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© IWA Publishing 2014 Water Science & Technology
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Effects of longitudinal baffles on particles settling in a sedimentation basin N. S. Park, S. S. Kim, Y. J. Lee and C. K. Wang
ABSTRACT This study was conducted to evaluate the effects of longitudinal baffles on particles settling 3
performance within a full-scale sedimentation basin with a flow rate of 1,000 m /hr. Comparative experiments on turbidity removal efficiency and sludge deposit distribution were performed in longitudinally baffled and non-baffled sedimentation basins. The turbidity removal rate in the baffled sedimentation basin was observed to be higher than that in the non-baffled basin. In addition, the depth of the sludge deposit in the baffled sedimentation basin was approximately 20% less than that in the non-baffled sedimentation basin, and the sludge concentration was 10% higher. To explain these results and to further investigate the effects of longitudinal baffles, the authors performed computational fluid dynamics (CFD) simulation for both basin types. The results of this CFD simulation indicated that the flow, particularly near the outlet orifice, was more stable in the longitudinally baffled sedimentation basin. Moreover, it could be concluded that the longitudinal baffle enables a fully developed flow and is thus more effective for sedimentation. Key words
N. S. Park (corresponding author) Department of Civil Engineering, Gyeongsang National University, 501, Jinju-daero, Jinju, 660-701, Republic of Korea E-mail: [email protected] S. S. Kim Y. J. Lee Water Research Center, Korea Institute of Water and Environment, K-water, 462-1, Jeonmin-Dong, Yusung-Gu, Daejeon, 305-730, Republic of Korea C. K. Wang Department of Environmental Engineering, Chungnam National University, 99 Daehak-Ro, Yusung-Gu, Daejeon, 305-764, Republic of Koera
| computational fluid dynamics (CFD), longitudinal baffle, particles settling performance, sedimentation basin, sludge deposit distribution
INTRODUCTION The actual performance of sedimentation basins in water treatment plants (WTPs) is governed strictly by physical parameters including hydraulic structure (Jayanti & Narayanan ). The adequacy of hydraulic structures has generally been evaluated on length-to-width ratio, surface overflow rate (SOR), weir overflow rate (WOR), hydraulic loading rate, Reynolds number, and Froude number (Park et al. ; Vittal & Ragahav ). Table 1 summarizes the standard parameters and the criteria suggested by the Korean Water Works Association (KWWA ). During the sedimentation process in Korean WTPs, an inadequate opening ratio in the inlet baffle and an extremely small Froude number are observed most frequently as problems related to hydraulic structures (Park et al. ). Because it is very difficult to guarantee that the perimeter is wetted enough to obtain a small hydraulic radius, it is impossible to simultaneously meet both criteria, i.e., Reynolds and Froude numbers, in a sedimentation basin. As the hydraulic radius increases, the Reynolds number increases and the Froude number decreases. Therefore, to ensure that the Froude number remains greater than 106, doi: 10.2166/wst.2013.818
the hydraulic radius must be decreased. In the same context, to decrease the hydraulic radius, it is necessary to reduce the horizontal area (A) or increase the wetted perimeter (P), as given in Equation (1): R¼
A P
(1)
where A is the horizontal area (effective height × width) and P is the wetted perimeter. Reducing the horizontal area would involve high construction expenses and a considerable amount of time, whereas increasing the wetted perimeter could be achieved more easily by installing a longitudinal baffle in a basin. In contrast to the large number of studies on the inlet structure of sedimentation basins (Kawamura ; Stovin & Saul ; Jayanti & Narayanan ; LeChevallier ), few studies are available that evaluate the effects of installation of longitudinal baffles in existing structures for improving the settling efficiency. A number of studies using computational fluid dynamics (CFD) techniques have been conducted in recent years to simulate the hydrodynamic behaviour within a
N. S. Park et al.
1213
Table 1
|
|
Effects of longitudinal baffles on particles settling in a sedimentation basin
Standard parameters and criteria used for evaluating hydraulic structures of horizontal sedimentation basins
Criteria
Criteria
suggested
suggested by KWWA
Parameter
by KWWA
Length/width
4:1–8:1
Over 106
Width/height Length/height
3:1–6:1 Over 15:1
Froude number SOR WOR Opening area ratio in inlet baffle
6–8%
Parameter
Length ratio
Reynolds number
Less than 10,000
15–49 Less than 248
sedimentation basin. In particular, Matko et al. showed the usefulness of CFD for investigating the hydraulics of sedimentation basins in their review (Matko et al. ). Stovin and Saul showed that commercial CFD software could be used to accurately predict the flow pattern in their storage chamber, and that the analysis of bed shear stresses enabled the prediction of efficient sedimentation (Stovin & Saul ). In addition, they used ANSYS Fluent particle tracking software to predict the location of sediment deposition in the storage chamber. The ultimate purpose of this study is to evaluate the effectiveness of a longitudinal baffle installed in a sedimentation basin, which has not yet been investigated. To analyze the effectiveness in a full-scale basin, the authors conducted long-term experiments to measure turbidity in each effluent and the distribution of sludge deposition at the bottoms of baffled and non-baffled basins installed in a selected domestic WTP. The two basins were geometrically identical with the exception of the installed longitudinal baffle. Moreover, to explain the experimental results and further investigate the effects of longitudinal baffles, the authors conducted CFD simulation for both basin types.
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17, 2009. The thickness of baffle is 65 mm, and its height is 3.2 m from inlet to the end of launder and 2.2 m from the latter to the end wall, respectively. To conduct comparative experiments between baffle-installed and non-baffled basins, the authors selected symmetrically located Basins 3 and 6, to represent the former and latter cases, respectively (Figure 1(a)). The values in the second column in Table 2 were calculated based on basin size and designed flow rate of 425,000 m3/day. During the comparative experiments conducted from December 18, 2009, to April 1, 2010, the inlet flow rate for each basin was set at 1,000 m3/hr. The Reynolds number and the Froude number derived from the designed flow rate of 425,000 m3/day were 18,091 and 2.12 × 106, respectively. These values failed to meet Korean standards. To conduct this research, sludge discharge was interrupted on December 12, 2009, to measure turbidity and distribution of sludge deposition. This interruption created a sludge depth of more than 4 m near the inlet wall. Turbidity in the effluent from Basin 3 (baffled) and Basin 6 (non-baffled) was measured continuously for approximately four months with a turbidimeter (Micro TOL; HF Scientific Co., Ltd). The turbidity measurements were classified based on two conditions. One is the case in which the inlet flow rate had been maintained stably at about 50% percent of the designed flow rate on March 19–21, 2010; the other is the case in which the flow was repeatedly shut off and restarted on March 25–27, 2010, which created dramatic fluctuation in the inlet flow rate. The distribution of sludge deposition was detected from December 18, 2009, to April 1, 2010. The authors selected a total of 34 distribution measuring points in each basin at intervals of 2 m from the inlet wall to the end wall on the left and right sides. The authors calculated the average values from the results obtained at both sides. Table 2 shows the hydraulic operating conditions based on basin size and the designed flow rate. The last column in the table represents criteria values regulated in Korea.
MATERIAL AND METHODS
Methodology of CFD simulation
To investigate factual phenomena in a full-scale sedimentation basin, the authors selected a particular domestic Korean WTP with a capacity of 425,000 m3/day of drinking water. This WTP contains eight sedimentation basins, and two chain-and-flight-type sludge collectors are operated on each basin. A longitudinal baffle composed of high density polyethylene, the plant’s Basin 3, was built on December
Governing equations To investigate the effects of various launder types on hydrodynamic behaviour within a full-scale sedimentation basin and to provide several retrofitting suggestions, the authors used CFX 11.0 design software (ANSYS ). The CFD simulation works by splitting the geometry of interest into
N. S. Park et al.
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Figure 1
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Effects of longitudinal baffles on particles settling in a sedimentation basin
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Sedimentation basin arrangement and wire frame geometry for computational fluid dynamics (CFD): (a) sedimentation basin arrangement and measuring points of sludge deposit distribution; (b) non-baffled basin (Basin 6); (c) baffled basin (Basin 3); (d) baffled basin photo.
Table 2
|
Hydraulic conditions of the selected full-scale sedimentation basin selected for this study
Hydraulic conditions (flow rate
Regulation
Parameters
425,000 m3/day)
criteria of Korea
Length/width ratio
4.4
4–8
Width/height ratio
4
3–6
Length/height ratio
17.7
Over 15
Velocity (m/sec)
0.0076
Below 0.0067
Wetted perimeter (m)
3
Reynolds number (Re)
18,091
Below 10,000
Froude number (Fr)
2.12 × 106
Over 1 × 106
Surface loading rate (m/d)
36.9
15–49
Weir loading rate (m3/m d)
229
Below 248
Upward velocity (m3/m d)
77.7
58.6–87.9
a large number of elements, collectively known as grids or cells. Then, momentum and continuity equations were formulated for each grid together with given boundary conditions and were repeatedly solved by using the finite volume method (Scilian et al. ; Park et al. ). In this simulation, about 70,000 cells for each case were generated. The time-averaged Navier–Stokes equations for
momentum and continuity were solved in this study for steady, incompressible, turbulent, and isothermal flow. The continuity and momentum equations are, respectively, ∇ ðU Þ ¼ 0
(2)
∇ ðρU ⊗ U μ∇U Þ ¼ B þ ∇P ∇ (ρu ⊗ u)
(3)
where ρ and μ are fluid density and dynamic viscosity, respectively; P is pressure; U is fluid mean velocity; B is body force; and u is fluctuating velocity. Turbulence modelling Although the Reynolds number in the sedimentation basin was higher than the 10,000 regulated by Korean standards, all cases were simulated by using turbulence modelling to investigate eddy flow and energy dissipation in greater detail. The Reynolds number is a ratio of inertia force to viscous force. The authors assumed that the turbulence in the basin was isotropic. Therefore, a standard k-ϵ model was used for modelling the turbulence transport of momentum (Suhas ; Versteeg & Malalasekera ).
N. S. Park et al.
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Effects of longitudinal baffles on particles settling in a sedimentation basin
Boundary conditions The liquid free surface at the top of the sedimentation basin, which is in contact with air, is considered flat and frictionless (i.e. a symmetry plane). Although some fluctuations occur at the free surface due to air friction, such inconsistencies are usually small enough to be neglected for the objectives of this study. At the side and bottom wall surface, a no-slip condition was assumed, and a widely used standard wall boundary method was applied to bridge the viscous sublayer. Therefore, it is assumed that each component’s
Figure 2
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velocity at each wall is zero. The wall shear stress was obtained from the logarithmic law of the wall (Currie ; Versteeg & Malalasekera ).
RESULTS AND DISCUSSION Comparison of turbidity removal rates Figure 2(a) shows residual turbidities in effluents from Basins 3 and 6 under stable inlet flow rate conditions, as previously
Residual turbidities in effluents from Basins 3 and 6: (a) residual turbidities in effluents from Basins 3 and 6 under stably maintained inlet flow rate; (b) residual turbidities in effluents from Basins 3 and 6 under conditions of repeated shutting off and restarting.
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Effects of longitudinal baffles on particles settling in a sedimentation basin
described, and the raw water turbidity measured between March 19 and 21, 2010, was below 10 nephelometric turbidity units (NTU). As shown in the figure, the stably maintained inlet flow rate resulted in an approximate 18% higher turbidity removal rate in Basin 3 over that in Basin 6. In addition, the average turbidities derived from Basins 3 and 6 were 0.49 and 0.60 NTU, respectively. Figure 2(b) shows the residual turbidities in effluents from the same basins under conditions of repeated shutting off and restarting. The curve represents the dramatic fluctuation in the flow rate. As shown in the figure, the turbidity removal rate from Basin 3 was approximately 38% higher than that from Basin 6 under unfavourable conditions. This result indicates that longitudinal baffles are effective even under highly erratic of flow rates. Distribution of sludge deposition To investigate the effects of longitudinal baffles on sludge distribution and depth, the deposited sludge remained in the tank for approximately four months. Each row of 34 sampling points was 1.2 m away from left and right wall sides. Figure 3 shows the sludge depth distribution in Basins 3 and 6. As shown in Figure 3, the total volume of sludge from Basin 6 was approximately 20% greater than that from Basin 3. This phenomenon is in contrast to the turbidity removal measurements. However, the suspended solids (SS) concentration in Basin 3 was 10% higher (2,000 mg/L) than that in Basin 6 (Table 3). These results
Figure 3
|
Total volume of deposited sludge in Basins 3 and 6: (a) relationship of results obtained with different baffle types; (b) actual deposited sludge of both Basins measured on April 1, 2010.
Table 3
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Results of SS concentration measurement
SS concentration from Basin 3 (%)
SS concentration from Basin 6 (%)
0 (upper level)
1.6
1.9
1
2.3
2.0
2
2.4
2.0
3
2.4
2.1
4 (bottom level)
2.7
2.3
Average
2.3
2.1
Depth (m)
indicate that the total volume of sludge from Basin 3 was lower because the baffle contained the sludge more effectively.
Results of CFD simulations The comparative experiments revealed that the installation of a longitudinal baffle in a sedimentation basin improves settling efficiency. To further examine these results and investigate the effects of longitudinal baffles in greater detail, the authors conducted CFD simulations for both basins. Figure 4 shows the results for Basins 3 and 6 under an operating flow rate of 1,000 m3/hr. Figure 4 depicts the flow pattern within two basins with a velocity contour. In the case of the non-baffled basin, the dead zone, outlined by a dotted-line box, was relatively larger than that of the baffled basin. In contrast, the baffled basin overall exhibited a well-developed and stable flow. A comparison of both side views indicates that the velocity at the central plane in the case of the baffled basin is less than that in the case of the non-baffled basin. This result occurred because the longitudinal baffle worked as a noslip wall to reduce the overall velocity within the basin. Moreover, the red-coloured regions in Figure 4, which represent higher velocities, are relatively smaller in the case of the baffled basin. High velocity beneath launders creates an especially adverse effect on sedimentation. To further examine this condition, Figure 5 shows velocity vectors for each case in greater detail. Figure 5 illustrates the velocity vector of the flow pattern within each basin. Since the longitudinal baffle at the central plane in the baffled basin works as a no-slip wall, the authors selected plane intervals at 5 cm from central plane for this type of basin. As is evident in the figure, tiny arrows indicate the flow pattern (upward velocity distribution) beneath the
N. S. Park et al.
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Figure 4
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Effects of longitudinal baffles on particles settling in a sedimentation basin
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Simulation results showing velocity contour of flow patterns within each basin: (a) top view of Basin 3 (baffled; on left) and Basin 6 (non-baffled; on right); (b) side view of Basin 3 (baffled; lower diagram) and Basin 6 (non-baffled; upper diagram) showing flow pattern at the central plane. The full colour version of this figure is available online at http://www. iwaponline.com/wst/toc.htm.
Figure 5
|
Simulation results of flow patterns within both basins highlighting the velocity vector with plane intervals of 5 cm from the central plane: (a) Basin 6 (non-baffled); (b) Basin 3 (baffled).
launder. In the case of the non-baffled basin, velocity was higher, and the flow pattern was more unstable than that observed in the case of the baffled basin. However, although a local high-velocity region was observed in the case of the baffled basin, the flow pattern beneath the launder showed greater stability.
CONCLUSIONS This study was conducted to evaluate the effects of longitudinal baffles on hydrodynamic behaviour within a certain fullscale sedimentation basin with a flow rate of 1,000 m3/hr. Comparative experiments were conducted on the turbidity removal efficiencies and sludge deposit distribution in longitudinally baffled and non-baffled sedimentation basins. Moreover, to explain these results and further investigate the effects of longitudinal baffles in greater detail, the authors performed CFD simulations for both basin types.
The findings of this study are summarized in the following points: (1) A comparison of the performances of baffled and nonbaffled basins revealed that under a stably maintained inlet flow rate, the turbidity removal rate from the baffled basin was approximately 18% higher than that from the non-baffled basin. In addition, the turbidity removal rate from the baffled basin was approximately 38% higher than that from the non-baffled basin under unfavourable, highly erratic flow rate conditions. These results indicate that longitudinal baffles effectively compensate for dramatic fluctuations in flow rate. (2) The investigation of distribution of sludge deposition within each basin revealed that the total volume of sludge from the non-baffled basin was approximately 20% greater than that from the baffled basin. However, the SS concentration from the baffled basin was 10% higher than that from the non-baffled basin. These
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Effects of longitudinal baffles on particles settling in a sedimentation basin
results indicate that although the total volume of sludge from the baffled basin was smaller, the baffle was more effective in sludge removal. (3) From the results of CFD simulation, velocity was higher and the flow pattern was more unstable in the nonbaffled basin. However, although a local high-velocity region was observed in the case of the baffled basin, the flow pattern beneath the launder was more stable because the longitudinal baffle worked as a no-slip wall to reduce the overall velocity within the basin.
REFERENCES ANSYS CFX 11.0-Application Manual. Oxfordshire, UK. Currie, I. G. Fundamental Mechanics of Fluids. McGrawHill, New York. Jayanti, S. & Narayanan, S. Computational study of particle-eddy interaction in sedimentation tanks. ASCE, Journal of Environmental Engineering 130 (1), 37–49. Kawamura, S. Integrated Design of Water Treatment Facilities. John Wiley & Sons, Inc., Republic of South Korea. Korea Water Works Association Standard Guideline for Water Treatment Plant. Korea Ministry of Environment, Seoul, Korea.
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LeChevallier, M. W. Water Treatment and Pathogen Control. IWA Publishing, London, UK. Matko, T., Fawcett, A. Sharp & Stephenson, T. Recent progress in the numerical modelling of wastewater sedimentation tanks. Transactions of IChemE 74B, 245–257. Park, N., Park, H. & Kim, J. Examining the effect of hydraulic turbulence in a rapid mixer on turbidity removal with CFD simulation and PIV analysis. Journal of Water Supply: Research & Technology-AQUA 52 (2), 95–108. Park, N., Kim, J., Bae, C., Moon, Y. & Ahn, H. Identification and prioritization of performance limiting factors for water treatment plant optimization in Korea. Water Science and Technology: Water Supply 6 (2), 71–76. Scilian, J. M., Hirt, C. W. & Harper, R. P. FLOW-3D: Computational Modelling Power for Scientists and Engineers. Flow Science Report (FSI-87-00-1). Stovin, V. R. & Saul, A. J. Sedimentation in storage tank structure. Water Science and Technology 29 (1–2), 363–372. Stovin, V. R. & Saul, A. J. Efficiency prediction for storage chambers using computational fluid dynamics. Water Science and Technology 33 (9), 167–170. Suhas, V. P. Numerical Heat Transfer and Fluid Flow. McGraw-Hill, New York. Versteeg, H. K. & Malalasekera, W. An Introduction to Computational Fluid Dynamics. Prentice-Hall, New York. Vittal, N. & Ragahav, M. S. Design of single-chamber settling basins. ASCE, Journal of Environmental Engineering 123 (10), 469–471.
First received 5 November 2013; accepted in revised form 13 December 2013. Available online 30 December 2013
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© IWA Publishing 2014 Water Science & Technology
|
69.6
|
2014
Effects of longitudinal baffles on particles settling in a sedimentation basin N. S. Park, S. S. Kim, Y. J. Lee and C. K. Wang
ABSTRACT This study was conducted to evaluate the effects of longitudinal baffles on particles settling 3
performance within a full-scale sedimentation basin with a flow rate of 1,000 m /hr. Comparative experiments on turbidity removal efficiency and sludge deposit distribution were performed in longitudinally baffled and non-baffled sedimentation basins. The turbidity removal rate in the baffled sedimentation basin was observed to be higher than that in the non-baffled basin. In addition, the depth of the sludge deposit in the baffled sedimentation basin was approximately 20% less than that in the non-baffled sedimentation basin, and the sludge concentration was 10% higher. To explain these results and to further investigate the effects of longitudinal baffles, the authors performed computational fluid dynamics (CFD) simulation for both basin types. The results of this CFD simulation indicated that the flow, particularly near the outlet orifice, was more stable in the longitudinally baffled sedimentation basin. Moreover, it could be concluded that the longitudinal baffle enables a fully developed flow and is thus more effective for sedimentation. Key words
N. S. Park (corresponding author) Department of Civil Engineering, Gyeongsang National University, 501, Jinju-daero, Jinju, 660-701, Republic of Korea E-mail: [email protected] S. S. Kim Y. J. Lee Water Research Center, Korea Institute of Water and Environment, K-water, 462-1, Jeonmin-Dong, Yusung-Gu, Daejeon, 305-730, Republic of Korea C. K. Wang Department of Environmental Engineering, Chungnam National University, 99 Daehak-Ro, Yusung-Gu, Daejeon, 305-764, Republic of Koera
| computational fluid dynamics (CFD), longitudinal baffle, particles settling performance, sedimentation basin, sludge deposit distribution
INTRODUCTION The actual performance of sedimentation basins in water treatment plants (WTPs) is governed strictly by physical parameters including hydraulic structure (Jayanti & Narayanan ). The adequacy of hydraulic structures has generally been evaluated on length-to-width ratio, surface overflow rate (SOR), weir overflow rate (WOR), hydraulic loading rate, Reynolds number, and Froude number (Park et al. ; Vittal & Ragahav ). Table 1 summarizes the standard parameters and the criteria suggested by the Korean Water Works Association (KWWA ). During the sedimentation process in Korean WTPs, an inadequate opening ratio in the inlet baffle and an extremely small Froude number are observed most frequently as problems related to hydraulic structures (Park et al. ). Because it is very difficult to guarantee that the perimeter is wetted enough to obtain a small hydraulic radius, it is impossible to simultaneously meet both criteria, i.e., Reynolds and Froude numbers, in a sedimentation basin. As the hydraulic radius increases, the Reynolds number increases and the Froude number decreases. Therefore, to ensure that the Froude number remains greater than 106, doi: 10.2166/wst.2013.818
the hydraulic radius must be decreased. In the same context, to decrease the hydraulic radius, it is necessary to reduce the horizontal area (A) or increase the wetted perimeter (P), as given in Equation (1): R¼
A P
(1)
where A is the horizontal area (effective height × width) and P is the wetted perimeter. Reducing the horizontal area would involve high construction expenses and a considerable amount of time, whereas increasing the wetted perimeter could be achieved more easily by installing a longitudinal baffle in a basin. In contrast to the large number of studies on the inlet structure of sedimentation basins (Kawamura ; Stovin & Saul ; Jayanti & Narayanan ; LeChevallier ), few studies are available that evaluate the effects of installation of longitudinal baffles in existing structures for improving the settling efficiency. A number of studies using computational fluid dynamics (CFD) techniques have been conducted in recent years to simulate the hydrodynamic behaviour within a
N. S. Park et al.
1213
Table 1
|
|
Effects of longitudinal baffles on particles settling in a sedimentation basin
Standard parameters and criteria used for evaluating hydraulic structures of horizontal sedimentation basins
Criteria
Criteria
suggested
suggested by KWWA
Parameter
by KWWA
Length/width
4:1–8:1
Over 106
Width/height Length/height
3:1–6:1 Over 15:1
Froude number SOR WOR Opening area ratio in inlet baffle
6–8%
Parameter
Length ratio
Reynolds number
Less than 10,000
15–49 Less than 248
sedimentation basin. In particular, Matko et al. showed the usefulness of CFD for investigating the hydraulics of sedimentation basins in their review (Matko et al. ). Stovin and Saul showed that commercial CFD software could be used to accurately predict the flow pattern in their storage chamber, and that the analysis of bed shear stresses enabled the prediction of efficient sedimentation (Stovin & Saul ). In addition, they used ANSYS Fluent particle tracking software to predict the location of sediment deposition in the storage chamber. The ultimate purpose of this study is to evaluate the effectiveness of a longitudinal baffle installed in a sedimentation basin, which has not yet been investigated. To analyze the effectiveness in a full-scale basin, the authors conducted long-term experiments to measure turbidity in each effluent and the distribution of sludge deposition at the bottoms of baffled and non-baffled basins installed in a selected domestic WTP. The two basins were geometrically identical with the exception of the installed longitudinal baffle. Moreover, to explain the experimental results and further investigate the effects of longitudinal baffles, the authors conducted CFD simulation for both basin types.
Water Science & Technology
|
69.6
|
2014
17, 2009. The thickness of baffle is 65 mm, and its height is 3.2 m from inlet to the end of launder and 2.2 m from the latter to the end wall, respectively. To conduct comparative experiments between baffle-installed and non-baffled basins, the authors selected symmetrically located Basins 3 and 6, to represent the former and latter cases, respectively (Figure 1(a)). The values in the second column in Table 2 were calculated based on basin size and designed flow rate of 425,000 m3/day. During the comparative experiments conducted from December 18, 2009, to April 1, 2010, the inlet flow rate for each basin was set at 1,000 m3/hr. The Reynolds number and the Froude number derived from the designed flow rate of 425,000 m3/day were 18,091 and 2.12 × 106, respectively. These values failed to meet Korean standards. To conduct this research, sludge discharge was interrupted on December 12, 2009, to measure turbidity and distribution of sludge deposition. This interruption created a sludge depth of more than 4 m near the inlet wall. Turbidity in the effluent from Basin 3 (baffled) and Basin 6 (non-baffled) was measured continuously for approximately four months with a turbidimeter (Micro TOL; HF Scientific Co., Ltd). The turbidity measurements were classified based on two conditions. One is the case in which the inlet flow rate had been maintained stably at about 50% percent of the designed flow rate on March 19–21, 2010; the other is the case in which the flow was repeatedly shut off and restarted on March 25–27, 2010, which created dramatic fluctuation in the inlet flow rate. The distribution of sludge deposition was detected from December 18, 2009, to April 1, 2010. The authors selected a total of 34 distribution measuring points in each basin at intervals of 2 m from the inlet wall to the end wall on the left and right sides. The authors calculated the average values from the results obtained at both sides. Table 2 shows the hydraulic operating conditions based on basin size and the designed flow rate. The last column in the table represents criteria values regulated in Korea.
MATERIAL AND METHODS
Methodology of CFD simulation
To investigate factual phenomena in a full-scale sedimentation basin, the authors selected a particular domestic Korean WTP with a capacity of 425,000 m3/day of drinking water. This WTP contains eight sedimentation basins, and two chain-and-flight-type sludge collectors are operated on each basin. A longitudinal baffle composed of high density polyethylene, the plant’s Basin 3, was built on December
Governing equations To investigate the effects of various launder types on hydrodynamic behaviour within a full-scale sedimentation basin and to provide several retrofitting suggestions, the authors used CFX 11.0 design software (ANSYS ). The CFD simulation works by splitting the geometry of interest into
N. S. Park et al.
1214
Figure 1
|
|
Effects of longitudinal baffles on particles settling in a sedimentation basin
Water Science & Technology
|
69.6
|
2014
Sedimentation basin arrangement and wire frame geometry for computational fluid dynamics (CFD): (a) sedimentation basin arrangement and measuring points of sludge deposit distribution; (b) non-baffled basin (Basin 6); (c) baffled basin (Basin 3); (d) baffled basin photo.
Table 2
|
Hydraulic conditions of the selected full-scale sedimentation basin selected for this study
Hydraulic conditions (flow rate
Regulation
Parameters
425,000 m3/day)
criteria of Korea
Length/width ratio
4.4
4–8
Width/height ratio
4
3–6
Length/height ratio
17.7
Over 15
Velocity (m/sec)
0.0076
Below 0.0067
Wetted perimeter (m)
3
Reynolds number (Re)
18,091
Below 10,000
Froude number (Fr)
2.12 × 106
Over 1 × 106
Surface loading rate (m/d)
36.9
15–49
Weir loading rate (m3/m d)
229
Below 248
Upward velocity (m3/m d)
77.7
58.6–87.9
a large number of elements, collectively known as grids or cells. Then, momentum and continuity equations were formulated for each grid together with given boundary conditions and were repeatedly solved by using the finite volume method (Scilian et al. ; Park et al. ). In this simulation, about 70,000 cells for each case were generated. The time-averaged Navier–Stokes equations for
momentum and continuity were solved in this study for steady, incompressible, turbulent, and isothermal flow. The continuity and momentum equations are, respectively, ∇ ðU Þ ¼ 0
(2)
∇ ðρU ⊗ U μ∇U Þ ¼ B þ ∇P ∇ (ρu ⊗ u)
(3)
where ρ and μ are fluid density and dynamic viscosity, respectively; P is pressure; U is fluid mean velocity; B is body force; and u is fluctuating velocity. Turbulence modelling Although the Reynolds number in the sedimentation basin was higher than the 10,000 regulated by Korean standards, all cases were simulated by using turbulence modelling to investigate eddy flow and energy dissipation in greater detail. The Reynolds number is a ratio of inertia force to viscous force. The authors assumed that the turbulence in the basin was isotropic. Therefore, a standard k-ϵ model was used for modelling the turbulence transport of momentum (Suhas ; Versteeg & Malalasekera ).
N. S. Park et al.
1215
|
Effects of longitudinal baffles on particles settling in a sedimentation basin
Boundary conditions The liquid free surface at the top of the sedimentation basin, which is in contact with air, is considered flat and frictionless (i.e. a symmetry plane). Although some fluctuations occur at the free surface due to air friction, such inconsistencies are usually small enough to be neglected for the objectives of this study. At the side and bottom wall surface, a no-slip condition was assumed, and a widely used standard wall boundary method was applied to bridge the viscous sublayer. Therefore, it is assumed that each component’s
Figure 2
|
Water Science & Technology
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69.6
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2014
velocity at each wall is zero. The wall shear stress was obtained from the logarithmic law of the wall (Currie ; Versteeg & Malalasekera ).
RESULTS AND DISCUSSION Comparison of turbidity removal rates Figure 2(a) shows residual turbidities in effluents from Basins 3 and 6 under stable inlet flow rate conditions, as previously
Residual turbidities in effluents from Basins 3 and 6: (a) residual turbidities in effluents from Basins 3 and 6 under stably maintained inlet flow rate; (b) residual turbidities in effluents from Basins 3 and 6 under conditions of repeated shutting off and restarting.
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described, and the raw water turbidity measured between March 19 and 21, 2010, was below 10 nephelometric turbidity units (NTU). As shown in the figure, the stably maintained inlet flow rate resulted in an approximate 18% higher turbidity removal rate in Basin 3 over that in Basin 6. In addition, the average turbidities derived from Basins 3 and 6 were 0.49 and 0.60 NTU, respectively. Figure 2(b) shows the residual turbidities in effluents from the same basins under conditions of repeated shutting off and restarting. The curve represents the dramatic fluctuation in the flow rate. As shown in the figure, the turbidity removal rate from Basin 3 was approximately 38% higher than that from Basin 6 under unfavourable conditions. This result indicates that longitudinal baffles are effective even under highly erratic of flow rates. Distribution of sludge deposition To investigate the effects of longitudinal baffles on sludge distribution and depth, the deposited sludge remained in the tank for approximately four months. Each row of 34 sampling points was 1.2 m away from left and right wall sides. Figure 3 shows the sludge depth distribution in Basins 3 and 6. As shown in Figure 3, the total volume of sludge from Basin 6 was approximately 20% greater than that from Basin 3. This phenomenon is in contrast to the turbidity removal measurements. However, the suspended solids (SS) concentration in Basin 3 was 10% higher (2,000 mg/L) than that in Basin 6 (Table 3). These results
Figure 3
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Total volume of deposited sludge in Basins 3 and 6: (a) relationship of results obtained with different baffle types; (b) actual deposited sludge of both Basins measured on April 1, 2010.
Table 3
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Results of SS concentration measurement
SS concentration from Basin 3 (%)
SS concentration from Basin 6 (%)
0 (upper level)
1.6
1.9
1
2.3
2.0
2
2.4
2.0
3
2.4
2.1
4 (bottom level)
2.7
2.3
Average
2.3
2.1
Depth (m)
indicate that the total volume of sludge from Basin 3 was lower because the baffle contained the sludge more effectively.
Results of CFD simulations The comparative experiments revealed that the installation of a longitudinal baffle in a sedimentation basin improves settling efficiency. To further examine these results and investigate the effects of longitudinal baffles in greater detail, the authors conducted CFD simulations for both basins. Figure 4 shows the results for Basins 3 and 6 under an operating flow rate of 1,000 m3/hr. Figure 4 depicts the flow pattern within two basins with a velocity contour. In the case of the non-baffled basin, the dead zone, outlined by a dotted-line box, was relatively larger than that of the baffled basin. In contrast, the baffled basin overall exhibited a well-developed and stable flow. A comparison of both side views indicates that the velocity at the central plane in the case of the baffled basin is less than that in the case of the non-baffled basin. This result occurred because the longitudinal baffle worked as a noslip wall to reduce the overall velocity within the basin. Moreover, the red-coloured regions in Figure 4, which represent higher velocities, are relatively smaller in the case of the baffled basin. High velocity beneath launders creates an especially adverse effect on sedimentation. To further examine this condition, Figure 5 shows velocity vectors for each case in greater detail. Figure 5 illustrates the velocity vector of the flow pattern within each basin. Since the longitudinal baffle at the central plane in the baffled basin works as a no-slip wall, the authors selected plane intervals at 5 cm from central plane for this type of basin. As is evident in the figure, tiny arrows indicate the flow pattern (upward velocity distribution) beneath the
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Figure 4
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Effects of longitudinal baffles on particles settling in a sedimentation basin
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Simulation results showing velocity contour of flow patterns within each basin: (a) top view of Basin 3 (baffled; on left) and Basin 6 (non-baffled; on right); (b) side view of Basin 3 (baffled; lower diagram) and Basin 6 (non-baffled; upper diagram) showing flow pattern at the central plane. The full colour version of this figure is available online at http://www. iwaponline.com/wst/toc.htm.
Figure 5
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Simulation results of flow patterns within both basins highlighting the velocity vector with plane intervals of 5 cm from the central plane: (a) Basin 6 (non-baffled); (b) Basin 3 (baffled).
launder. In the case of the non-baffled basin, velocity was higher, and the flow pattern was more unstable than that observed in the case of the baffled basin. However, although a local high-velocity region was observed in the case of the baffled basin, the flow pattern beneath the launder showed greater stability.
CONCLUSIONS This study was conducted to evaluate the effects of longitudinal baffles on hydrodynamic behaviour within a certain fullscale sedimentation basin with a flow rate of 1,000 m3/hr. Comparative experiments were conducted on the turbidity removal efficiencies and sludge deposit distribution in longitudinally baffled and non-baffled sedimentation basins. Moreover, to explain these results and further investigate the effects of longitudinal baffles in greater detail, the authors performed CFD simulations for both basin types.
The findings of this study are summarized in the following points: (1) A comparison of the performances of baffled and nonbaffled basins revealed that under a stably maintained inlet flow rate, the turbidity removal rate from the baffled basin was approximately 18% higher than that from the non-baffled basin. In addition, the turbidity removal rate from the baffled basin was approximately 38% higher than that from the non-baffled basin under unfavourable, highly erratic flow rate conditions. These results indicate that longitudinal baffles effectively compensate for dramatic fluctuations in flow rate. (2) The investigation of distribution of sludge deposition within each basin revealed that the total volume of sludge from the non-baffled basin was approximately 20% greater than that from the baffled basin. However, the SS concentration from the baffled basin was 10% higher than that from the non-baffled basin. These
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results indicate that although the total volume of sludge from the baffled basin was smaller, the baffle was more effective in sludge removal. (3) From the results of CFD simulation, velocity was higher and the flow pattern was more unstable in the nonbaffled basin. However, although a local high-velocity region was observed in the case of the baffled basin, the flow pattern beneath the launder was more stable because the longitudinal baffle worked as a no-slip wall to reduce the overall velocity within the basin.
REFERENCES ANSYS CFX 11.0-Application Manual. Oxfordshire, UK. Currie, I. G. Fundamental Mechanics of Fluids. McGrawHill, New York. Jayanti, S. & Narayanan, S. Computational study of particle-eddy interaction in sedimentation tanks. ASCE, Journal of Environmental Engineering 130 (1), 37–49. Kawamura, S. Integrated Design of Water Treatment Facilities. John Wiley & Sons, Inc., Republic of South Korea. Korea Water Works Association Standard Guideline for Water Treatment Plant. Korea Ministry of Environment, Seoul, Korea.
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LeChevallier, M. W. Water Treatment and Pathogen Control. IWA Publishing, London, UK. Matko, T., Fawcett, A. Sharp & Stephenson, T. Recent progress in the numerical modelling of wastewater sedimentation tanks. Transactions of IChemE 74B, 245–257. Park, N., Park, H. & Kim, J. Examining the effect of hydraulic turbulence in a rapid mixer on turbidity removal with CFD simulation and PIV analysis. Journal of Water Supply: Research & Technology-AQUA 52 (2), 95–108. Park, N., Kim, J., Bae, C., Moon, Y. & Ahn, H. Identification and prioritization of performance limiting factors for water treatment plant optimization in Korea. Water Science and Technology: Water Supply 6 (2), 71–76. Scilian, J. M., Hirt, C. W. & Harper, R. P. FLOW-3D: Computational Modelling Power for Scientists and Engineers. Flow Science Report (FSI-87-00-1). Stovin, V. R. & Saul, A. J. Sedimentation in storage tank structure. Water Science and Technology 29 (1–2), 363–372. Stovin, V. R. & Saul, A. J. Efficiency prediction for storage chambers using computational fluid dynamics. Water Science and Technology 33 (9), 167–170. Suhas, V. P. Numerical Heat Transfer and Fluid Flow. McGraw-Hill, New York. Versteeg, H. K. & Malalasekera, W. An Introduction to Computational Fluid Dynamics. Prentice-Hall, New York. Vittal, N. & Ragahav, M. S. Design of single-chamber settling basins. ASCE, Journal of Environmental Engineering 123 (10), 469–471.
First received 5 November 2013; accepted in revised form 13 December 2013. Available online 30 December 2013
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