Travis Russell Watters and Travis Reed Miller

Transcription

1 Travis Russell Watters and Travis Reed Miller MIT Masters of Environmental and Water Quality Engineering Final Presentation, May 2010

2 Outline Project Overview Filter Performance Filter Durability Questions Results Recommendations Combined Recommendations Paraboloid Filter Flow Goal Goal Study Design Study Design Results Results

3 Project Overview Team Objective Recommend type of ceramic pot filter to manufacture Simultaneously optimized for flow rate, removal efficiencies, and durability Travis Reed Miller Investigate impact of design variables on coliform and turbidity removal, and flowrate Model flow of innovative paraboloid shape Travis Russell Watters Investigate impact of design variables on durability

4 Design Variables and Parameters Variable Parameter E. Coli Removal Total Coliform Removal Flowrate Turbidity Removal Strength Combustible Type Rice Husk Sawdust Addition of Grog Grog No Grog Low : 43-47% Combustible Volume Med: 51-54% High: 50-56% Additional Variables Sifting Shape

5 Filter Recipes Filter Combustible Hammermill Combustible Grog Recipe Type Product Amount Added Shape 1 Rice Husk Fine & Waste Low No Flower Pot 2 Rice Husk Fine & Waste Low Yes Flower Pot 3 Rice Husk Fine & Waste Medium No Flower Pot 4 Rice Husk Fine & Waste Medium Yes Flower Pot 5 Rice Husk Fine & Waste High No Flower Pot 6 Rice Husk Fine & Waste High Yes Flower Pot 7 Sawdust Fine & Waste Low No Flower Pot 8 Sawdust Fine & Waste Low Yes Flower Pot 9 Sawdust Fine & Waste Medium No Flower Pot 10 Sawdust Fine & Waste Medium Yes Flower Pot 11 Sawdust Fine & Waste High No Flower Pot 12 Sawdust Fine & Waste High Yes Flower Pot 13 Sawdust Fine, Sifted Low No Flower Pot 14 Rice Husk Fine, Sifted Low No Flower Pot 15 Rice Husk Fine & Waste Low Yes Paraboloid

6 Outline Project Overview Filter Performance Filter Durability Questions Results Recommendations Combined Recommendations Paraboloid Filter Flow Goal Goal Study Design Study Design Results Results

7 Filter Performance Study Design

8 Analysis Statistical analysis of data T-tests to estimate difference between population means Influence of design variables on performance Relatedness of duplicate filters T-tests to test difference between population means Ranking of filters for recommendation

9 Impact of Combustible Type: E. coli Count 25 E. coli in Filtered Water 20 E. coli (CFU/100 ml) A 1B 2A 2B 3A 3B 4A 4B 5A 5B 6A 6B 7A 7B 8A 8B 9A 9B 10A 10B 11A 11B 12A 12B 13A 13B 14A 14B 15A 15B Conformity Low Intermediate

10 Impact of Combustible Type: Total Coliform Log Removal Total Coliform LRV Rice Husk Sawdust Statistically significant difference

11 Impact of Combustible Type: Flowrate Flow Rate (L/Hour) Rice Husk Sawdust Statistically significant difference

12 Impact of Combustible Type: Turbidity Removal 100% 80% 60% Turbidity Reduction (%) 40% 20% 0% Rice Husk Sawdust -20% -40% Statistically significant difference

13 Impact of Addition of Grog: Total Coliform Removal Total Coliform LRV Without Grog Grog Statistically not significant difference

14 Impact of Addition of Grog: Flowrate Flow Rate (L/Hour) Without Grog Grog Statistically not significant difference

15 Impact of Addition of Grog: Turbidity Removal 100% 80% 60% Turbidity Reduction (%) 40% 20% 0% Without Grog Grog -20% -40% Statistically not significant difference

16 Impact of Mass of Combustible: Total Coliform Removal Increasing Mass Increasing Mass Total Coliform LRV Rice Husk Sawdust

17 Impact of Mass of Combustible: Flowrate Increasing Mass Increasing Mass Flow Rate (L/Hour) Rice Husk Saw Dust

18 Impact of Mass of Combustible: Turbidity Removal 1 Increasing Mass Increasing Mass 0.8 Turbidity Reduction (%) Rice Husk Sawdust

19 Impact of Additional Variables Hammermilled and sifted combustible material reduces flowrate Paraboloid shape reduces flowrate by 0.2 to 0.6 L/hr

20 Design Variables and Parameters Variable Parameter Key: + Variable increases parameter -- Variable decreases parameter 0 No effect E. Coli Removal Total Coliform Removal Flowrate Turbidity Removal Strength Combustible Type Addition of Grog Combustible Volume Additional Variables Rice Husk Sawdust Grog No Grog Low : 43-47% Med: 51-54% High: 50-56% Sifting Shape 0 0-0

21 Outline Project Overview Filter Performance Filter Durability Questions Results Recommendations Combined Recommendations Paraboloid Filter Flow Goal Goal Study Design Study Design Results Results

22 Paraboloid Filter Flow Goal Derive equation to represent flow through paraboloid filter based on Darcy s law Test to see if hydraulic conductivity is homogenous throughout filter

23 Drawdown Test

24 Determining Radii

25 Results: Flowrate Model Flowrate model in terms of z, height with Darcy s Law Q is the flowrate c is the coefficient relating the change in radius with height, r=cz 1/2 K is the hydraulic conductivity t is the thickness H w is the height of the water

26 1.Determining Weighted Ave. K Three methods were used to determine K with height Using the drawdown data, the weighted average K was found for each interval measured by fitting the model to the measured flowrate

27 2.Determing K: Three Segments The hydraulic conductivity of three large segments was calculated using drawdown data

28 3.Determing K of Filter Slices The filter was cut into 6 slices, and the flow through each was measured and modeled

29 3.Determining K of Filter Slices The slices were attached to the bottoms of buckets with holes cut out, and placed inside containers Bucket Clear Container Filter Slice Styrofoam Support

30 Results: Hydraulic Conductivity Hydraulic Conductivity constant, ~0.22 cm/hr Interval 12cm - 18cm Interval 6cm - 12cm Weighted Average, Constant Thickness, Section Weighted Average, Variable Thickness, Section Segments, Section Interval 0cm - 6cm Filter Slices, Section Average Interval Hydraulic Conductivity (cm/hr)

31 Determining Total Porosity The total porosity, V voids /V filter of the filter slices was also determined V voids = M Saturated - V Dry V filter was found by displacement of water Wood Beam Scale Support Strings Water Level Filter Slice Wire Rack Support

32 Results: Porosity of Filter Slices 50% 49% 48% Filter Slice Total Porosity (%) 47% 46% 45% 44% 43% 42% 41% 40% Average Height of Filter Slice (cm)

33 Outline Project Overview Filter Performance Filter Durability Questions Results Recommendations Combined Recommendations Paraboloid Filter Flow Goal Goal Study Design Study Design Results Results

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37 250 Load vs. Time for Sample Break Test 1A Load (Newtons) Time (s)

38 Questions How Does Combustible Mass Affect Bending Strength?

39 Mean Modulus of Rupture vs. Combustible Mass Rupture Modulus (Mpa) Combustible Mass (kg) Rice Husk, No Grog Rice Husk, Grog Sawdust, No Grog Sawdust, Grog

40 Comparison of Mean Modulus of Rupture Between Recipes with Incrementally Differing Combustible Mass, 95% Confidence Test t T.05 t>t.05? 1> FALSE 2> FALSE 3> TRUE 4> TRUE 7> TRUE 8> TRUE 9> TRUE 10> TRUE

41 Questions How Does Combustible Mass Affect Bending Strength? In general, increasing the mass of combustible causes a decrease in bending strength.

42 Questions How Does the Inclusion of Grog Affect Bending Strength?

43 Mean Modulus of Rupture vs. Combustible Mass: Sawdust With/Without Grog Rupture Modulus (Mpa) Combustible Mass (kg) Sawdust, No Grog Sawdust, Grog

44 Mean Modulus of Rupture vs. Combustible Mass: Rice Husk With/Without Grog Rupture Modulus (Mpa) Combustible Mass (kg) Rice Husk, No Grog Rice Husk, Grog

45 Comparison of Mean Modulus of Rupture Between Recipes With and Without Grog, 95% Confidence Test t T.05 t>t.05? 1> FALSE 3> FALSE 6> FALSE 7> FALSE 10> FALSE 11> TRUE

46 Questions How Does the Inclusion of Grog Affect Bending Strength? In general, the inclusion of grog does not statistically significantly impact bending strength.

47 Questions Which is Stronger in Bending Recipes with Sawdust or Recipes with Rice Husk?

48 Mean Modulus of Rupture vs. Combustible Mass Rupture Modulus (Mpa) Combustible Mass (kg) Rice Husk, No Grog Rice Husk, Grog Sawdust, No Grog Sawdust, Grog Linear (Rice Husk, No Grog) Linear (Rice Husk, Grog) Linear (Sawdust, No Grog) Linear (Sawdust, Grog)

49 Comparison of Mean Modulus of Rupture for Recipes Containing Similar Masses of Different Combustible Types, 95% Confidence Test t T.05 t>t.05? 9> FALSE 10> TRUE

50 Questions Which is Stronger in Bending Recipes with Sawdust or Recipes with Rice Husk? Statistically significant conclusions cannot be drawn from the available data.

51 Questions How does the Bending Strength of the Recipes Compare Overall?

52 Rupture Modulus vs. Combustible Mass: All Recipes Rupture Modulus (Mpa) Combustible Mass (kg) Rice Husk, Grog Sawdust, No Grog Sawdust, Grog Recipe 13 Recipe 14

53 Simple Rank Ordering of Mean Modulus of Rupture Recipe # Rank R mean (Mpa) % Confidence Tiered Rank Ordering of Mean Modulus of Rupture Recipe #s Rank Stronger Than: ,7, , ,4, ,5 8 None

54 Questions How does the Bending Strength of the Recipes Compare Overall? Recipes 13 and 14, whose manufacturing process included only fine materials, are strongest. There is a generally decreasing trend in strength as combustible mass is added. Recipes 6 and 5, containing the greatest combustible mass, are weakest.

55 Questions How do the Observed Bending Strengths Compare to Common Loading Conditions?

56 Modeling of Common Loading Condition

57 Model of the Loading Condition of the Filter Lip

58 Resultants

59 Comparison of Lower Bound of 95% Confidence Interval for Mean Modulus of Rupture to Expected Bending Stress Recipe # Lower Bound (Mpa) >0.45Mpa (Full Pot)? >.20Mpa (Empty Pot)? YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES YES

60 Probability that the Modulus of Rupture of a Particular Sample from a Given Recipe will be Less than the Expected Bending Stress Arising from A Full Water Load Recipe # Probability that R <.45 Mpa

61 Questions How do the Observed Bending Strengths Compare to Common Loading Conditions? The expected bending loads are far below the lower bound of the mean bending strength of the tested recipes (weakest mix: 1 Mpa > 0.45 Mpa) The maximum probability of failure under expected loading conditions is (4.2%). Rate of breakage reported in Ghana is 0.11 (11%).

62 Questions How Does Thickening the Lip Affect the Maximum Allowable Moment?

63 Moment at Rupture vs. Beam Thickness 6.0E E+03 Moment at Rupture (Nmm) 4.0E E E E+03 y = 1.2x 2.6 R² = 0.89 Rwt M critical = 6 2 y = 6.5x 2 R² = 1 0.0E Thickness (mm) Experimental Theoretical Power (Experimental) Power (Theoretical)

64 Comparison of Allowable Moment for Samples of Varying Thickness, 95% Confidence Test t T.05 t>t.05? M max,medium >M max,thin TRUE M max,thick >M max,medium TRUE

65 Questions How Does Thickening the Lip Affect the Maximum Allowable Moment? The maximum allowable moment increases with at least the square of the thickness

66 Questions What is the Effect of Kiln Position on Bending Strength?

67 Schematic of Kiln Loading (Left) and Photograph of Pyrometric Cones after Firing with Relative Positions Preserved (Right)

68 Modulus of Rupture vs. Combustible Mass: Organized by Kiln Position 6.0E E+00 Modulus of Rupture 4.0E E E+00 Linear (A) Linear (B) Linear (C) Linear (D) Linear (E) Linear (F) Linear (G) Linear (H) Linear (I) 1.0E E Combustible Mass (kg)

69 Questions What is the Effect of Kiln Position on Bending Strength? Samples fired to a higher maturity exhibit generally greater bending strength than samples fired to a lesser maturity. In a particularly dramatic case, recipe #1 exhibited a 3.6- fold increase in strength in position E as compared to position H

70 Recommendations Geometry It is recommended that the filter lip be thickened to 25mm. This will increase shear capacity by 66% and moment capacity by 180% with a 10% material increase. Firing After first four hours, witness cones in door and spyhole must be checked hourly. Once guide cone bends, cones must be checked every fifteen minutes. Communication must be maintained with consultant Manny Hernandez to alter kiln configuration until sufficiently even heating is attained. Being that shear and bending are well beyond the expected loads, control of this variable may be key to filter durability

71 Outline Project Overview Filter Performance Filter Durability Questions Results Recommendations Combined Recommendations Paraboloid Filter Flow Goal Goal Study Design Study Design Results Results

72 Variable Design Variables and Parameters Combustible Type Addition of Grog Combustible Volume Parameter E. Coli Removal Total Coliform Removal Flowrate Turbidity Removal Rice Husk Sawdust Strength Higher, stronger Lower, stronger Sum Grog o No Grog Low : 43-47% Med: 51-54% High: 50-56% Key: + Variable increases parameter -- Variable decreases parameter 0 No effect Additional Sifting

73 Variable Design Variables and Parameters Combustible Type Addition of Grog Combustible Volume Parameter E. Coli Removal Total Coliform Removal Flowrate Turbidity Removal Rice Husk Sawdust Strength Higher, stronger Lower, stronger Grog o No Grog Low : 43-47% Med: 51-54% High: 50-56% Key: + Variable increases parameter -- Variable decreases parameter 0 No effect Sum Additional Sifting

74 Combined Ranking System Total Coliform Removal E. coli Flowrate Strength

75 Combined Ranking System Tier 1 &2 Filters: 2, 3, 5 and 14 Flowrate: 5>3>2>14 Filter 14 difficult to make due to sifting Filter 5 is weak Choose Filter 3 Tier 3 Filters: 1, 4, 6, 15 Flowrate: 6>4>1>15 Filter 6 is weak Choose Filter 4 Paraboloid shape of 15 acceptable

76 Recommendations to PHW Filter design, based on 3 and 4 Rice Husk Medium Volume 51%-54% of total mix volume Hammer-milled only Not sifted ~10% Grog by mass if desired by potters for shrinkage No effect Paraboloid or Flower Pot filters Coagulate to remove further turbidity

77 Acknowledgments Emmanuel Hernandez kiln and press designer Dr. Jack Germaine adviser for clay characterization Dr. Krystyn Van Vliet adviser for structural analysis Dr. Tomasz Wierzbicki adviser for structural analysis Stephen Rudolph adviser for structural experiments Thomas Hay partner in factory construction Leah Nation partner in factory construction Lydia Senanu laboratory technician for Miller s study All Pure Home Water Management and Staff Gbalhai women potters Abiba, Semata, Selamatu

78 The End.