Transcript ME414 Spring 2006 Design Project 2

ME414
Spring 2006
Design Project 2
Heat Exchanger
Ugo Anyoarah
Osinanna Okonkwo
Vinay Prisad
Daniel Reed
Introduction
• Introduction
• Project Definition
– Design Optimization Goals
• First Design Pass
• Second Design Pass
• Other Factors
• Design Results
Project Definition
• During the make of a liquid chemical product, its
temperature needs to be reduced by 10 degrees Celsius.
– Mass flow rate is 80,000 kg/hr
– Fluid enters the heat exchanger at 35 C and should leave at 25 C
– Material properties of this chemical product can be approximated as
water
• Cooling of the chemical product will be achieved by using
treated city water
– City water is available at 20 C
– Mass flow rate is adjustable and one of the design parameters to be
selected
– Exit temperature of city water from the heat exchanger is a function
of the selected mass flow rate
Design Optimization Goals
• Must cool the chemical from 35 C to 25 C
• Heat exchanger length can not exceed 7 m
• Heat exchanger shell diameter can not
exceed 2 m
• Minimize heat exchanger shell and tube
weight hence the cost
• Minimize heat exchanger pressure drop
First Design Pass
• Matlab Variables
– 4 variables
• Tube_OD (6.350 – 25.4)e-3 meters
• Shell_ID (.8 – 2) meters
• Tube_Len (4 – 7) meters
• N_tube
(40 – 100)
– 7 levels
• Gives 7^4 = 2401 runs
First Design Pass
• Matlab Variables
– Tube and Shell Material set to Aluminum
• Consistent expansion between shell & tubes.
• Maximum heat transfer
• Corrosion Resistance (chemical similar to H20)
– Tube pass set to two (2)
• Most space efficient
– Baffle Space set to 0.1048 m
– Baffle Cut set to 0.3750 m
– City water flow rate set to 38.8889 Kg/Sec
First Design Pass
• Matlab Results
– Weight: 2069.17 – 22415.9
– DP Shell: 335149 – 6364756
– DP Tube: 17701.66 – 4.26e11
– Q Calc: 107043.7 – 919867.5
• 2401 runs = AAARRRGGGHHH!!!!!
First Design Pass - MiniTab Results
Main Effects Plot (data means) for DP_Tube
Tube_OD
1.6000E+11
Main Effects Plot (data means) for Weight_HE
Tube_OD
Shell_ID
15000
1.2000E+11
8.0000E+10
10000
4.0000E+10
0
0
35
6.
5
00
75
50
50
00
53
.7
.8
.0
.2
.4
9.
12
15
19
22
25
8
0.
0
1.
2
1.
Tube_Len
1.6000E+11
4
1.
1.
6
8
1.
0
2.
N_tube
1.2000E+11
Mean of Weight_HE
Mean of DP_Tube
Shell_ID
8.0000E+10
5000
0
35
6.
5
00
75
50
50
00
53
.7
.8
.0
.2
.4
9.
12
15
19
22
25
8
0.
0
1.
2
1.
Tube_Len
4
1.
6
1.
1.
8
0
2.
80
90
0
10
6
1.
8
1.
0
2.
80
90
0
10
N_tube
15000
10000
4.0000E+10
5000
0
0
4.
4.
5
0
5.
5
5.
0
6.
5
6.
0
7.
40
50
60
70
80
90
0
10
4.
0
5
4.
Main Effects Plot (data means) for q_Calc
Tube_OD
600000
0
5.
5
5.
0
6.
5
6.
0
7.
40
50
60
70
Main Effects Plot (data means) for DP_Shell
Tube_OD
Shell_ID
Shell_ID
3000000
500000
2000000
300000
0
35
6.
9.
5
53
00
75
50
50
00
.7
.8
.0
.2
.4
12
15
19
22
25
8
0.
1.
0
2
1.
Tube_Len
600000
4
1.
6
1.
8
1.
0
2.
N_tube
Mean of DP_Shell
Mean of q_Calc
400000
1000000
3
6.
50
5
00
75
50
50
00
53
.7
.8
.0
.2
.4
9.
12
15
19
22
25
Tube_Len
8
0.
0
1.
2
1.
4
1.
N_tube
3000000
500000
2000000
400000
1000000
300000
0
4.
5
4.
0
5.
5
5.
0
6.
5
6.
0
7.
40
50
60
70
80
90
0
10
0
4.
5
4.
0
5.
5
5.
0
6.
5
6.
0
7.
40
50
60
70
First Design Pass
• Findings
– MiniTab will not do Pareto charts for systems
with more than 2 levels.
– Higher levels ( >4) are beneficial for
identifying linear regions and critical areas.
Second Design Pass
• Used Excel to find variable combinations
with Qcalc/Qdes = 1 +/-10%
• 12 combinations met criteria
• Used the max and min in 2nd iteration of
Matlab (2 level)
Second Design Pass
• Matlab Variables
– 4 variables
• Tube_OD (9.535 – 25.4)e-3 meters
• Shell_ID (.8 – 1) meters
• Tube_Len (6.5 – 7) meters
• N_tube
(90 – 100)
– 2 levels
• Gives 2^4 = 16 runs
Second Design Pass
• Matlab Results
– Weight: 3444 – 5773
– DP Shell: 122279 – 3933472
– DP Tube: 24799 – 41293392
– Q Calc: 844667 – 919867
• 16 runs = MMM! (Much more manageable)
Second Design Pass - MiniTab Results
Pareto Chart of the Standardized Effects
Pareto Chart of the Standardized Effects
(response is DP_Shell, Alpha = .05)
(response is Weight_HE, Alpha = .05)
2
2.2
F actor
A
B
C
A
N ame
TU BE _O D
S H E LL_ID
TU BE _LE N
B
C
F actor
A
B
C
D
N ame
TU BE _O D
S H E LL_ID
TU BE _LE N
N _TU BE
A
BC
AC
D
BC
0
200
400
600
800
Standardized Effect
1000
1200
0
100
Pareto Chart of the Standardized Effects
200
300
400
500
Standardized Effect
600
700
Pareto Chart of the Standardized Effects
(response is DP_Tube, Alpha = .05)
(response is q_Calc, Alpha = .05)
2.2
2.45
F actor
A
C
D
A
N ame
TU BE _O D
TU BE _LE N
N _TU BE
D
C
B
D
Term
A
Term
N ame
TU BE _O D
S H E LL_ID
TU BE _LE N
N _TU BE
C
AB
Term
Term
B
F actor
A
B
C
D
AD
AB
AD
C
CD
BC
AC
BD
0
100
200
300
400
500
Standardized Effect
600
700
800
0
10
20
30
40
50
60
Standardized Effect
70
80
90
Second Design Pass - Optimizer
Second Design Pass - Optimizer
Second Design Pass
• Check W/ Matlab
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–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
Number of Tubes N = 100.00
Number of Passes
=
2.00
Tubes OD
OD = 0.0191 m
Tubes ID
ID = 0.0135 m
Tube Length
L = 6.7500 m
Tube Pitch
PT = 0.0238 m
Shell ID
= 0.9000 m
Baffle Space
= 0.1048 m
Number of Baffles = 63.0000 m
Desired Heat Transfer Rate = 928501.84 W
Calculated Heat Transfer Rate = 843364.57 W
Difference = 85137.28 W
Desired-to-Calculated Ratio =
1.10
Shell Side Delta-P = 1517783.93 Pa
Tube Side Delta-P = 138509.45 Pa
Total HE Weight = 4550.87 kg
Second Design Pass
• Fouling Factor
– Increased tube number to account for fouling
– 116 tubes required for Q/q=1
– 135 tubes for Q/q=0.91
• DP Shell: Unchanged
• DP Tube: 79943.83 Pa
• Weight: 4607.82 Kg
Other Factors
• Full Factorial desirable
–
–
–
–
–
City Water Flow Rate
Baffle Spacing
Baffle Cut Height
Tube Pitch
Tube Layout Angle
– Yields 12 factors
• Even 2 levels is long: 4096 data points
Design Results
• Length: 6.5m
• Shell ID: 1m
• Tube OD: 19.1mm
• Tube Length: 6.75m
• Number of Tubes: 135