Simple polynomial fit to data for the specific heat capacity of monoethanolamine
as a function of temperature, CO2 loading, and concentration.
Where:
Cp = heat capacity (kJ/kg-K)
T = temperature (°C)
,x = mass fraction of MEA, or, weight percent MEA
,α = CO2 loading (mol CO2/mol MEA)
Just a poly fit to data from:
“Heat Capacity of Aqueous Monoethanolamine, Diethanolamine, N-Methyldiethanolamine,
and N-Methyldiethanolamine-Based Blends with Carbon Dioxide”
For effect of loading on Cp
“Heat Capacity of Alkanolamine Aqueous Solutions (Li-Feng Chiu and Meng-Hui Li)”
For effect of high MEA concentration on Cp
For pure water data.
Data:
|
|
|
data
|
vs. fit
|
|
T (degC)
|
wt%
|
load alpha
|
CP (kJ/kg-K)
|
CP (kJ/kg-K)
|
out by:
|
25
|
10%
|
0
|
4.061
|
4.04
|
0.5%
|
25
|
10%
|
0.05
|
4.015
|
3.99
|
0.5%
|
25
|
10%
|
0.1
|
3.823
|
3.95
|
3.4%
|
25
|
10%
|
0.2
|
3.917
|
3.89
|
0.6%
|
25
|
10%
|
0.3
|
3.915
|
3.86
|
1.4%
|
25
|
10%
|
0.4
|
3.891
|
3.86
|
0.8%
|
25
|
10%
|
0.5
|
3.857
|
3.88
|
0.7%
|
25
|
20%
|
0
|
3.911
|
3.91
|
0.0%
|
25
|
20%
|
0.1
|
3.656
|
3.80
|
3.9%
|
25
|
20%
|
0.2
|
3.766
|
3.71
|
1.4%
|
25
|
20%
|
0.3
|
3.670
|
3.66
|
0.3%
|
25
|
20%
|
0.4
|
3.648
|
3.63
|
0.5%
|
25
|
20%
|
0.5
|
3.597
|
3.63
|
1.0%
|
25
|
30%
|
0
|
3.734
|
3.77
|
1.0%
|
25
|
30%
|
0.1
|
3.508
|
3.63
|
3.6%
|
25
|
30%
|
0.2
|
3.570
|
3.53
|
1.2%
|
25
|
30%
|
0.3
|
3.457
|
3.45
|
0.3%
|
25
|
30%
|
0.4
|
3.418
|
3.40
|
0.6%
|
25
|
30%
|
0.5
|
3.359
|
3.37
|
0.5%
|
25
|
40%
|
0
|
3.634
|
3.63
|
0.2%
|
25
|
40%
|
0.2
|
3.343
|
3.34
|
0.2%
|
25
|
40%
|
0.3
|
3.238
|
3.23
|
0.2%
|
25
|
40%
|
0.4
|
3.163
|
3.16
|
0.2%
|
25
|
40%
|
0.5
|
3.109
|
3.11
|
0.1%
|
30
|
46%
|
0
|
3.523
|
3.56
|
1.1%
|
35
|
46%
|
0
|
3.549
|
3.58
|
0.9%
|
40
|
46%
|
0
|
3.575
|
3.60
|
0.7%
|
45
|
46%
|
0
|
3.601
|
3.62
|
0.5%
|
50
|
46%
|
0
|
3.628
|
3.64
|
0.4%
|
55
|
46%
|
0
|
3.658
|
3.66
|
0.1%
|
60
|
46%
|
0
|
3.684
|
3.68
|
0.1%
|
65
|
46%
|
0
|
3.710
|
3.70
|
0.2%
|
70
|
46%
|
0
|
3.737
|
3.72
|
0.4%
|
75
|
46%
|
0
|
3.755
|
3.74
|
0.3%
|
80
|
46%
|
0
|
3.793
|
3.76
|
0.8%
|
30
|
69%
|
0
|
3.178
|
3.20
|
0.7%
|
35
|
69%
|
0
|
3.235
|
3.23
|
0.1%
|
40
|
69%
|
0
|
3.263
|
3.26
|
0.1%
|
45
|
69%
|
0
|
3.292
|
3.29
|
0.1%
|
50
|
69%
|
0
|
3.320
|
3.32
|
0.1%
|
55
|
69%
|
0
|
3.377
|
3.35
|
0.9%
|
60
|
69%
|
0
|
3.405
|
3.37
|
0.9%
|
65
|
69%
|
0
|
3.433
|
3.40
|
0.9%
|
70
|
69%
|
0
|
3.462
|
3.43
|
0.8%
|
75
|
69%
|
0
|
3.519
|
3.46
|
1.6%
|
80
|
69%
|
0
|
3.547
|
3.49
|
1.6%
|
30
|
84%
|
0
|
2.987
|
2.97
|
0.6%
|
35
|
84%
|
0
|
3.010
|
3.00
|
0.3%
|
40
|
84%
|
0
|
3.056
|
3.04
|
0.6%
|
45
|
84%
|
0
|
3.078
|
3.07
|
0.3%
|
50
|
84%
|
0
|
3.124
|
3.10
|
0.6%
|
55
|
84%
|
0
|
3.147
|
3.14
|
0.2%
|
60
|
84%
|
0
|
3.170
|
3.17
|
0.1%
|
65
|
84%
|
0
|
3.215
|
3.21
|
0.2%
|
70
|
84%
|
0
|
3.238
|
3.24
|
0.1%
|
75
|
84%
|
0
|
3.284
|
3.28
|
0.2%
|
80
|
84%
|
0
|
3.306
|
3.31
|
0.1%
|
30
|
93%
|
0
|
2.840
|
2.80
|
1.2%
|
35
|
93%
|
0
|
2.859
|
2.84
|
0.6%
|
40
|
93%
|
0
|
2.897
|
2.88
|
0.6%
|
45
|
93%
|
0
|
2.916
|
2.92
|
0.1%
|
50
|
93%
|
0
|
2.954
|
2.96
|
0.1%
|
55
|
93%
|
0
|
2.973
|
2.99
|
0.7%
|
60
|
93%
|
0
|
3.011
|
3.03
|
0.7%
|
65
|
93%
|
0
|
3.030
|
3.07
|
1.3%
|
70
|
93%
|
0
|
3.069
|
3.11
|
1.2%
|
75
|
93%
|
0
|
3.088
|
3.14
|
1.8%
|
80
|
93%
|
0
|
3.126
|
3.18
|
1.8%
|
0.01
|
0
|
0
|
4.220
|
4.15
|
1.6%
|
10
|
0
|
0
|
4.196
|
4.16
|
0.8%
|
20
|
0
|
0
|
4.184
|
4.17
|
0.4%
|
25
|
0
|
0
|
4.182
|
4.17
|
0.3%
|
30
|
0
|
0
|
4.180
|
4.17
|
0.2%
|
40
|
0
|
0
|
4.180
|
4.18
|
0.0%
|
50
|
0
|
0
|
4.182
|
4.19
|
0.1%
|
60
|
0
|
0
|
4.185
|
4.19
|
0.2%
|
70
|
0
|
0
|
4.190
|
4.20
|
0.2%
|
80
|
0
|
0
|
4.197
|
4.20
|
0.2%
|
90
|
0
|
0
|
4.205
|
4.21
|
0.1%
|
100
|
0
|
0
|
4.216
|
4.22
|
0.0%
|
Hi, could you explain how you have done it?
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