monisha alam_1412059
TRANSCRIPT
MEC E 668: Design of ExperimentInstructor: Professor Kajsa Duke
Final Projectby
Monisha AlamSupervisor: Dr. Zaher Hashisho
Design of Experiments to Optimize the Regeneration Process of Spent Activated Carbon Cloth by Resistive
Heating Method
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 pores2
http://northharfordcollision.net/wp-content/uploads/2013/06/car-painting.jpg
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
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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)
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• 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
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Regeneration CartridgeSpent ACC
Experimental Setup
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Thermocouple
Quartz Reactor
3 Layered ACC
Electrode Tube
Application of Heat
Flow of N2
Measurement of Heel & Pore Volume
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Measuring Heel
Measuring Pore Volume
% of Heel = Mreg = Mass of regenerated ACCMV = Mass of virgin ACC
(MReg – MV ) / MV x 100%
Stage 1: Full Factorial DesignScreening Test with experimental & made-up data
• Responding Variables1. Amount of heel: < 5%2. Pore volume: ≥ 0.8 cm3/g
• Controlled Variables1. Heating rate: 10 °C/min2. Electrode Tubes: 1.65 cm dia
• Nuisance Factors1. Batch of ACC2. Voltage generator
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0 1 2 3 4 5 66.78
6.82
6.86
6.9
Percentage of Heel vs. batches
Batch of ACC
Perc
enta
ge o
f Hee
l0 1 2 3 4 5 6
0.720.7220.7240.7260.728
0.73
Pore Volume vs. batches
Batch of ACC
Pore
Vol
ume
Effects of Nuisance Variables
Stage 1: Full Factorial Design
Low (-) High (+)1. Kinetic diameter (nm) 0.3 0.82. Molecular weight (g/mole) 80 1403. Heating temperature (°C) 60 2604. Heating duration (h) 1 35. Nitrogen flow rate (L/min) 1 3
No. of runs = 25 = 329
Manipulated Variables
Stage 1: Full Factorial Design-Results
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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
Stage 1: Full Factorial Design-Results
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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
Stage 2: Central Composite Design
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Responding Variables Objective Acceptable Rangei Percentage of Heel (%) To minimize < 5ii Pore Volume Recovered (cm3/g) To maximize > 0.8
Manipulated Variables -1.682 -1 0 +1 +1.682A Adsorbates Kinetic Diameter (nm) 0.22 0.25 0.30 0.35 0.38B Adsorbates Molecular Weight
(g/mole) 46.4 60 80 100 113.6C Heating Temperature (°C) 226.4 240 260 280 293.6
Controlled Variables Set Conditions1 Heating Duration (h) 12 Nitrogen Flow Rate (L/min) 13 Heating Rate (C/min) 104 Electrode Tube 1.65 cm dia
Curvature effects, surface response, 5 levels, No. of runs: 16
Central Composite Design: Results
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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)
Central Composite Design: Results
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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)
Central Composite Design: Surface Plots – % of Heel
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Central Composite Design: Surface Plots–Pore Volume
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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
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• Pore Volume, V = – 4.3724 – 44.7958 Ae + 92.9736 Ae2 + 0.0311 Be –
0.0009 Be2 + 0.0818 Ce – 0.000155 Ce
2 – 0.020039 Ae Be – 0.0241919 Ae Ce
17A = 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
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
Mol
ecul
ar W
eigh
t-B
Central Composite Design: Optimum Results
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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
Mol
ecul
ar W
eigh
t-B
Heel < 5%
Favorable Regions
MATLAB optimum results (coded values):Kinetic Diameter = -0.44Molecular Weight = -0.03Heel = 4.07%, Pore Volume = 0.82 cm3/g
Pore Volume ≥ 0.8 cm3/g
Central Composite Design: Optimum Results
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Favorable Regions
MATLAB optimum results (coded values):Molecular Weight = -0.03,Heating Temperature= -0.07Heel = 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
Heati
ng Te
mp.
-CFitted 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
Heati
ng Te
mp.
-C
Pore Volume ≥ 0.8 cm3/g
Heel < 5%
Central Composite Design: Optimum Results
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Favorable Regions
MATLAB optimum results (coded values):Kinetic Diameter = -0.44Heating Temperature= -0.07Heel = 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
Heati
ng Te
mp.
-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
Heati
ng Te
mp.
-C
s
Heel < 5%Pore Volume ≥ 0.8 cm3/g
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
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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
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• Professor Kajsa Duke
• Professor Zaher Hashisho & all my colleagues from Air Quality Control group
• Ford Motor Company for financial support
Acknowledgement
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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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