Long-Term Study of Peripheral Feed/Peripheral Discharge Secondary Clarifiers. By Alex Ekster and Cristina Pena

San Jose/Santa Clara Water Pollution Control Plant (WPCP)

ABSTRACT

Long term study of peripheral feed, peripheral output clarifer was performed at the San

Jose/Santa Clara Water Pollution Control Plant. The effect of eleven operational parameters on

clarifier performance was analyzed. Results indicated that effluent TSS depends only on two

parameters: overflow rate and temperature. An increase of overflow rate deteriorates effluent

TSS due to an increase in the number of large heavy particles in the effluent probably caused by

short-circuiting. A decrease of temperature increases effluent TSS due to a decrease of settling

velocity, and an increase in fraction of non-settleable particles. The best prediction of clarifier

failure can be achieved using overflow rate as an individual indicator with a prediction success

of 33%. The use several operational parameters increases rate of prediction success up to 70%.

KEY WORDS: Clarifier, TSS, testing, overflow rate.

INTRODUCTION

Secondary clarifier performance has a critical impact on effluent total suspended solids (TSS)

and turbidity, and, as a result, has a major impact on the performance of the entire treatment

plant. The purpose of these clarification studies was to optimize the performance of secondary

(BNR) activated sludge clarifiers.

Objectives

The principal objectives of the parallel clarification studies were to:

Determine conditions at which a clarifier fails.

Determine conditions at which clarifier effluent has minimum total suspended solids

concentration.

Determine conditions at which clarifier effluent turbidity does not exceed 5 NTU.

Clarifier performance was studied from 01/22/96 to 6/9/97. It consisted of long-term testing and

short-term stress experiments. The purpose of the long-term testing program was to investigate

the performance of the clarifier at various flows, different sludge settling characteristics, and

different temperatures.

The purpose of short term testing was to study the performance of the clarifier at various flows

with constant sludge settling characteristics and constant temperature.

METHODS AND MATERIALS

The design of the clarifier used in this study, the variables examined, the physical measurements,

the sampling and analysis protocols, and the database developed for this study are described

briefly in the following discussion.

Clarifier design. The clarifier used in this study is peripheral feed, peripheral discharge type

with a 98-ft diameter and 12-ft side water depth (see Figure 1).

Inflow

Inflow

Sludge collector

Influent

Effluent

Weir

98 ft

12.4 ft

1 in

RAS

Figure 1. Schematic diagram of peripheral feed clarifier

Sludge is removed through a perforated manifold located 1 in. off the clarifier bottom. The

rotation speed is approximately 2 rev/hr. An individual motorized valve located on the inflow

pipe controls flow to each clarifier, and an individual Parshall flume measures the effluent flow

from each clarifier. Return sludge flow is measured by individual magnetic flow meters.

Flow. During long-term testing clarifier flows reflected needs of the Biological Nutrient

Removal (BNR) system. All instantaneous readings of flows were transferred electronically to a

central computer where they were averaged on a daily basis. During short-term testing flows

were selected specifically for clarifier testing purposes. The schedule of clarifier effluent flows

during short-term stress testing is given in Table 1.

Table 1. Short-term stress test hydraulic flow.

Test No. Flow, Mgal/d Overflow,gal/ft2-d

1 9 1,200

2 4.5 600

3 8 1,060

4 4 530

5 7 930

6 3.5 465

Clarifier testing for each flow rate during short-term testing was started 24 hours after the flow

rate was changed.

Sampling and analytical procedures. Water temperature was measured continuously and was

averaged on a daily basis. In addition, once a month, a depth temperature profile was measured

using a thermopair. Mixed liquor samples were collected and analyzed for MLSS and SVI twice

a day and the results were averaged on a daily basis. MLSS concentration was measured initially

(until 3/96) using gravimetric analysis (Standard Methods, Sections 2540D AWWA, 1992) and

then by a suspended solids meter (Royce INC. Model 7011). SVI was measured using the sludge

volume index method (Standard Methods, Section 2710D, AWWA, 1992). Clarifier effluent

samples were collected using 24-hour composite samplers (ISCO Model 2910). The 24-hour

composite effluent samples were collected at midnight and analyzed for total suspended solids

(TSS). In addition several “ultimate” TSS tests were performed during the course of the study.

In this test, effluent was settled in a jar for 30 minutes and the supernatant was sampled and

analyzed for TSS. The purpose of this test was to determine flocculation ability of the activated

sludge.

The aforementioned sampling and analytical procedures were used during both long-term and

short-term testing. During short-term testing, ultimate effluent TSS was determined, and particle

sizes of effluent solids were measured. Turbidity was measured using Cole-Palmer turbidity

meter model 8391-50. A Met One particle counter (model WGS-267) was used to determine the

distribution of effluent particles during short-term experiments. The manufacturer calibrated the

particle counter every 12 months using standardized polystyrene latex spheres. Particles in grab

samples were counted within one hour of collection. To reduce the possibility of contamination,

the particle counter was cleaned thoroughly with deionized water before and after testing each

sample. Sample flow through the particle counter was kept at manufacturer’s suggested flow

rate of 100 ml/min and was verified before testing each sample. During analysis, particles were

kept in suspension by employing a gentle swirling motion in the sample container. Each sample

was counted in 5 replicates. If the difference between replicate counts was more than 10%, the

sample was re-analyzed. The volume of the particles was determined by assuming that

individual particles were spherical in shape. The volume distribution of particles was calculated

by multiplying the total number of particles found in a size range by the spherical volume of that

particular range size. The size ranges were chosen according to manufacturer’s calibration. A

dye tracer test was performed on the secondary clarifier in order to determine the hydraulic

residence time using a fluorometer with continuous flow (Turner Design Model 10-AU).

Rodamine WT fluorescent dye was injected at the clarifier influent channel and the concentration

was monitored at the clarifier effluent channel as a function of time.

Independent variables. To examine clarifier operation during long-term testing, a database of

all of the parameters that could potentially affect performance of the clarifiers was compiled.

The list of parameters is given in Table 2.

Table 2 List of parameters that can potentially affect performance of the clarifier.

Parameter

Variable

Effect on clarification was discussed in following

reference

Effluent Flow Q Daigger, 1995

Settled Volume Index SVI Daigger, 1995

Mixed Liquor Suspended Solids concentration

MLSS Daigger, 1995

Solids load including recycle flow L Tekippe, Bender 1983

Solids load without recycle flow L1 Tekippe, Bender 1983

Sludge recycle ratio R Tekippe, Bender 1983

Temperature T Wilson, 1996

Q/Qo1 Q/Qo Daigger, 1995

Settling volume2 SV Voutchkov, 1992

Air flow F Parker et al,1972

1 Qo = VoA, where Vo is the initial settling velocity calculated according to

Daigger(1995), and A is the clarifier surface area. 2 SV = SVI x MLSS/1000

Results of long-term testing comprised 494 data sets (one set for each day of testing). After the

database was assembled, outliers were identified for the following parameters: effluent total

suspended solids (TSS) and MLSS. The following method was used for identifying outliers. The

average absolute difference, (|Bav|), between corresponding consecutive 24 hr composites was

calculated for the entire database. The potential outliers were identified based on the following

criteria:

1) IBi|>|Bav|

2) |Bi+1 |>|Bav|

3) Bi and Bi+1have different signs

where Bi is the difference between two consecutive samples.

The operating conditions, on the day when a potential outlier was identified, were compared with

conditions on the previous three days and the following three days. If effluent flow, return

sludge rate, and the sludge wasting rates did not change by more than ten percent on the day

when a potential MLSS outlier was identified, the MLSS and SVI values were considered as

errors and were removed from the data base. Similarly, TSS outliers were eliminated from the

database if, in addition to Q, R and waste rates, MLSS, SVI, and F did not change by more than

ten percent. It was recognized that some of the TSS outliers could be real values associated with

conditions such as the presence of foam, algae, or floating sludge. However, the presence of

these values in the data base would be misleading in developing true relationship between TSS

and independent variables listed in Table 2. Less than 5 percent of TSS and MLSS data were

removed from the database.

Next, the database was divided into two parts based on effluent TSS values: below and above 30

mg/L. Values below 30 mg/L represent performance of unfailed clarifier. The 30 mg/L

threshold was chosen, based on the analysis of the Voutchkov’s (1992) data produced in similar

studies. Occurrences when effluent TSS exceeded 30 mg/L were considered to be the result of

clarifier failure, and were analyzed separately.

Using the statistical computer software JMP, a correlation between TSS and Q, Q/Qo, SVI,

MLTSS, F , T, L, L1 was developed from the database containing effluent TSS values less than

30 mg/L. Before performing the statistical analysis the relationships between the function and

each individual independent variable were examined by plotting the TSS versus each

independent variable. The purpose of this examination was to determine whether the

relationship is homogenous. Except for SVI, the relationship was homogeneous for all

parameters. The SVI-TSS relationship was homogeneous only within 50 to 150 mL/g SVI

range(see Figure 2), and only this range of SVI was used in statistical analysis.

0

2

4

6

8

10

12

14

<50 50-100 100-150 >150

Med

ian

efflu

ent

TS

S, m

g/L

SVI, mL/g

Figure 2. Effluent TSS versus SVI.

After dividing the database, a multivariable linear regression analysis was used to develop the

relationship between TSS and the independent variables. The objective of this analysis was to

select the regression model which best satisfied the following two criteria: minimizing the

number of independent variables and maximizing the predictive power of the mode. Each

variable was examined to determine its contribution toward explaining TSS variability. Stepwise

regression analysis described elsewhere (Chapman, 1983) was used for this purpose. Realizing

that the TSS may be affected by other variables than those mentioned in Table 2, and that some

of these variables such as foam, floating sludge, floc structure, etc. may introduce autocorrelation

properties into statistical relationships, prior day effluent suspended solids concentration was

used as an independent variable.

Clarifier failure was assumed whenever effluent TSS exceeded 30 mg/L. Independent variables

such as Q, L1, Q/Qo were considered separately as predictors of clarifier failure. Minimum

values of each independent variable at which TSS >30 mg/L were considered to be critical

values. After critical values were established, percent failures were calculated by comparing the

total number of days that the independent variable exceeded critical value with the total number

of days when TSS >30mg/L. Higher percent of failure indicates better predictor.

RESULTS

Long term testing

Clarifier operational parameters are given in Table 3.

Table 3. Range of change for various operations parameters used to evaluate the performance of the clarifiers.

Parameter Q, gpd/ft2

SVI, mL/g

MLSS, mg/L

L, lb/ft2 L1, lb/ft2 R, % T, oF Q/Qo F, ft3/gal

SV, mL/L

TSS, mg/L

Minimum 260 50 2000 11 5.5 22 65 0.23 1.2 170 3

Maximum 1200 150 4390 54 36 108 79 1.34 4.9 890 102

Average 710 115 2940 26 17 50 72 0.58 1.6 360 10

Median 720 106 3020 27 17 50 71 0.51 1.6 310 8

10 percentile 520 76 2480 18 12 36 67 0.32 1.4 210 5

90 percentile 860 138 3800 34 24 67 77 0.98 1.8 590 14

The only three parameters that affected suspended solids concentration were temperature

(student coefficient t = -13.03), overflow rate (student t = 13.29), and settling volume (student t =

3.23). The regression coefficient without autocorrelation was 0.64, with autocorrelation the

regression coefficient was 0.8. The contribution of each variable to the improvement of the

correlation coefficient ( R) is reported in Table 4.

Table 4. Contribution of each statistically significant variable to the improvement of the correlation coefficient( R).

Parameter Cumulative R

Q 0.31

T 0.61

SV 0.64

All other parameters listed in Table 2 did not have a statistically significant effect on the TSS.

There was also no change in temperature with clarifier depth either in winter or in summer.

There were a total of 5 days when effluent suspended solids exceeded 30 mg/L. The critical

values of the independent variables were Q = 8.3 Mgal/d (1,100 gal/ft2d), L = 37 lb/ft2, and

Q/Qo = 0.73. The flow could be used as a failure predictor 33 percent of the time, load (L) 6

percent of the time, and Q/Qo 5 percent of the time.

During long-term testing several ultimate TSS tests were performed. The data showed that

ultimate TSS observed in the beginning of the mixed liquor channel, the end of the mixed liquor

channel and in the clarifier effluent were the same.

There were forty-five incidents when instantaneous effluent turbidity exceeded 5.0 NTU. Less

than ten percent of these cases were associated with high overflow rate. The critical overflow

rate for these cases was 980 gal/ft2d. All other incidents when the effluent turbidity exceeded

5.0 NTU were associated with Nocardia foaming and the presence of pin flocs.

Short term testing

The results from the short-term testing program are given in Table 5.

Table 5.

Operational parameters during short-term testing.

Test # Q,

gpd/ft2 SVI, mL/g

MLSS, mg/L

L1, lb/ft2

L, lb/ft2 R,% T, oF Q/Qo

SV, mL/L

TSS, mg/L

TSS1,

mg/L

1 1,200 100 2,600 24 31 30 71 0.77 260 17 -

2 600 87 2,500 13 21 56 71 0.44 220 12 3

3 1,060 91 2,500 23 30 30 71 0.7 220 25 5

4 530 95 2,400 10 17 65 72 0.45 240 4 3

5 930 98 2,400 18 25 40 72 0.56 240 9 3

6 465 84 2,500 10 17 70 72 0.3 250 9 2

TSS1 - after settling in a jar for 30 min (ultimate TSS)

Because the short-term stress test was conducted over a three-week period, settling

characteristics and temperature remained constant throughout the test.

Particle counting. The distributions of particles for two flow rates (465 gpd/ft2 and 1,200

gpd/ft2) are depicted on Figure 3. For both flow rates the majority of particles were less than 15

μm in diameter. Particle distributions for Tests 2 through 5 (not shown) followed the same

distribution trend.

1

10

100

1000

104

0 20 40 60 80 100

465 gpd/ft21200 gpd/ft2

Num

ber

of P

artic

les

Particle Size, um

Figure 3. Distribution of particles in the clarifier effluent at high and low overflow rates.

DISCUSSION

Long term testing

The results obtained in this study are examined in the following discussion, with respect to

correlation and the effect of the individual variables.

Correlation coefficient. The correlations described in the results section only explain 41% of

effluent variability without autocorrelation and 64% with autocorrelation. The average error of

the predicted value was 1.7 mg/L, which is less than the expected laboratory error of 1.8 mg/L as

determined by Tuntoolavest et. al. (1983) of an average value of 10 mg/L. Therefore, it can be

concluded that the significant part of TSS variation is caused by the inaccuracy of the

gravimetric analytical method.

Effect of individual independent variables. The effect of overflow rate on effluent suspended

solids is well known. Less expected was the strong relationship between temperature and

effluent quality. One explanation for the strong relationship could be attributed to the change of

particle settling velocity with the temperature as calculated by Bhargava and Rajagopal (1992).

Analyzing Bhargava and Rajagopal data within the temperature range observed in our study, it

was found that individual particle settling velocity increases by 1.5% with each oF increase.

Based on this finding, the overflow rate was multiplied by the correction factor expressed by

Equation 1:

Correction factor = [1-0.015(T - 68oF)] (1)

where T is temperature, oF

The coefficient of regression between TSS and corrected overflow rate was 0.48. Although the

coefficient of regression for the corrected overflow rate value (0.48) was better than the

coefficient of regression for the non-corrected overflow rate value (0.3), it was still below the

coefficient of regression existing for the relationship in which both temperature and overflow

rate are considered as shown in Table 6.

Table 6. Relationship with Effluent Total Suspended Solids

Relationship with TSS Corrected factor Coefficient of Regression

Non-corrected overflow rate - 0.3

Corrected overflow rate 1.5%(oF) 0.48

Corrected overflow rate 4.3%(oF) 0.61

Temperature and overflow rate - 0.61

Based on the results of the above analysis it can be concluded that an increase of individual

particle settling velocity alone cannot explain the strong correlation between temperature and

effluent suspended solids. Winter storms and Nocardia foaming observed in winter and

springtime coincided with the period of low temperature. During this time, the range of ultimate

TSS increased from 2-3 mg/L(summer) to 5-6 mg/L. We postulate that the strong correlation

between effluent TSS and temperature presented in Table 6 is caused not only by a decrease of

settling velocity at lower temperature, but also with the increase of non-settleable TSS in the

winter. The best correlation between TSS and corrected overflow rate was found when the

correction factor was equal to 4.3 percent for each oF. The correlation coefficient was equal to

0.61. The effect of the temperature corrected overflow rate on the median effluent suspended

solids is shown on Figure 4. As shown in Figure 4, the median value of TSS is not affected until

overflow rate reaches 650 gal/ft2d. The average TSS, as shown in Figure 5, starts to increase at

lower overflow rate. This difference in behavior between the median and average TSS indicates

that incidents of temporary increase of TSS are less frequent at overflow rates below 550

gal/ft2d.

0

2

4

6

8

10

12

14

450-550 551-650 651-750 751-850 851-950

Eff

luen

t TS

S, m

g/L

Overflow rate, gal/ft2-d

Figure 4

Effect of overflow rate normalized for 68oF on median clarifier effluent TSS

0

2

4

6

8

10

12

14

450-550 551-650 651-750 751-850 851-950

Eff

luen

t TS

S, m

g/L

Overflow rate, gal/ft2-d

Figure 5

Effect of overflow rate normalized for 68oF on average clarifier effluent TSS.

The effect of settling volume on effluent quality, although statistically significant, is less

pronounced than the effect of overflow rate. These results are consistent with Voutchkov’s

(1992) results developed under conditions comparable to this study.

The absence of any relationship between other parameters listed in Table 2 and effluent

suspended solids may indicate that the effect of these parameters on effluent quality is site

specific, and needs to be analyzed for each activated sludge system. Literature presents varying

opinions regarding the relative magnitude of the effect of these parameters on TSS. For instance

Tuntoolavest et. al. (1983) and Pfalnz (1969) reported a strong relationship between TSS and

MLSS. Chapman (1983) found that a relationship existed, but the correlation was not very

strong, but his findings were contrary to the findings of Agnew (1972) and Villiers (1967).

Similarly, Tuntoolavest et al. (1983) and Parker et. al.(1972) found strong effect of air flow on

TSS, whereas Chapman (1983) observed none. Similar contradictions can be found regarding

other parameters listed in Table 2. Parker presented the data that indicated overflow rate in a

well design clarifier doesn’t affect effluent TSS, whereas Wilson has an opposite opinion (Parker

and Wilson, 1998). The reason we observed strong effect of overflow rate on the effluent TSS in

this study is probably due to short-circuiting in the clarifier. A dye study showed (see Figure 6)

that dye was first observed in the effluent in less than 20 minutes after initial dye injection into

mixed liquor and reached the maximum concentration in 1 hour 12 minutes. The theoretical

residence time was 2.25 hours. This data clearly indicates the presence of short-circuiting, which

is usually intensified with an increase of overflow-rate. Zhou and Vitasovic(1995) predicted

short-circuiting based on 2-D modeling of the peripheral feed-peripheral outtake clarifiers and

proposed to rectify this problem by installing two additional effluent launders at a distance of 1/3

and 2/3 radius from the center.

0

10

20

30

40

50

60

70

80

0:36 1:12 1:48 2:24 3:01 3:37 4:13 4:49 5:25 6:02

Dye

Con

cent

ratio

n, m

g/L

Time (hrs:min)

t0 = 0 hrs 16 min

Cmax

@ 1 hr 12 min

Figure 6 Dye concentration at the end of the secondary clarifier in 16 minutes indicated short-circuiting.

The regression analysis showed strong correlation between water temperature and effluent TSS.

Wilson (1996) reported that temperature affects effluent TSS because of change in the settling

velocity. However, we believe that the strong correlation observed between effluent TSS and

temperature is caused, not only by temperature changes, but also by the rainy season that

coincided with the decrease in temperature. During the rainy season, ultimate TSS increases

from 3 mg/L to 5-6 mg/L. Small, poor settling, particles coming in with rain water probably

caused an increase of unsettleable solids in the effluent. We speculate that if non-settleable

solids in the sludge during the winter storm is decreased by polymer addition or improved

flocculation, for example, the correlation between effluent TSS and temperature will not be as

strong.

Interestingly enough, no changes were observed in ultimate TSS from the aerator and clarifier

effluent. This indicates that there is no break-up of floc, neither in the mixed liquor channel nor

in the clarifier. At the same time, there is no additional flocculation observed in the clarifier,

which is probably due to the absence of a flocculation chamber in the clarifier. The fact that the

number of small particles (<10 μm) in the effluent is not affected by the flow, serves as another

indication that clarification process in this type of clarifier does not change fraction of non-

settleable solids.

When comparing the results presented in this report with the results reported in the literature, the

following points need to be taken into account.

The database in this study is much larger than databases used in most clarifier studies

reported in literature.

This study was conducted in an industrial setting; the majority of other studies were

conducted in research settings, with much smaller and shallower clarifiers.

The clarifier feed in this study was peripheral, in most studies reported in literature the

clarifiers were of the center feed type.

The average effluent suspended solids concentration in this study was considerably lower

than in other studies.

The airflow rate in this study varied considerably less than in other studies.

Taken together, all of these factors may explain the differences in the results.

Clarifier failure. Clarifier failure was best predicted using overflow rate as a predictive

parameter. However, use of the overflow rate as a predictor was successful only 33 percent of

the time. The overflow rate was corrected according to the following formula Qx[1-0.043 (T -

68)]. The critical corrected overflow rate value was found to be 1,100 gal/ft2d. When the

corrected overflow rate was used as a predictor the prediction success increased up to 50 percent.

In all cases, when the temperature corrected overflow rate exceeded a critical value, the TSS

exceeded 15 mg/L, which corresponds to the upper 10 percent of the observed TSS values.

When two indicators (temperature corrected overflow rate and Q/Qo) were used, the prediction

increased up to 70 percent. In all cases when the temperature corrected overflow rate exceeded

critical value (1100 gal/ft2d) and Q/Qo exceeded critical value (0.72), the effluent suspended

solids exceeded 22 mg/L, which corresponds to the upper 2.5 percent of the observed TSS

values. When Q/Qo was normalized for the temperature, the failure predictability did not

improve. The fact that a correlation could not be established between clarifier failure and

clarifier loading could probably be explained by short circuiting; an increase of solids in the

clarifier effluent happened before the clarifier was overloaded with solids.

Short-Term Testing

An increase of clarifier overflow rate generally did not affect the number of particles with

diameters below 10 μm, but increased the number of particles with diameters greater than 10 μm.

The effect of the overflow rate became more pronounced as the particle diameter became larger

and larger. There were three times more particles with diameters between 25 and 50 μm at 1,200

gal/ft2•d than at 465 gal/ft2•d and 4 times more particles with diameters between 50 μm and 100

μm at 1,200 gal/ft2•d than at 465 gal/ft2•d. An increase in the number of large (heavy) particles

explains the good correlation between overflow rate and effluent TSS found during long-term

testing. Analysis of the relationship between overflow rate and effluent TSS confirmed that

there was still a general tendency of deterioration in effluent quality with an increase of overflow

rate (Figure 7). However, the same graph illustrates the fact that even at the same temperature

and the same mixed liquor suspended solids concentration effluent TSS was affected by more

factors than just overflow rate.

0

5

10

15

20

25

30

400 500 600 700 800 900 1000 1100 1200

Eff

luen

t TS

S, m

g/L

Overflow Rate, gal/ft2-d

Figure 7 Effect of clarifier overflow rate on effluent TSS during short term testing.

Analysis of Table 5 showed that sludge settleability (SVI,SV) and ultimate TSS were practically

the same. Variation in clarifier effluent TSS during short term testing probably is associated

with more factors that are depicted in Table 5. Inaccuracy of gravimetric method of TSS

analysis is one of such factor. Short-circuiting, wind, and other factors affecting hydraulic

performance of the clarifier feasibly are contributing to the variability of effluent TSS. Inability

to consider all parameters that may affect clarifier effluent TSS generally reduces efficiency of

short-term testing, because some of the results may be incidental and do not reflect long-term

clarifier performance. Combination of short-term stress testing and long-term testing provides

better opportunity for evaluation of clarifier performance.

Conclusion

The overflow rate (Student t = 13.29) and water temperature (student t =-13.03) had

significant statistical correlation with effluent suspended solids. The settling volume

(Student t = 3.23) had considerably less effect on TSS, although still statistically significant.

All other parameters listed in Table 2 did not have a statistically significant effect on TSS.

Ultimate TSS did not change through mixed liquor channel and clarifier. This indicates that

no floc breakup nor flocculation occurs in these process units. At the same time a

considerable increase in ultimate and effluent TSS was observed during the rainy season.

The fact that rainy season coincided with the low temperature may explain the reason why

statistical analysis showed higher than expected effect of temperature on effluent TSS.

The lowest TSS value was achieved when overflow rate was below 550 gal/ft2d. An

increase of overflow rate deteriorates effluent TSS due to an increase in the number of large

heavy particles in the effluent probably caused by short-circuiting.

The best prediction of clarifier failure can be achieved using overflow rate as an individual

indicator with a prediction success of 33%. If overflow rate was normalized for temperature

using Equation 1 and used with another indicator Q/Qo, the prediction success rate increases

to 70%. The critical values for the overflow rate and Q/Qo are 1100 gal/ft2d and 0.72,

respectively.

At overflow rate below 1000 gal/ ft2d, incidents of instantaneous turbidity readings

exceeding 5 NTU will be reduced. However, the most important preventive measures

against turbidity increase are foaming control and the prevention of pin floc formation.

REFERENCES

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2. AWWA. (1992) Standard Methods for the Examination of Water and Wastewater, APHA, AWWA, WEF.

3. Bhargava, D. S. and K. Rajagopal (1992) "An Integrated Expression for Settling Velocity of Particles in Water." Wat.Res. Vol.26, No.7, pp1005-1008

4. Chapman. D. (1983) “The Influence of Process Variables on Secondary Clarification,” Journal Water Pollution Control Federation, Vol. 55, No.12. pp 1425-1433.

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8. Parker,D.S. and Wilson, T.E. (1998) “The Great Secondary Clarifier Debate: I. Surface Overflow Rate is Not an Appropriate Design Criterion For Dimensioning Secondary Clarifiers.” Wat.Env.Fed. Proceedings of the Water Environment Federation 71st Annual Conference & Exposition.

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10. Tekippe, R. and J.H. Bender (1987) "Activated Sludge Clarifiers: Design Requirements and Research Priorities," Journal Water Pollution control Federation, Vol. 59, No. 10, pp. 865-870.

11. Tuntoolsvest, M., E. Miller, and C. P. Grady (1983) "Factors Affecting the Clarification Performance of Activated Sludge Final Settlers," Journal Water Pollution Control Federation,, Vol 55, No.3, pp. 234-247.

12. Villiers, R. V. (1967) "Removal of Organic Carbon from Domestic Wastewaters." M.S. Thesis, Univ. of Cincinnati, Cincinnati Ohio.

13. Voutchkov, N. S. (1992) "Relationship for Clarification Efficiency of Circular Secondary Clarifiers." Water science and Technology, Vol. 26, No. 9-11, pp 2539-2542.

14. Wilson, T. E. (1996) "A New Approach to Interpreting Settling Data." Proc. Wat. Env. Fed. 69th Annual Conference & Exposition, Vol. 1, pp491-497.1996.

15. Zhou and Vitasovic. Memorandum on Clarifier Modeling. August 17,1995.