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MEC E 668: Design of Experiment
Instructor: Professor Kajsa Duke
Final Project
by
Monisha Alam
Supervisor: Dr. Zaher Hashi...
Introduction
• Volatile organic compounds
(VOCs) emitted from car painting
solvents in automobile industries
cause indoor ...
Introduction
• ACC used for 1 adsorption cycle: spent ACC
• Spent ACC reused for economic purpose
• Regeneration (VOCs are...
Introduction
Successful regeneration indicates:
• Minimum Heel (residual amount of strongly adsorbed VOCs
on ACC)
• Maximu...
• Spent ACC samples wrapped in hollow cylinder shape
(1.65 cm inner diameter, 10 cm length)
• Two stainless steel electrod...
Experimental Setup
6
Thermocouple
Quartz
Reactor
3 Layered
ACC
Electrode
Tube
Application of
Heat
Flow of N2
Measurement of Heel & Pore Volume
7
Measuring Heel
Measuring
Pore Volume
% of Heel =
Mreg = Mass of regenerated ACC
MV = M...
Stage 1: Full Factorial Design
Screening Test with experimental &
made-up data
• Responding Variables
1. Amount of heel: <...
Stage 1: Full Factorial Design
Low (-) High (+)
1. Kinetic diameter (nm) 0.3 0.8
2. Molecular weight (g/mole) 80 140
3. He...
Stage 1: Full Factorial Design-Results
10
Pareto Chart of Standardized Effects: % of Heel - H
p=.05
(5)N2 Flow Rate-E
3by4...
Stage 1: Full Factorial Design-Results
11
Pareto Chart of Standardized Effects: Pore Volume - V
p=.05
4by5
3by5
1by5
2by4
...
Stage 2: Central Composite Design
12
Responding Variables Objective Acceptable Range
i Percentage of Heel (%) To minimize ...
Central Composite Design: Results
13
Pareto Chart of Standardized Effects: % of Heel-H
p=.05
1Lby3L
1Lby2L
2Lby3L
Molecula...
Central Composite Design: Results
14
Pareto Chart of Standardized Effects: Pore Volume-V
p=.05
2Lby3L
1Lby2L
Kinetic Diame...
Central Composite Design: Surface Plots – % of Heel
15
Central Composite Design: Surface Plots–Pore Volume
16
Central Composite Design: Regression Model
For Engineering Values
• Percentage of Heel, H = 68.135 – 71.840 Ae + 169.60 Ae...
Fitted Surface: Pore Volume-V
> 1.1
< 1.1
< 1
< 0.9
< 0.8
< 0.7
< 0.6
< 0.5
-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0
Kineti...
Central Composite Design: Optimum Results
19
Favorable Regions
MATLAB optimum results (coded values):
Molecular Weight = -...
Central Composite Design: Optimum Results
20
Favorable Regions
MATLAB optimum results (coded values):
Kinetic Diameter = -...
Discussions
• VOCs properties (molecular weight & kinetic diameter) more
significant than process parameters (heating dura...
Conclusions
• Heel minimized & Pores maximized for moderately high regeneration
temperature, lower molecular weight & smal...
23
• Professor Kajsa Duke
• Professor Zaher Hashisho & all my colleagues from Air
Quality Control group
• Ford Motor Compa...
24
1. Kim, B. R., 2011, “VOC emissions from automotive painting and their
control: A review”, Environ. Eng. Res., 16 (1), ...
25
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  1. 1. MEC E 668: Design of Experiment Instructor: Professor Kajsa Duke Final Project by Monisha Alam Supervisor: Dr. Zaher Hashisho Design of Experiments to Optimize the Regeneration Process of Spent Activated Carbon Cloth by Resistive Heating Method
  2. 2. Introduction • Volatile organic compounds (VOCs) emitted from car painting solvents in automobile industries cause indoor air pollution • Activated carbon cloth (ACC) • highly porous material, used as adsorbent • adsorbs (VOCs) on surface & inside pores 2 http://northharfordcollision.net/wp-content/uploads/2013/06/car-painting.jpg
  3. 3. Introduction • ACC used for 1 adsorption cycle: spent ACC • Spent ACC reused for economic purpose • Regeneration (VOCs are removed from pores of ACC) for economical reuse • Resistive heating: higher heating rate, fast desorption • To find optimized regeneration conditions: • “Factorial Design”: deals with several factors at a time • “Best-guess” : inefficient due to inadequate previous study • “One-factor-at-a-time”: lengthy, costly, no interaction 3
  4. 4. Introduction Successful regeneration indicates: • Minimum Heel (residual amount of strongly adsorbed VOCs on ACC) • Maximum Pore Volume available for adsorption Objective: To identify optimum conditions to obtain regenerated ACC that contains: • heel (< 5 wt% of the virgin ACC) • pore volume (≥ 0.8 cm3/g) 4
  5. 5. • Spent ACC samples wrapped in hollow cylinder shape (1.65 cm inner diameter, 10 cm length) • Two stainless steel electrode tubes, with heating elements Materials and Methods 5 Regeneration CartridgeSpent ACC
  6. 6. Experimental Setup 6 Thermocouple Quartz Reactor 3 Layered ACC Electrode Tube Application of Heat Flow of N2
  7. 7. Measurement of Heel & Pore Volume 7 Measuring Heel Measuring Pore Volume % of Heel = Mreg = Mass of regenerated ACC MV = Mass of virgin ACC (MReg – MV ) / MV x 100%
  8. 8. Stage 1: Full Factorial Design Screening Test with experimental & made-up data • Responding Variables 1. Amount of heel: < 5% 2. Pore volume: ≥ 0.8 cm3/g • Controlled Variables 1. Heating rate: 10 °C/min 2. Electrode Tubes: 1.65 cm dia • Nuisance Factors 1. Batch of ACC 2. Voltage generator 8 6.8 6.82 6.84 6.86 6.88 6.9 0 1 2 3 4 5 6 PercentageofHeel Batch of ACC Percentage of Heel vs. batches 0.722 0.724 0.726 0.728 0.73 0 1 2 3 4 5 6 PoreVolume Batch of ACC Pore Volume vs. batches Effects of Nuisance Variables
  9. 9. Stage 1: Full Factorial Design Low (-) High (+) 1. Kinetic diameter (nm) 0.3 0.8 2. Molecular weight (g/mole) 80 140 3. Heating temperature (°C) 60 260 4. Heating duration (h) 1 3 5. Nitrogen flow rate (L/min) 1 3 No. of runs = 25 = 32 9 Manipulated Variables
  10. 10. Stage 1: Full Factorial Design-Results 10 Pareto Chart of Standardized Effects: % of Heel - H p=.05 (5)N2 Flow Rate-E 3by4 2by5 2by4 3by5 2by3 (1)Kinetic Diameter-A (2)Molecular Weight-B (3) Heating Temperature-C (4) Heating Duration-D
  11. 11. Stage 1: Full Factorial Design-Results 11 Pareto Chart of Standardized Effects: Pore Volume - V p=.05 4by5 3by5 1by5 2by4 1by2 1by4 (3)Heating Temp.-C (2)Molecular Weight-B (1) Kinetic Diameter- A 1 by 3
  12. 12. Stage 2: Central Composite Design 12 Responding Variables Objective Acceptable Range i Percentage of Heel (%) To minimize < 5 ii Pore Volume Recovered (cm3/g) To maximize > 0.8 Manipulated Variables -1.682 -1 0 +1 +1.682 A Adsorbates Kinetic Diameter (nm) 0.22 0.25 0.30 0.35 0.38 B Adsorbates Molecular Weight (g/mole) 46.4 60 80 100 113.6 C Heating Temperature (°C) 226.4 240 260 280 293.6 Controlled Variables Set Conditions 1 Heating Duration (h) 1 2 Nitrogen Flow Rate (L/min) 1 3 Heating Rate (C/min) 10 4 Electrode Tube 1.65 cm dia Curvature effects, surface response, 5 levels, No. of runs: 16
  13. 13. Central Composite Design: Results 13 Pareto Chart of Standardized Effects: % of Heel-H p=.05 1Lby3L 1Lby2L 2Lby3L Molecular Weight-B(Q) Heating Temp.-C(Q) Kinetic Diameter-A(Q) (3)Heating Temp.-C(L) (1)Kinetic Diameter-A(L) (2)Molecular Weight-B(L)
  14. 14. Central Composite Design: Results 14 Pareto Chart of Standardized Effects: Pore Volume-V p=.05 2Lby3L 1Lby2L Kinetic Diameter-A(Q) 1Lby3L Molecular Weight-B(Q) Heating Temp.-C(Q) (3)Heating Temp.-C(L) (1)Kinetic Diameter-A(L) (2)Molecular Weight-B(L)
  15. 15. Central Composite Design: Surface Plots – % of Heel 15
  16. 16. Central Composite Design: Surface Plots–Pore Volume 16
  17. 17. Central Composite Design: Regression Model For Engineering Values • Percentage of Heel, H = 68.135 – 71.840 Ae + 169.60 Ae 2 + 0.091 Be – 0.456 Ce + 0.0008 Ce 2 • Pore Volume, V = – 4.3724 – 44.7958 Ae + 92.9736 Ae 2 + 0.0311 Be – 0.0009 Be 2 + 0.0818 Ce – 0.000155 Ce 2 – 0.020039 Ae Be – 0.0241919 Ae Ce 17 A = kinetic diameter, B = molecular weight, C = heating temperature. Subscript “c” : coded value, “e” : engineering value. Factors Relationships (coded to engineering) Kinetic Diameter Ae = 0.0482 Ac + 0.3 Molecular Weight Be = 19.982Bc + 80 Heating Temperature Ce = 19.982Cc + 260
  18. 18. Fitted Surface: Pore Volume-V > 1.1 < 1.1 < 1 < 0.9 < 0.8 < 0.7 < 0.6 < 0.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Kinetic Diameter-A -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 MolecularWeight-B Central Composite Design: Optimum Results 18 Fitted Surface: % of Heel-H > 8 < 8 < 7 < 6 < 5 < 4 < 3 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Kinetic Diameter-A -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 MolecularWeight-B Heel < 5% Favorable Regions MATLAB optimum results (coded values): Kinetic Diameter = -0.44 Molecular Weight = -0.03 Heel = 4.07%, Pore Volume = 0.82 cm3/g Pore Volume ≥ 0.8 cm3/g
  19. 19. Central Composite Design: Optimum Results 19 Favorable Regions MATLAB optimum results (coded values): Molecular Weight = -0.03, Heating Temperature= -0.07 Heel = 4.07%, Pore Volume = 0.82 cm3/g Fitted Surface: Pore Volume-V > 1 < 1 < 0.9 < 0.8 < 0.7 < 0.6 < 0.5 < 0.4 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Molecular Weight-B -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 HeatingTemp.-C Fitted Surface: % of Heel-H > 8 < 8 < 7 < 6 < 5 < 4 < 3 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Molecular Weight-B -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 HeatingTemp.-C Pore Volume ≥ 0.8 cm3/g Heel < 5%
  20. 20. Central Composite Design: Optimum Results 20 Favorable Regions MATLAB optimum results (coded values): Kinetic Diameter = -0.44 Heating Temperature= -0.07 Heel = 4.07%, Pore Volume = 0.82 cm3/g Fitted Surface: % of Heel-H > 8 < 8 < 7 < 6 < 5 < 4 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Kinetic Diameter-A -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 HeatingTemp.-C Fitted Surface: Pore Volume-V > 1.1 < 1.1 < 1 < 0.9 < 0.8 < 0.7 < 0.6 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Kinetic Diameter-A -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 HeatingTemp.-C s Heel < 5% Pore Volume ≥ 0.8 cm3/g
  21. 21. Discussions • VOCs properties (molecular weight & kinetic diameter) more significant than process parameters (heating duration etc.) • Obtained results in well agreement with literature • Models were verified (normal, residual, half normal plots checked) • Effects of nuisance factors were checked & found negligible • Limited time & resources: physical experiments not done in 2nd stage • Anticipated results comply best with real results • Future Works : perform real experiments & verify the results 21
  22. 22. Conclusions • Heel minimized & Pores maximized for moderately high regeneration temperature, lower molecular weight & smaller kinetic diameter VOCs • Optimum results (heel = 4.1%, pore volume = 0.82 cm3/g) identified for: • VOCs molecular weight : 79.2 g/mol , kinetic diameter: 0.28 nm • Heating temperature: 259°C • Recommendation • To reduce no. of runs: Fractional factorial in 1st stage • Taguchi method : better results in least no. of runs 22
  23. 23. 23 • Professor Kajsa Duke • Professor Zaher Hashisho & all my colleagues from Air Quality Control group • Ford Motor Company for financial support Acknowledgement
  24. 24. 24 1. Kim, B. R., 2011, “VOC emissions from automotive painting and their control: A review”, Environ. Eng. Res., 16 (1), pp.1 – 9). 2. D.C. Montgomery, Design and analysis of experiments. 8th edition, John Wiley & Sons, New York, 2014. 3. Hou, P., Byrne, T., Cannon, F. S., Chaplin, B. P., Hong, S., and Nieto- Delgado, C., 2014, “Electrochemical regeneration of polypyrrole-tailored activatedcarbons that have removed sulfate”, Carbon 7 9, pp 4 6 –5 7 4. Dong, L., Liu, W., Jiang, R., Wanga, Z., 2014, “Physicochemical and porosity characteristics of thermally regenerated activated carbon polluted with biological activated carbon process”, Bioresource Technol, 171, pp. 260 - 264 References
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