hydrodynamics of full scale annular ditches equipped with fine bubble EPDM membrane diffusers and slow speed mixers. Methods to measure bubble sizes, ...
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IN SITU LOCAL PARAMETER MEASUREMENTS FOR CFD MODELING TO OPTIMIZE AERATION Yannick Fayolle*, Sylvie Gillot*, Arnaud Cockx**, Michel Roustan** and Alain Héduit* * Cemagref, Unité HBAN, Parc de Tourvoie, BP 44, 92163 Antony Cedex, France ** INSA - Laboratoire d’Ingénierie des Procédés de l’environnement, Département G.P.I, 135 avenue de Rangueil, 31077 Toulouse Cedex 4, France
ABSTRACT Measurement methods to determine in situ local parameters were developed, in order to optimize design and operating parameters impacting oxygen transfer in aeration tanks equipped with EDPM membrane diffusers and slow speed mixers. New tools to measure bubble sizes and gas hold-ups were coupled with the traditional ones used to determine liquid velocities and oxygen transfer coefficients. These methods have been developed and applied to an annular loop reactor (1493 m3). Using an immersed camera, 100 bubbles are sufficient to determine the local Sauter diameter by image analysis. Obtained results are reproducible and independent of the operator. The gas hold-up, deduced from water level measurements with the help of a magnetostrictif level meter, can be determined with a confidence interval of ± 5% using an integration time of 380 s. The obtained increase in the oxygen transfer coefficient (+ 29%) with the horizontal liquid velocity (from 0 to 0.42 m/s) is mainly due to the increase of the global gas hold-up, the bubble size varying only slightly (from 0.46 to 0.43 cm). These results will be used as input data and validation data to model hydrodynamics and mass transfer, in order to set up a simulation methodology for aeration tanks using computational fluid dynamics. KEYWORDS Aeration tank, horizontal liquid velocity, bubble size, gas hold-up, wastewater treatment INTRODUCTION Aeration can represent up to 70% of the energy expenditure of an activated sludge wastewater treatment plant. Optimizing this process is therefore required to reduce operating costs, in addition to guaranty a reliable and efficient treatment. Since the last 20 years, fine bubble aeration systems have extensively been implemented. They proved to give high oxygenation performances, and to be adaptive to oxygen requirements. For loop reactors commonly installed in Europe, aeration is separated from mixing, carried out by slow speed mixers. To optimize aeration capacities, numerous on site results pointed out the main parameters impacting oxygen transfer (Groves et al., 1992; Wagner et al., 1998; Gillot et al., 2000; Mueller et al., 2002; Gillot et al., 2005). Relationships resulting from a dimensional analysis (Gillot et al., 2005) pointed out the difficulty in predicting the oxygen transfer in deep aeration tanks. This may be due to parameters that were not taken into account in the analysis (bubble diameters or mixer pumping areas, for example). More precise information on the local hydrodynamics of aeration tanks is therefore necessary in order to better understand the impact of design and operating parameters on oxygen transfer. At the same time, computational fluid dynamics (CFD) is more and more used to optimize aeration systems (Simon, 2000; Cockx et al., 2001; Vermande et al., 2003; Vermande et al., 2005). However, these studies are still facing a lack of in situ measurements of the local physical parameters that govern oxygen mass transfer and hydrodynamics, i.e. bubble size, gas hold-up and local liquid velocities. Some of this local data are essential for a robust modeling as input data (i.e. bubble size), the other Copyright ©2006 Water Environment Foundation. All Rights Reserved
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parameters allowing the validation process (i.e. oxygen transfer coefficient, gas hold-up, local liquid velocity). The objective of this work was therefore to develop measurement methods in order to characterize the hydrodynamics of full scale annular ditches equipped with fine bubble EPDM membrane diffusers and slow speed mixers. Methods to measure bubble sizes, gas hold-ups and horizontal liquid velocities have been developed and applied to an annular loop reactor (1 493 m3). Local parameter values are used to analyze the results obtained, concerning the impact of the horizontal velocity on oxygen transfer. MATERIAL AND METHOD Aeration tank The aeration tank is of annular type (V = 1 493 m3; Dout = 20.25 m; Din = 7.83 m; dw= 5.45m), and is equipped with six grids of 26 fine bubble EDPM membrane diffusers (tubes of 0.8 m length) and one large blades slow speed mixer (2.5 m diameter), mounted at the bottom of the tank (Figure 1). The tank was filled with tap water. Figure 1: Annular loop reactor Probe 1 Probe 2 Probe 3
Grid 2 εG and dbS measurement sections Probe 4 Probe 5 Probe 6
UL measurement section
Grid 4 Probe 7 Probe 8 Probe 9
where: εG is the gas hold-up, UL is the horizontal liquid velocity and dbS is the bubble Sauter diameter. Grids of diffusers are divided into two sections with a different density (10 tubes inside and 16 tubes outside). Experimental set-ups Bubble diameter: Bubble diameters were determined from images obtained by an immersed camera (Canon Powershot G6) located in the bubble plume (see Figure 2). Figure 2: Bubble size measurement tool
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The bubbles (Figure 3) are supposed to have an ellipsoid shape in clean water and an equivalent diameter dbi, defined as the diameter of a spherical bubble having the same volume as the ellipsoid. dbi is expressed as:
d bi = 3 a i2 .b i where: ai and bi are respectively the major and the minor axis of the ellipsoidal bubble i (m). Figure 3: Typical photo obtained in the bubble plume
The Sauter diameter is given as:
d bs =
∑n d ∑n d i
3 bi
i
2 bi
where: dbi is the equivalent diameter of the bubble i (m) and ni the number of bubbles having an equivalent diameter dbi. The measurements were performed on two sections above two different grids (see Figure 1) with and without mixing (note that the measurement sections were not changed with the horizontal velocity to follow the bubble plumes). On each measurement sections, bubble sizes were determined on 9 points regularly distributed on 3 water depths. The impact of the sample size on the Sauter diameter was also examined. Gas hold-up: On two sections of the tank (in the bubble plume, indicated on Figure 1), the water level was measured using a magnetostrictif level meter KTEK AT100, on 5 points on each section (1 to 5 m from the external wall). The sampling time was fixed to 1s. The gas hold-up (εG) was deduced from the water level as follows:
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εG =
H − H0 H
where: H0 and H are the liquid heights without and with aeration (m).
Interfacial area: the air-water interfacial area (a) is deduced from the measurement of the Sauter diameter and the gas hold-up as follows:
a=
6 εG d bs 1 − ε G
Horizontal liquid velocity: The horizontal liquid velocities were determined with and without aeration using a flow-meter on 30 points (corresponding to one point/m2 of section, Da Silva - Déronzier, 1994) in one section of the tank away from the bubble plume (see Figure 1). The sampling time was fixed to 1 s. The impact of the integration time was analyzed. Oxygen transfer coefficient: the oxygen transfer coefficient was determined in clean water according to the non-steady state method (ASCE, 1992; NF-EN-12255-15, 2004) on 9 points using nine dissolved oxygen probes (YSI 57), located on 3 water depths (1 m, 3 m and 5 m from the bottom of the tank), on 3 verticals (see Figure 1). RESULTS AND DISCUSSION Bubble size determination
Figure 4 shows a typical histogram of bubble size distribution obtained. The same type of distribution is observed on all the measurement points, without and with horizontal liquid velocity. Figure 4: Typical histogram of bubble size distribution (Grid 2, without mixing, distance from the diffusers = 1.25 m, distance from internal wall = 1 m) 45% 40%
Frequency (%)
35% 30% 25% 20% 15% 10% 5% 0% 0
0,1
0,2
0,3
0,4 0,5 0,6 Bubble size (cm)
0,7
0,8
0,9
1
This distribution is well described by a Gaussian law, usually obtained in bubble columns (Hebrard, 1995; Gillot, 1997; Capela, 1999; Painmanakul et al., 2004).
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The impact of the number of bubbles taken into account in the determination of the Sauter diameter on one measurement point is presented on Figure 5. Figure 5: Difference between the Sauter diameter calculated from Nb bubbles (dbS Nb) and the Sauter diameter obtained for the maximum bubble number (dbS Nbmax) 16% 14% UL = 0 m/s
UL = 0.42 m/s
dbS Nb/dbS Nbmax (%)
12% 10% 8% 6% 4% 2% 0% 0
50
100
150
200
250
Nb
The bubble size obtained with 100 bubbles gives a Sauter diameter close to the one obtained with around 200 bubbles (difference lower than 3 %) whatever the horizontal liquid velocity. This result corresponds to the numbers of bubbles generally taken into account for a Sauter diameter calculation in pilot scale bubble columns (Painmanakul et al., 2004; Bordel et al., 2006). Diameter values presented thereafter are therefore calculated with a minimum of 100 bubbles. In order to determine the reproducibility of the Sauter diameter calculation for a same operator as well as the sensitivity to the operator, the Kolmogorov-Smirnov test for samples of more than 40 values (NF-X06-065, 1971), is used. This test makes it possible to compare two continuous datasets. Each distribution is divided into 10 classes from 0 cm to 1 cm having the same limits. FA and FB represent the normalized cumulative frequencies until the higher limits of the classes and d, the difference FA-FB having the largest absolute value. The criterion C is defined by: n1n2 C=d n1 + n2 where d = max( FA − FB ) and n1, n2 are the number of values of each dataset. If C is lower or equal to 1.36 (with a risk of 5%), the two distributions can be considered as no significantly different. Several applications of this test are summarized in Table 1. Table 1: Test on the Sauter diameter determination for (a) repeatability (one operator) and (b) reproducibility (two operators) dbS (cm) Same operator Different operators
Case 1 Case 2 Case 1 Case 2
Result 1 0.4302 0.5357 0.4347 0.4271
Result 2 Result 3 0.4303 0.5463 0.5429 0.4410 0.4233 -
C1-2 0.26 0.38 1.08 0.85
C C1-3 C2-3 0.30 0.38 -
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All the C values are lower than 1.36, the Sauter diameter calculation can be considered as reproducible and independent of the operator. The global Sauter diameters on the observed grids were determined using all the bubble size on each measurement point (900 bubbles representing 100 bubbles for each measurement point). Global bubble size distribution without and with horizontal liquid velocity is represented on Figure 6 (Grid 2) and in Table 2. Figure 6: Bubble size distributions obtained on one grid without/with aeration (Grid 2, calculated from 9 points on 3 water depths) 45% 40% UL = 0 m/s
UL = 0.42 m/s
Frequency (%)
35% 30% 25% 20% 15% 10% 5% 0% 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Bubble size (cm)
Table 2: Standard deviation of bubble size distributions on 1 grid for 900 bubbles UL (m/s) 0 0.42
Grid 2 4 2 4
Standard deviation (cm) 0.0975 0.0838 0.0780 0.0794
Global bubble size distributions (9 points on 3 water depths and 3 verticals) present the same shape as bubble size distributions observed on one measurement point (see Figure 6). Bubble diameters are slightly dispersed. The horizontal liquid velocity lowers the standard deviation (see Table 2).
Gas hold-up determination On each measurement point, the water depth was recorded every second during about 5 minutes. Figure 7 presents the evolution of the water depth on one point without and with mixing. Figure 7: Water depth evolution without/with horizontal liquid velocity (grid 4, distance from internal wall = 2.2 m)
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UL = 0 m/s
UL = 0.42 m/s
Water depth (mm)
5540 5520 5500 5480 5460 5440 5420 0
50
100
150
200
250
300
350
Time (s)
Without mixing, the water depth varies between 5.444 m and 5.541 m, corresponding to a gas hold-up value from –0.10% to 1.65% (a negative value corresponding to a water depth lower than the reference water depth due to the presence of waves at the liquid surface). When the mixer is on, the water depth varies between 5.451 m and 5.480 m, corresponding to a hold-up value from 0.03% to 0.56%. The different ranges of water depth are explained by the vertical movements of the water caused by the rise of the air bubbles (spiral flows), producing strong eddies on the water surface, which are attenuated by the horizontal flow. Similar results have been obtained on all measurement points. In order to determine the integration time, an estimation of the error made as a function of the number of values taken into account is calculated. With the assumption that the individual measurements of the water depth can be considered as a sequence of independent and identically distributed random variables, each having a finite mean μ and variance σ2, the central limit theorem gives a 100(1-α)% confidence interval for the population mean μ (ISO2602, 1980):
s s ⎞ ⎛ ; X + t1−α ⎜ X − t1−α ⎟ n n⎠ ⎝ where X = the sample average, n = the sample size, s = the estimator of the standard deviation, and t1−α = the (1-α) percentile of the Student’s t-distribution (in our case, for α = 0.025, t1−α = 1.96).
s as a percentage of the average X , obtained while increasing the n sample size (corresponding to an increase in the integration time). Figure 8 represents the term t1−α
Figure 8: γ =
t1−α
s n versus integration time on one measurement point, without/with
X horizontal liquid velocity for each measurement grid
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UL (m/s)
Grid 2
Grid 4
0
20%
18%
18%
16%
16%
14%
14%
12%
12% γ (%)
γ (%)
20%
10%
10%
8%
8%
6%
6%
4%
4%
2%
2% 0%
0% 0
100
200
300
400
500
600
0
700
50
100
150
200
250
300
350
Time (s)
Time (s) 20%
12%
18% 10%
16% 14%
8% γ (%)
0.42
γ (%)
12% 10%
6%
8% 4%
6% 4%
2%
2% 0% 0
50
100
150
200
0%
250
0
50
Time (s)
100
150 200 Time (s)
250
300
350
A minimal integration time can be deduced in order to minimize the confidence interval of the average water depth. Without horizontal liquid velocity, the confidence interval is of ± 5% when the sampling time is longer than 380 s. With horizontal liquid velocity, a sampling time of 240 s is required. A more important precision could be obtained with a longer integration time. However, this time has to be fixed considering also the number of measurement points. 380 s seem therefore adequate to estimate the gas hold-up.
Local horizontal liquid velocity determination On each measurement point, the liquid velocity was recorded every second during about 3 minutes, without and with aeration. Figure 9 presents the evolution of the horizontal liquid velocity on one point without and with aeration. Figure 9: Horizontal liquid velocity versus time on one point, without and with aeration 0.650 Without aeration
With aeration
Horizontal liquid velocity (m/s)
0.600 0.550 0.500 0.450 0.400 0.350 0.300 0
50
100
150
200
250
300
Time (s)
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The horizontal liquid velocity varies between 0.383 m/s and 0.585 m/s without aeration, and between 0.311 m/s and 0.602 m/s with aeration. The difference in the interval range is due to the instabilities caused by aeration. Similar results have been obtained on the other measuring points. In order to determine the adequate integration time, a similar technique than the one applied to the water depth was used. Results are presented on Figure 10.
X
s n versus sampling time on one measurement point, without/with aeration
6%
6%
5%
5%
4%
4% γ (%)
γ (%)
Figure 10: γ =
t1−α
3%
3%
2%
2%
1%
1% 0%
0% 0
50
100
150
200
250
0
300
50
100
150
200
250
300
Time (s)
Time (s)
Without aeration
With aeration
Without aeration, in order to obtain a confidence interval between ± 2%, a sampling time of 60 s is enough. With aeration, a sampling time of 130 s is required. Considering the 30 measurement points, a integration time of 60 s has been chosen, corresponding to a confidence interval of ± 3%. Impact of the horizontal flow on bubble size and oxygen transfer
The effect of the horizontal flow on the Sauter diameter and on the oxygen transfer coefficient is summarized in Table 3. Oxygen transfer coefficients are expressed at a water temperature of 20°C:
k L aT = k L a20 ×1.024T −20 where kLaT the transfer coefficient at a temperature T; kLa20 the transfer coefficient at 20°C. Table 3: Sauter diameter and oxygen transfer coefficient as a function of the horizontal liquid velocity for the two measurement grids UL (m/s) kLa20 (h-1) Difference (%) Grid Global dbS (cm) 2 0.46 0 5.39 4 0.46 2 0.43 0.42 6.93 29% 4 0.43
When the average horizontal velocity was increased from 0 to 0.42 m/s, the oxygen transfer was enhanced by 29%. A similar increase was observed on pilot scale (Gillot et al., 2000; Simon, 2000) and on real site (Déronzier et al., 1998).
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The impact of horizontal liquid velocity on bubble size was studied on pilot scale (Gillot et al., 2000; Simon, 2000) but never on industrial size tanks. Independently of the location of the studied grid (see Figure 1), the global bubble size is of 0.43 mm for a horizontal velocity of 0.42 m/s in comparison to 0.46 mm without velocity (+ 5%). From a modeling point of view, the size of the bubbles produced by each grid is the same. In addition, the variation due to the horizontal liquid circulation is negligible. The enhancement of the oxygen transfer coefficient with the horizontal liquid velocity cannot be explained by the reduction of bubble size. Impact of the horizontal flow on the gas hold-up The gas hold-up profiles on the two grids are presented on Figure 11. Figure 11: Gas hold up profiles on 2 different grids with and without mixing 0.9%
Grid 2/UL=0m/s
Grid 2/UL=0.42m/s
0.8%
Grid 4/UL=0m/s
Grid 4/UL=0.42m/s
Gas hold-up (-)
0.7% 0.6% 0.5% 0.4% 0.3% 0.2% 0.1% 0.0% 0
1
2
3
4
5
6
Distance from internal wall (m)
The evolution of the gas hold-up without mixing could be linked to the dissymmetry of the grid in terms of diffuser density (see Figure 1). The horizontal velocity seems to inverse the shape of this profile. This impact will be further examined with the help of CFD. Average values of the gas hold-up (obtained by integration of the profile on the measurement section) and interfacial area are reported in Table 4. Table 4: Average gas hold-up and interfacial area on Grid 2 and 4 UL (m/s) 0 0.42
Grid 2 4 2 4
-1 Gas hold-up (%) Difference (%) Interfacial area (m ) Difference (%) 0.11% 1.3783 0.30% 3.9611 0.56% 431% 7.7172 460% 0.27% -12% 3.6212 -9%
Without mixing, for a given air flow rate, the gas hold-up on grid 2 is lower than on grid 4. The direct influence of the "spiral flows", created on both sides of the aerated zone, could explain this difference. Moreover, the horizontal liquid velocity doesn’t have the same influence on each grid. On grid 2, the gas hold-up strongly increases (+ 431%), whereas on grid 4, it slightly varies (- 12%). Grid 2 is more influenced by the horizontal liquid velocity than grid 4, located in the center of the aerated zone.
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The evolution of the local interfacial area is directly linked to the evolution of the gas hold-up. Although the liquid velocity has a strong impact on the interfacial area, no conclusion can be made on the influence of horizontal liquid velocity on the global interfacial area. Application to CFD modelling Local parameters determined in this study will be used to model the aeration tank hydrodynamics and oxygen transfer capacities as follows: 1. Bubble diameters will be considered as input data; 2. Gas hold-ups and horizontal velocities will allow to validate the hydrodynamic models; 3. A global interfacial area and the corresponding liquid phase mass transfer coefficient (kL) will be determined to validate the mass transfer models. Impact of the main design and operating parameters on oxygen transfer will finally be analyzed using the validated model. CONCLUSIONS
With the aim of characterizing the local hydrodynamics of aeration tanks, measurement methods were developed and tuned: -
100 bubbles are sufficient to determine the local Sauter diameter by image analysis. Obtained results are reproducible and independent of the operator; the gas hold-up, without and with mixing, can be determined with a confidence interval of ± 5% when the integration time of the water level measurement (every second) is longer than 380s; local horizontal liquid velocity, without and with aeration, can be determined with a confidence interval of ± 2% when the integration time of the velocity measurement (every second) is longer than 130 s. This time has to be fixed considering also the number of measurement points.
These methods were implemented on a tank of 1 493 m3. Velocity, bubble size, gas hold-up and oxygen transfer measurements were carried out. These measurements highlighted that: -
the order of magnitude of the bubble size is 0.45 cm. The bubble size doesn’t depend on the studied grid and varies slightly with the horizontal liquid velocity(- 5% when the horizontal liquid velocity varies from 0 to 0.42 m/s); the gas hold-up values measured above each grid are not subjected to the same influence of the horizontal liquid velocity. The first grids in the direction of the flow are subjected to a stronger impact on the gas hold-up (+ 431%) than the ones located in the centre of the aerated zone (– 12%). The oxygen transfer enhancement is principally due to this gas holdup increase.
In order to set up a simulation methodology of aeration tanks, these results will be used as input data (i.e. bubble sizes), and validation data to model the local hydrodynamics and the mass transfer (i.e. gas hold-up, liquid velocities and oxygen transfer coefficients). ACKNOWLEDGEMENTS
The authors would like to acknowledge Laetitia Bensimhon for her invaluable assistance during the data processing. They are also grateful to the persons who were involved in the measurements.
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REFERENCES
ASCE (1992). Standard measurement of oxygen transfer in clean water. American Society of Civil Engineers, 41 p. Bordel, S., R. Mato and S. Villaverde (2006). Modeling of the evolution with length of bubble size distributions in bubble columns. Chemical Engineering Science 61, pp. 3663-3673. Capela, S. (1999). Influence des facteurs de conception et des conditions de fonctionnement des stations d'épuration en boues activées sur le transfert d'oxygène. Thèse de doctorat, Université Paris XII - Val de Marne, 152 p. + annexes. Cockx, A., Z. Do-Quang, J. M. Audic, A. Liné and M. Roustan (2001). Global and local mass transfer coefficients in waste water treatment process by computational fluid dynamics. Chemical Engineering and Processing 40, pp.187-194. Da Silva - Déronzier, G. (1994). Eléments d'optimisation du transfert d'oxygène par aération en fines bulles et agitation séparée en chenal d'épuration. Thèse de doctorat, Université Louis Pasteur, Strasbourg, 119 p. + annexes. Déronzier, G., P. Duchène and A. Héduit (1998). Optimization of oxygen transfer in clean water by fine bubble diffused air system and separate mixing in aeration ditches. Water Science and Technology 28(3), pp. 35-42. Gillot, S. (1997). Transfert d'oxygène en boues activées par insufflation d'air - Mesure et élements d'interprétation. Thèse de doctorat, Université Paris XII - Val de Marne, 145 p. + annexes. Gillot, S., S. Capela-Marsal, G. Carrand, K. Wouters-Wasiak, P. Baptiste and A. Héduit (2005). Fine bubble aeration with EPDM membranes : coclusions from 15 years of pratice. IWA Specialized Conference Nutrient Management in Wastewater Treatment Processes and Recycle Streams, Krakow, Poland, pp. 607-616. Gillot, S., S. Capela-Marsal, M. Roustan and A. Héduit (2005). Predicting oxygen transfer of fine bubble diffused aeration systems - model issued from dimensional analysis. Water reseach 39, pp. 1379-1387. Gillot, S., S. Capela and A. Héduit (2000). Effect of horizontal flow on oxygen transfer in clean water with surfactants. Water reseach 34(2), pp. 678-683. Groves, K. P., G. T. Daigger, T. J. Simpkin, D. T. Redmon and L. Ewing (1992). Evaluation of oxygen transfer and alpha-factor on a variety of diffused aeration systems. Water Environment Research 64(5), pp. 691-698. Hebrard, G. (1995). Etude de l'influence du distributeur de gaz sur l'hydrodynamique et le transfert de matière gaz-liquide des colonnes à bulles. Thèse de doctorat, INSA, Toulouse, 174 p. + annexes. ISO2602 (1980). Statistical interpretation of test results - Estimation of the mean - Confidence interval. 5p. Mueller, J. A., B. W.C. and H. J. Pöpel (2002). Aeration: principle and practice. Water Quality Management Library, 353 p. NF-EN-12255-15 (2004). Wastewater treatment plants - Part 15: Measurements of the oxygen transfer in clean water in aeration tanks of activated sludge plants. NF-X06-065 (1971). Introduction à l'utilisation des tests statistiques - Comparaison de deux échantillons. 68p. Painmanakul, L. P., H. K. and B. G., P. (2004). Study of different membrane spargers used in waste water treatment : characterisation and performance. Chemical Engineering and Processing 43(11), pp. 1347-1359. Simon, S. (2000). Etude d'un chenal d'oxydation par des approches globales et locales Hydrodynamique et transfert de matière. Thèse de doctorat, INSA, Toulouse, 188 p. + annexes. Vermande, S., M. Chaumaz, S. Marsal, L. Dumoulin, K. Essemiani and J. Meinhold (2005). Modélisation numérique d'un bassin à grande profondeur. Récent progrès en Génie des Procédés 92, 8 p.
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Vermande, S., K. Essemiani, J. Meinhold, C. De Traversay and C. Fonade (2003). Trouble shooting of agitation in an oxidation ditch : Applicability of hydraulic modeling. 79th Annual Technical Exhibition and Conference WEFTEC'06, October 21-25, Dallas, USA. Wagner, M. R. and H. J. Pöpel (1998). Oxygen transfer and aeration efficiency - Influence of of diffuser submergence, diffuser density, and blower type. Water Science and Technology 38(3), pp. 1-6.
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