floc Team Fall 2012,
 AguaClara Project, School of Civil and Environmental Engineering, Cornell
 University, Aug.
 2012.
\end_layout

\begin_layout Paragraph*

\color black
7.
 Karen A.
 Swetland, Materials List for the FReTA Apparatus, Tube Floc research, AguaClara
 Project, School of Civil and Environmental Engineering, Cornell University,
 Jun.
 2010.
\end_layout

\begin_layout Paragraph*

\color black
8.
 Monroe Weber-Shirk, An Automated Method for Testing Process Parameters,
 AguaClara Project, School of Civil and Environmental Engineering, Cornell
 University, Jun.
 2010.
\end_layout

\end_body
\end_document
