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Use Slide Show (F5) in PowerPoint A New Correlation Equation for Predicting Single-Collector Efficiency in Physicochemical Filtration in Saturated Porous.

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Presentation on theme: "Use Slide Show (F5) in PowerPoint A New Correlation Equation for Predicting Single-Collector Efficiency in Physicochemical Filtration in Saturated Porous."— Presentation transcript:

1 Use Slide Show (F5) in PowerPoint A New Correlation Equation for Predicting Single-Collector Efficiency in Physicochemical Filtration in Saturated Porous Media Tufenkji, N. and Elimelech M. “Correlation Equation for Predicting Single-Collector Efficiency in Physicochemical Filtration in Saturated Porous Media”, Environmental Science and Technology, 2004, Vol. 38, Nathalie Tufenkji Menachem Elimelech Department of Chemical Engineering Environmental Engineering Program Yale University

2 Outline Background and Motivation Development of Correlation Equation
Comparison to Current Approaches and Experimental Data Implications

3 Background and Motivation
Transport and fate of colloidal particles in saturated porous media In-situ bioremediation Riverbank filtration Deep-bed granular filtration Tufenkji, Ryan and Elimelech, ES&T, 2002.

4 Background and Motivation
Transport Mechanisms in Filtration A Collector B C A. Sedimentation B. Interception C. Brownian Diffusion

5 Background and Motivation
Limitations of Current Approaches Yao, Habibian and O’Melia, 1971, ES&T (5) 1105. First model suggesting 3 mechanisms are additive Do not consider: (i) hydrodynamic interactions (HI) (ii) van der Waals attractive forces (vdW) Rajagopalan and Tien, 1976, AIChE J (22) 523. Improved YHO model, however, has several limitations Omitted HI and vdW forces for mechanism of Brownian diffusion

6 Development of Correlation Equation
Governing Equation and Boundary Conditions

7 Development of Correlation Equation
Determination of Single-Collector Contact Efficiency I Dimensionless Parameters Governing Filtration

8 Development of Correlation Equation
Dimensionless Parameters Governing Filtration

9 Development of Correlation Equation
General Approach – Additivity Assumption Parameter Values 0.01 < dp < 10 m 0.05 < dc < 0.50 mm 7 x 10-6 < U < 2 x 10-3 m/s 3 x < A < 4 x J 1.0 < p < 1.8 g/cm3 T = 298 K f = 0.36

10 Development of Correlation Equation
General Approach – Additivity Assumption Correlation for D “Turn off” mechanisms of interception and gravity Calculate D numerically over range of NR, NPe, and NvdW

11 Development of Correlation Equation
General Approach – Additivity Assumption Correlation for I “Turn off” mechanism of gravity Calculate over range of NR, NPe, and NvdW

12 Development of Correlation Equation
General Approach – Additivity Assumption Correlation for G Calculate over range of NR, NPe, NvdW, and Ngr

13 Development of Correlation Equation
General Approach – Additivity Assumption

14 Development of Correlation Equation
General Approach – Additivity Assumption D

15 Development of Correlation Equation
General Approach – Additivity Assumption I

16 Development of Correlation Equation
General Approach – Additivity Assumption G

17 Development of Correlation Equation
General Approach – Additivity Assumption 0 dp (m) Subsurface transport U = 9 x 10-6 m/s

18 Development of Correlation Equation
General Approach – Additivity Assumption Bank filtration U = 4 x 10-5 m/s 0 0 dp (m) (m) dp (m) (m) Subsurface transport U = 9 x 10-6 m/s

19 Deep-bed granular filtration
Development of Correlation Equation General Approach – Additivity Assumption Bank filtration U = 4 x 10-5 m/s Deep-bed granular filtration U = 2.8 x 10-3 m/s 0 0 dp (m) (m) dp (m) (m) dp (m) (m) Subsurface transport U = 9 x 10-6 m/s

20 Comparison to RT Equation
Major Limitation (1) Overestimates  over wide range of dp in Brownian regime Conditions: dc = 0.40 mm U = 8 x 10-6 m/s f = 0.36 A = 1 x J p = 1.05 g/cm3 T = 288 K 0 ~ 50% difference dp (m)

21 Comparison to RT Equation
Major Limitations (2) Increased deviation for microbial particles in Brownian regime Apolio virus - quartz ≈ x J Asilica - quartz ≈ 1 x J

22 Comparison to RT Equation
Major Limitations (2) Increased deviation for microbial particles in Brownian regime Apolio virus - quartz ≈ x J Asilica - quartz ≈ 1 x J Conditions: dc = 0.40 mm U = 8 x 10-6 m/s f = 0.36 A = 3 x J p = 1.05 g/cm3 T = 288 K 0 ~ 60% difference (m)

23 Unique Features of Correlation Equation

24 Unique Features of Correlation Equation
Include HI and vdW forces on transport by diffusion

25 Unique Features of Correlation Equation
Include HI and vdW forces on transport by diffusion Transport by gravity is not a strong function of porosity

26 Unique Features of Correlation Equation
Include HI and vdW forces on transport by diffusion Transport by gravity is not a strong function of porosity Include influence of vdW forces in gravity term

27 Comparison with Experimental Data
Data taken from well-controlled column experiments, under favorable conditions, using uniform spherical latex particles and glass beads YHO Model EXP YHO slope = 0.34

28 Comparison with Experimental Data
Data taken from well-controlled column experiments, under favorable conditions, using uniform spherical latex particles and glass beads YHO Model RT Model EXP YHO RT slope = 0.34 slope = 0.74

29 Comparison with Experimental Data
Data taken from well-controlled column experiments, under favorable conditions, using uniform spherical latex particles and glass beads YHO Model RT Model TE Model EXP YHO RT TE slope = 0.90 slope = 0.34 slope = 0.74

30 Implications Accurate predictions of colloid filtration behavior are critical in several processes in natural and engineered systems Predictions of  with TE equation show remarkable agreement with exact theoretical values Experimental data are in much closer agreement with predictions based on TE equation in comparison to current approaches

31 Acknowledgements Natural Sciences and Engineering Research Council of Canada (NSERC) National Science Foundation (NSF) US EPA


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