1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
|
{
"metadata": {
"name": "ch5",
"signature": "sha256:2ee4e5f8137c7268975819ca4a31ef66c4a59076a802f56667cecd1c3f67b2a9"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Chapter 5 : Humidification"
]
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.1 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"\n",
"# Variable Declaration \n",
"#dry bulb temperature=50 and wet bulb temperature=35 \n",
"Tg=50.; #dry bulb temperature=50\n",
"To=0; #refrence temperature in degree celcius \n",
"Mb=28.84; #average molecular weight of air\n",
"Ma=18.; #average molecular weight of water\n",
"\n",
"#part(i)\n",
"ybar=.0483 #0.003 kg of water vapour/kg of dry air\n",
"print \"\\n the humidity(from chart) is \\t\\t:%f percent\"%ybar\n",
"\n",
"#part(ii)\n",
"humper=35.; #humidity percentage\n",
"print \"\\n the percentage humidity is(from chart) :%f percent\"%humper\n",
"\n",
"# Calculation and Result\n",
"#part(iii)\n",
"pt=1.013*10**5; #total pressure in pascal\n",
"molhum=0.0483; #molal humidity =pa/(pt-pa)\n",
"pa=molhum*pt/(1+molhum);\n",
"#the vopour pressure of water(steam tables)at 50degree = .1234*10**5 N/m**2\n",
"relhum=(pa/(.1234*10**5))*100; #percentage relative humidity =partial pressure/vapour pressure\n",
"print \"\\n the percentage relative humidity is \\t percent:%f \"%relhum\n",
"\n",
"#part(iv)\n",
"dewpoint=31.5; #dew point temperature in degree celcius\n",
"print \"\\n the dew point temperature \\t\\t :%f degree celcius\"%dewpoint\n",
"\n",
"#part(v)\n",
"Ca=1.005;\n",
"Cb=1.884;\n",
"ybar=.03; #saturation temperature inkg water vapour/kg dry air\n",
"Cs=Ca+Cb*ybar; #humid heat in kj/kg dry air degree celcius\n",
"print \"\\n we get humid heat as \\t\\t\\t :%f kj/kg dry air degree celcius \"%Cs\n",
"\n",
"#part(vi)\n",
"d=2502; #latent heat in kj/kg\n",
"H=Cs*(Tg-0)+ybar*d; #enthalpy for refrence temperature of 0 degree\n",
"print \"\\n we get H as \\t\\t\\t\\t :%f kj/kg\"%H\n",
"Hsat=274.; #enthalpy of sturated air\n",
"Hdry=50.; #enthalpy of dry air in kj/kg\n",
"Hwet=Hdry+(Hsat-Hdry)*0.35; #enthalpy of wet air in kj/kg\n",
"print \"\\n we get enthalpy of wet air as \\t:%f kj/kg\"%Hwet\n",
"\n",
"#part(vii)\n",
"VH=8315*((1./Mb)+(ybar/Ma))*((Tg+273.)/pt); #humid volume in m**3mixture/kg of dry air\n",
"print \"\\n we get VH as (a)\\t\\t\\t :%f m**3/kg of dry air\"%VH\n",
"spvol=1.055; #specific volume of saturated air in m**3*kg\n",
"vdry=0.91; #specific volume of dry air in m**3/kg\n",
"Vh=vdry+(spvol-vdry)*.35 #by interpolation we get Vh in m**3/kg of dry air \n",
"print \"\\n by interpolation we get specific volume Vh as(b) :%f m**3/kg of dry air\"%Vh\n",
"\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the humidity(from chart) is \t\t:0.048300 percent\n",
"\n",
" the percentage humidity is(from chart) :35.000000 percent\n",
"\n",
" the percentage relative humidity is \t percent:37.822988 \n",
"\n",
" the dew point temperature \t\t :31.500000 degree celcius\n",
"\n",
" we get humid heat as \t\t\t :1.061520 kj/kg dry air degree celcius \n",
"\n",
" we get H as \t\t\t\t :128.136000 kj/kg\n",
"\n",
" we get enthalpy of wet air as \t:128.400000 kj/kg\n",
"\n",
" we get VH as (a)\t\t\t :0.963494 m**3/kg of dry air\n",
"\n",
" by interpolation we get specific volume Vh as(b) :0.960750 m**3/kg of dry air\n"
]
}
],
"prompt_number": 13
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.2 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"# Variable Declaration \n",
"\n",
"#dry bulb temperature=25 and wet bulb temperature=22\n",
"Tg=25.; #dry bulb temperature=50\n",
"To=0; #refrence temperature in degree celcius \n",
"Mb=28.84; #average molecular weight of air\n",
"Ma=18.; #average molecular weight of water\n",
"\n",
"\n",
"# Calculation and Result\n",
"#part(i)\n",
"hum=.0145 #0.0145 kg of water/kg of dry air\n",
"print \"\\n the saturation humidity(from chart) is :%f percent\"%hum\n",
"\n",
"#part(ii)\n",
"humper=57.; #humidity percentage\n",
"print \"\\n the percentage humidity is \\t\\t:%f percent\"%humper\n",
"\n",
"#part(iii)\n",
"pt=1.; #total pressure in atm\n",
"sathum=0.0255; #molal humidity =pa/(pt-pa)\n",
"pa1=sathum*pt*(28.84/18)/(1+(sathum*(28.84/18)));\n",
"#the vopour pressure of water(steam tables)at 25 = .0393*10**5 N/m**2\n",
"pt=1; #total pressure in atm\n",
"molhum=0.0145; #molal humidity =pa/(pt-pa)\n",
"pa2=molhum*pt*(28.84/18)/(1+(molhum*pt*(28.84/18)));\n",
"#the vopour pressure of water(steam tables)at 25 = .0393*10**5 N/m**2\n",
"relhum=(pa2/pa1)*100; #percentage relative humidity =partial pressure/vapour pressure\n",
"print \"\\n the percentage relative humidity is \\t :%f \"%relhum\n",
"\n",
"#part(iv)\n",
"dewpoint=19.5; #dew point temperature in degree celcius\n",
"print \"\\n the dew point temperature \\t :%f degree celcius\"%dewpoint\n",
"\n",
"#part(v)\n",
"Ca=1005.;\n",
"Cb=1884.;\n",
"ybar=.0145; # humidity inkg water /kg dry air\n",
"Cs=Ca+Cb*ybar; #humid heat in j/kg dry air degree celcius\n",
"d=2502300.; #latent heat in j/kg\n",
"H=Cs*(Tg-0)+ybar*d; #enthalpy for refrence temperature of 0 degree\n",
"print \"\\n we get Humid heat H as \\t :%f j/kg\"%H\n",
"#the actual answer is 62091.3 bt in book it is given 65188.25(calculation mistake in book)\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the saturation humidity(from chart) is :0.014500 percent\n",
"\n",
" the percentage humidity is \t\t:57.000000 percent\n",
"\n",
" the percentage relative humidity is \t :57.842165 \n",
"\n",
" the dew point temperature \t :19.500000 degree celcius\n",
"\n",
" we get Humid heat H as \t :62091.300000 j/kg\n"
]
}
],
"prompt_number": 14
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.3"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"# Variable Declaration \n",
"\n",
"#part(i)\n",
"pt=800.; #total pressure in mmHg\n",
"pa=190.; #vapour pressure of acetone at 25 degree \n",
"ys_bar=pa*(58./28)/(pt-pa) #\n",
"#percentage saturation = y_bar/ys_bar *100\n",
"s=80; #percent saturation\n",
"\n",
"# Calculation and Result\n",
"y_bar=ys_bar*s/100.; #absolute humidity\n",
"print \"\\n the absolute humidity is \\t :%f kg acetone/kmol N2 \"%y_bar\n",
"\n",
"#part(ii)\n",
"#y_bar=pa*(58/28)/(pt-pa) \n",
"pa1=pt*y_bar*(28./58)/(1+(y_bar*(28./58)));\n",
"print \"\\n the partial pressure of acetone is:%f mmHg\"%pa1\n",
"\n",
"#part(iii)\n",
"y=pa1/(pt-pa1); #absolute molal humidity\n",
"print \"\\n absolute molal humidity \\t:%f kmol acetone/kmol N2\"%y\n",
"\n",
"#part(iv)\n",
"#volume of .249kmol acetone vapour at NTP =.249*22.14\n",
"#p1v1/T1 =p2v2/T2\n",
"p2=800.; #final pressure of acetone and nitrogen at 25 degree\n",
"p1=760.; #initial pressure of acetone and nitrogen at 25 degree\n",
"T2=298.; #final temperature of acetone and nitrogenat 25 degree\n",
"T1=273.; #initial temperature of acetone and nitrogen at 25 degree\n",
"vA1=5.581; #initial volume of acetone at 25 degree\n",
"vN1=22.414; #initial volume of nitrogen at 25 degree \n",
"vA2=T2*vA1*p1/(T1*p2); #final volume of acetone at 25 degree\n",
"vN2=T2*vN1*p1/(T1*p2); #final volume of nitrogen at 25 degree\n",
"vtotal=vA2+vN2; #total volume of the mixture\n",
"vper=vA2*100/vtotal; #percentage volume of acetone\n",
"print \"\\n the percentage volume of acetone is :%f m**3\"%vper\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the absolute humidity is \t :0.516159 kg acetone/kmol N2 \n",
"\n",
" the partial pressure of acetone is:159.580052 mmHg\n",
"\n",
" absolute molal humidity \t:0.249180 kmol acetone/kmol N2\n",
"\n",
" the percentage volume of acetone is :19.935703 m**3\n"
]
}
],
"prompt_number": 15
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.4 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"\n",
"# Variable Declaration \n",
"\n",
"#part(i)\n",
"pa=13.3; #pressure in kpa\n",
"pa2=20.6; #vapour pressure at 60 degree\n",
"pt=106.6 #total pressure in kpa\n",
"y=pa/(pt-pa); #absolute molal humidity\n",
"\n",
"# Calculation and Result\n",
"y_bar=y*(18/28.84); #relative humidity\n",
"print \"\\n absolute humidity of mixture :%f kg water-vapour/kg dry air\"%y_bar\n",
"\n",
"\n",
"#part(ii)\n",
"mf=pa/pt; #mole fraction\n",
"print \"\\n the mole fraction is :%f\"%mf\n",
"\n",
"#part(iii)\n",
"vf=mf; #volume fraction\n",
"print \"\\n the volume fraction is :%f\"%vf\n",
"\n",
"#part(iv)\n",
"Ma=18.; #molecular weight\n",
"Mb=28.84; #molecular weight\n",
"Tg=60.; #temperature of mixture\n",
"rh=(pa/pa2)*100.; #relative humidity in pecentage \n",
"print \"\\n we get relative humidity as as :%f percent\"%rh\n",
"\n",
"#part(v)\n",
"VH=8315.*((1./Mb)+(y_bar/Ma))*((Tg+273)/pt)*10**-3; #humid volume in m**3mixture/kg of dry air\n",
"x=y_bar/VH; #g water/m**3 mixture \n",
"print \"\\n we get x i.e. gwater/m**3 mixture as :%f \"%(x*1000)\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" absolute humidity of mixture :0.088971 kg water-vapour/kg dry air\n",
"\n",
" the mole fraction is :0.124765\n",
"\n",
" the volume fraction is :0.124765\n",
"\n",
" we get relative humidity as as :64.563107 percent\n",
"\n",
" we get x i.e. gwater/m**3 mixture as :86.460483 \n"
]
}
],
"prompt_number": 16
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.5 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"\n",
"# Variable Declaration \n",
"\n",
"#part(i)\n",
"y_bar=.0183; #kg water vapour/kg dry air\n",
"print \"\\n we get humidity as(from chart) :%f kg of water/kg dry air\"%y_bar\n",
"print \"\\n we get saturation humidity as(from chart) :%d percent\"%67\n",
"Ma=18.; #molecular weight\n",
"Mb=28.84; #molecular weight\n",
"Tg=30.; \n",
"pa = 13.3\n",
"pa2 = 20.6 #temperature of mixture\n",
"rh=(pa/pa2)*100; #relative humidity in pecentage \n",
"pt=1.013*10**5; #total pressure in pascal\n",
"\n",
"# Calculation and Result\n",
"VH=8315*((1./Mb)+(y_bar/Ma))*((Tg+273)/pt); #humid volume in m**3mixture/kg of dry air\n",
"print \"\\n we get humid volume as \\t:%f m**3/kg dry air\"%VH\n",
"\n",
"#part(ii)\n",
"Ca=1005.;\n",
"Cb=1884.;\n",
"Cs=Ca+Cb*y_bar; #humid heat in j/kg dry air degree celcius\n",
"print \"\\n we get humid heat as \\t\\t :%f j/kg dry air degree celcius \"%Cs\n",
"\n",
"#part(iii)\n",
"d=2502300.; #latent heat in j/kg\n",
"H=Cs*(Tg-0)+y_bar*d; #enthalpy for refrence temperature of 0 degree\n",
"print \"\\n we get Enthalpy H as \\t\\t:%f j/kg dry air\"%H\n",
"\n",
"#part(iv)\n",
"dewpoint=23.5; #dew point temperature in degree celcius\n",
"print \"\\n the dew point temperature \\t :%f degree celcius\"%dewpoint\n",
"\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" we get humidity as(from chart) :0.018300 kg of water/kg dry air\n",
"\n",
" we get saturation humidity as(from chart) :67 percent\n",
"\n",
" we get humid volume as \t:0.887669 m**3/kg dry air\n",
"\n",
" we get humid heat as \t\t :1039.477200 j/kg dry air degree celcius \n",
"\n",
" we get Enthalpy H as \t\t:76976.406000 j/kg dry air\n",
"\n",
" the dew point temperature \t :23.500000 degree celcius\n"
]
}
],
"prompt_number": 17
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.6 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"# Variable Declaration \n",
"\n",
"#part(i)\n",
"y=.048; #humidity kmol water vapour/kmol dry air\n",
"y_bar=y*(18/28.84); #(from chart) absolute humidity\n",
"print \"we get absolute humidity as :%f kg of water/kg dry air\"%(y_bar)\n",
"print \"we get percentage humidity as(from chart) :%f percent\"%(25.5);\n",
"\n",
"# Calculation and Result\n",
"y_bar=y*(18/28.84); #relative humidity\n",
"Ma=18.; #molecular weight\n",
"Mb=28.84; #molecular weight\n",
"Tg=55.; #temperature of mixture\n",
"pt=1.013*10**5; #total pressure in pascal\n",
"VH=8315*((1./Mb)+(y_bar/Ma))*((Tg+273)/pt); #humid volume in m**3mixture/kg of dry air\n",
"print \"\\n we get VH as \\t :%f m**3/kg dry air\"%VH\n",
"\n",
"#part(ii)\n",
"Ca=1005.;\n",
"Cb=1884.;\n",
"Cs=Ca+Cb*y_bar; #humid heat in j/kg dry air degree celcius\n",
"print \"\\n we get humid heat as \\t :%f j/kg dry air degree celcius \"%Cs\n",
"\n",
"#part(iii)\n",
"d=2502300.; #latent heat in j/kg\n",
"H=Cs*(Tg-0)+y_bar*d; #enthalpy for refrence temperature of 0 degree\n",
"print \"\\n we get H as \\t :%f j/kg dry air\"%H\n",
"\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"we get absolute humidity as :0.029958 kg of water/kg dry air\n",
"we get percentage humidity as(from chart) :25.500000 percent\n",
"\n",
" we get VH as \t :0.978346 m**3/kg dry air\n",
"\n",
" we get humid heat as \t :1061.441609 j/kg dry air degree celcius \n",
"\n",
" we get H as \t :133344.170596 j/kg dry air\n"
]
}
],
"prompt_number": 18
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.7 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"\n",
"# Variable Declaration \n",
"\n",
" \n",
"ft=46; #final temperature in degree celcius\n",
"# Calculation and Result\n",
"print \"\\n final temperature is (from chart):%f degree celcius\"%ft\n",
"y_bar=.0475; # humidity of air\n",
"print \"\\n the humidity of air(from chart) :%f kg water vapour /kg dry air\"%y_bar\n",
"\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" final temperature is (from chart):46.000000 degree celcius\n",
"\n",
" the humidity of air(from chart) :0.047500 kg water vapour /kg dry air\n"
]
}
],
"prompt_number": 19
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.8"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"# Variable Declaration \n",
"\n",
"pa1=4.24 #data:vapour pressure of water at 30degree = 4.24 kpa\n",
"pa2=1.70 #vapour pressure of water at 30degree = 1.70 kpa\n",
"\n",
"#part(i)\n",
"pt=100.; #total pressure\n",
"\n",
"# Calculation \n",
"ys_bar=pa1/(pt-pa1); #kg water vapour/kg dry air\n",
"rh=.8; #relative humidity\n",
"pa3=rh*pa1; #partial pressure\n",
"y_bar=pa3*(18/28.84)/(pt-pa3); #molal humidity\n",
"print \"\\n the molal humidity:%f kg/kg dry air\"%y_bar\n",
"\n",
"#part(ii)\n",
"\n",
"pa=1.7; \n",
"pt=200.;\n",
"ys=pa/(pt-pa);\n",
"ys_bar=ys*(18/28.84);\n",
"\n",
"# Result\n",
"print \"\\n the molal humidity if pressure doubled and temp. is 15 :%f kg/kg dry air\"%ys_bar\n",
"\n",
"#part(iii) \n",
"Ma=18.; #molecular weight\n",
"Mb=28.84; #molecular weight\n",
"Tg=30.; #temperature of mixture\n",
"rh=(pa/pa2)*100; #relative humidity in pecentage \n",
"pt=10**5; #total pressure in pascal\n",
"VH=8315*((1./Mb)+(y_bar/Ma))*((Tg+273)/pt); #humid volume in m**3mixture/kg of dry air\n",
"print \"\\n we get humid volume VH as \\t :%f m**3/kg of dry air\"%VH\n",
"w=100/VH; #100 m**3 of original air \n",
"wo= w*y_bar; #water present in original air\n",
"wf= w*ys_bar; #water present finally\n",
"wc=wo-wf; #water condensed from 100m**3 of original sample\n",
"print \"\\n the weight water condensed from 100m**3 of original sample:%f kg\"%wc\n",
"\n",
"#part(iv)\n",
"Tg=15.; #temperature of mixture \n",
"pt=2*10**5; #total pressure in pascal\n",
"VH=8315*((1./Mb)+(ys_bar/Ma))*((Tg+273)/pt); #humid volume in m**3mixture/kg of dry air\n",
"vf=VH*110.6; #final volume of mixture\n",
"print \"\\n we get VH final volume of mixture as \\t :%f m**3\"%vf\n",
"\n",
"#end\n"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the molal humidity:0.021914 kg/kg dry air\n",
"\n",
" the molal humidity if pressure doubled and temp. is 15 :0.005351 kg/kg dry air\n",
"\n",
" we get humid volume VH as \t :0.904267 m**3/kg of dry air\n",
"\n",
" the weight water condensed from 100m**3 of original sample:1.831684 kg\n",
"\n",
" we get VH final volume of mixture as \t :46.311825 m**3\n"
]
}
],
"prompt_number": 20
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.9"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"# Variable Declaration \n",
"\n",
"#part(i)\n",
"y_bar=.03; # humidity inkg water /kg dry air\n",
"pt=760.; #total pressure in pascal\n",
"pa2=118.; #final pressure\n",
"\n",
"# Calculation and Result\n",
"y=y_bar/(18/28.84); #humidity kmol water vapour/kmol dry air\n",
"pa=(y*pt)/(y+1); #partial pressure\n",
"rh=pa/pa2; #relative humidity\n",
"sh=pa2/(pt-pa2); #saturated humidity\n",
"ph=(y/sh)*100; #percentage humidity\n",
"print \"\\n percentage humidity is :%f\"%ph\n",
"\n",
"#/part(ii)\n",
"Ma=18.; #molecular weight\n",
"Mb=28.84; #molecular weight\n",
"Tg=55.; #temperature of mixture\n",
"pt=1.013*10**5; #total pressure in pascal\n",
"VH=8315*((1./Mb)+(y_bar/Ma))*((Tg+273)/pt); #humid volume in m**3mixture/kg of dry air\n",
"print \"\\n we get VH humid volume as :%f m**3/kg dry air\"%VH\n",
"\n",
"\n",
"#part(iii)\n",
"Ca=1005.;\n",
"Cb=1884.;\n",
"Cs=Ca+Cb*y_bar; #humid heat in j/kg dry air degree celcius\n",
"print \"\\n we get humid heat as \\t :%f j/kg dry air degree celcius \"%Cs\n",
"d=2502300; #latent heat in j/kg\n",
"H=Cs*(Tg-0)+y_bar*d; #enthalpy for refrence temperature of 0 degree\n",
"print \"\\n we get H enthalpy as \\t :%f j/kg\"%H\n",
"\n",
"#part(iv)\n",
"v=100.; #volume of air\n",
"mass=v/VH; #mass of dry air\n",
"Tg=110.; #temperature of mixture\n",
"d=2502300.; #latent heat in j\n",
"H_final=Cs*(Tg-0)+y_bar*d; #enthalpy for refrence temperature of 0 degree\n",
"H_added=(H_final-H)*102.25; #HEAT added in kj \n",
"print \"\\n we get heat added as \\t :%f kj\"%(H_added/1000)\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" percentage humidity is :26.151525\n",
"\n",
" we get VH humid volume as :0.978409 m**3/kg dry air\n",
"\n",
" we get humid heat as \t :1061.520000 j/kg dry air degree celcius \n",
"\n",
" we get H enthalpy as \t :133452.600000 j/kg\n",
"\n",
" we get heat added as \t :5969.723100 kj\n"
]
}
],
"prompt_number": 21
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.10"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"# Variable Declaration \n",
"\n",
"%pylab inline\n",
"L=2000.; #flow rate of water to be cooled in kg/min\n",
"T1=50.; #temperature of inlet water\n",
"T2=30.; #temp. of outlet water\n",
"H1=.016; #humidity of incoming air\n",
"cp=4.18; #specific heat of water\n",
"cpair=1.005; #specific heat capcity of air\n",
"cpwater=1.884; #specific heat capcity of water\n",
"tg=20.; #temperature in degree\n",
"to=0;\n",
"ybar=0.016; #saturated humidity at 20 degree\n",
"d=2502.; #latent heat\n",
"Ky_a=2500.; #value of masstransfer coefficient in kg/hr*m**3*dybar\n",
"\n",
"# Calculation \n",
"E=cpair*(tg-to)+(cpwater*(tg-to)+d)*ybar; #enthalpy\n",
"#similarly for other temperatures\n",
"T=[20,30,40,50,55] #differnt temperature for different enthalpy calculation\n",
"i=0;\n",
"E= [0,0,0,0,0]\n",
"while(i<5): #looping for different enthalpy calculation of operating line\n",
" E[i]=cpair*(T[i]-to)+(cpwater*(T[i]-to)+d)*ybar;\n",
" print \"\\n the enhalpy at :%f is :%f\"%(T[i],E[i]);\n",
" i=i+1;\n",
"\n",
"ES=[60.735,101.79,166.49,278.72,354.92] #enthalpy of eqll condition\n",
"from matplotlib.pyplot import *\n",
"\n",
"# Result\n",
"plot(T,E);\n",
"plot(T,ES);\n",
"title(\"Fig.5.10(b),Temperature-Enthalpy plot\");\n",
"xlabel(\"X-- Temperature, degree celcius\");\n",
"ylabel(\"Y-- Enthalpy ,kj/kg\");\n",
"legend(\"operating line\",\"Enthalpy at saturated cond\")\n",
"show()\n",
"\n",
"Hg1=71.09; #point on the oper. line(incoming air)\n",
"Hg2=253.; #point after drawing the tangent\n",
"slope=(Hg2-Hg1)/(T1-T2); #we gt slope of the tangent\n",
" #slope = (L*Cl/G)_min\n",
"Cl=4.18;\n",
"G_min=L*60*Cl/slope; #tangent gives minimum value of the gas flow rate\n",
"G_actual=G_min*1.3; #since actual flow rate is 1.3 times the minimum\n",
"slope2=L*Cl*60/G_actual; #slope of operating line\n",
"Hg2_actual=slope2*(T1-T2)+Hg1; #actual humidityat pt 2\n",
"Ggas=10000.; #minimum gas rate in kg/hr*m**2\n",
"Area1=G_actual/Ggas; #maximum area of the tower(based on gas)\n",
"Gliq=12000.; #minimum liquid rate in kg/hr*m**2\n",
"Area2=60*L/Gliq; #maximum area of the tower(based on liquid)\n",
"print \"\\n \\n the maximum area of the tower(based on gas) is :%f m**2\"%Area1\n",
"print \"\\n the maximum area of the tower(based on liquid) is :%f m**2\"%Area2\n",
"dia=(Area1*4/3.14)**0.5; #diameter of the tower in m\n",
"\n",
"\n",
" \n",
"#table\n",
"T=[20,30,40,50,55] #differnt temperature for different enthalpy calculation\n",
"#enthaly \n",
"H_bar=[101.79,133.0,166.49,210.0,278.72] #H_bar i.e. at equl.\n",
"Hg=[71.09,103.00,140.00,173.00,211.09] #Hg i.e. of operating line\n",
"i=0;\n",
"y = [0,0,0,0,0]\n",
"while(i<5): #looping for different enthalpy calculation of operating line\n",
" y[i]=1./(H_bar[i]-Hg[i]);\n",
" print \"\\n the enhalpy at :%f is :%f\"%(T[i],y[i]);\n",
" i=i+1;\n",
"\n",
"plot(Hg,y,\"o-\");\n",
"\n",
"#area under this curve gives Ntog =4.26\n",
"Ntog=4.26; #no. of transfer unit\n",
"Gs=10000.; #gas flow rate\n",
"Htog=Gs/Ky_a; # height of transfer unit\n",
"height=Ntog*Htog; #height of the tower\n",
"print \"\\n \\nthe tower height is :%f m\"%height\n",
"\n",
"\n",
"#M = E + B + W\n",
"W=.2/100 *L*60; #windage loss(W)\n",
"B=0; #blow down loss neglected\n",
"E=G_actual*(.064-.016); #assuming air leaves fully saturated\n",
"M = E + B + W; #make up water is based onevaporation loss(E),blow down loss(B),windage loss(W)\n",
"print \"\\n make up water is based onevaporation loss(E),blow down loss(B),windage loss(W) is :%f kg /hr\"%M\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
"For more information, type 'help(pylab)'.\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the enhalpy at :20.000000 is :60.734880\n",
"\n",
" the enhalpy at :30.000000 is :71.086320\n",
"\n",
" the enhalpy at :40.000000 is :81.437760\n",
"\n",
" the enhalpy at :50.000000 is :91.789200\n",
"\n",
" the enhalpy at :55.000000 is :96.964920\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"C:\\Anaconda\\lib\\site-packages\\matplotlib\\legend.py:336: UserWarning: Unrecognized location \"Enthalpy at saturated cond\". Falling back on \"best\"; valid locations are\n",
"\tright\n",
"\tcenter left\n",
"\tupper right\n",
"\tlower right\n",
"\tbest\n",
"\tcenter\n",
"\tlower left\n",
"\tcenter right\n",
"\tupper left\n",
"\tupper center\n",
"\tlower center\n",
"\n",
" % (loc, '\\n\\t'.join(self.codes.iterkeys())))\n"
]
},
{
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAYcAAAEXCAYAAABGeIg9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nXJQcRETERclBRERc3gD5uXssNmBL3wAAAABJRU5ErkJggg==\n"
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" \n",
" the maximum area of the tower(based on gas) is :7.169260 m**2\n",
"\n",
" the maximum area of the tower(based on liquid) is :10.000000 m**2\n",
"\n",
" the enhalpy at :20.000000 is :0.032573\n",
"\n",
" the enhalpy at :30.000000 is :0.033333\n",
"\n",
" the enhalpy at :40.000000 is :0.037750\n",
"\n",
" the enhalpy at :50.000000 is :0.027027\n",
"\n",
" the enhalpy at :55.000000 is :0.014786\n",
"\n",
" \n",
"the tower height is :17.040000 m"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
"\n",
" make up water is based onevaporation loss(E),blow down loss(B),windage loss(W) is :3681.244571 kg /hr\n"
]
},
{
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAD9CAYAAABTJWtQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n3JueAAAAAElFTkSuQmCC\n"
}
],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.11"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
" \n",
"T1=30.; #temperature at the inlet in degree celcius\n",
"T2=17.; #temperature at the exit in degree celcius\n",
"f=100000.; #flow rate of water in kg/hr\n",
"hi=.004; #humidity of incoming air in kg/kg of dry air\n",
"hl=.015; #humidity of leaving air in kg/kg of dry air\n",
"Hi=18.11; #enthalpy of incoming air in kg/kg of dry air\n",
"Hl=57.16; #enthalpy of leaving air in kg/kg of dry air\n",
"#w=mdry*(hl-hi) = mdry*0.011; -----equn 1st \n",
"#mass of water evaporated\n",
"\n",
"#making energy balance: total heat in = total heat out\n",
"#heat in entering water + heat in entering air = heat in leaving water + heat in leaving air\n",
"#100000*1*(30-0) + mdry*Hi = (100000-w)*1*(17-0) + mdry*Hl ----eqn 2nd\n",
"\n",
"#substituting eqn 1st in 2nd we get;\n",
"a=14.4; #cross sectional area of the tower in m**2\n",
"\n",
"# Calculation \n",
"mdry=(T1*f-T2*f)/(Hl-Hi-T2*.011); #mass of dry air\n",
"velocity=mdry/a; #air velocity in kg/m**2* hr\n",
"x=mdry*.011; #make up water needed in kg/hr\n",
"\n",
"# Result\n",
"print \"\\n the make up water needed is :%f kg /hr\"%x\n",
"print \"\\n the velocity of air is as :%f kg/hr\"%velocity\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the make up water needed is :367.959241 kg /hr\n",
"\n",
" the velocity of air is as :2322.975009 kg/hr\n"
]
}
],
"prompt_number": 22
},
{
"cell_type": "heading",
"level": 3,
"metadata": {},
"source": [
"Example 5.12 "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
" \n",
"import math\n",
" \n",
"\n",
"T1=65; #dry bulb temperature at the inlet in degree celcius\n",
"f=3.5; #flow rate of air in m**3/s\n",
"hi=1.017; #humidity of incoming air in kg/kg of dry air\n",
"hl=.03; #humidity of leaving air in kg/kg of dry air\n",
"k=1.12; #mass transfer coefficient in kg/m**3*s\n",
"y1=.017; #molefraction at recieving end\n",
"y2=.03; #molefraction at leaving end\n",
"\n",
"#substituting eqn 1st in 2nd we get;\n",
"a=2; #cross sectional area of the tower in m**2\n",
"d=1.113; #density o fair in kg/m**3\n",
"\n",
"# Calculation \n",
"m=(f*d) #mass flow rate of air\n",
"gs=m/hi; #air velocity in kg/m**2* hr\n",
"ys_bar=.032;\n",
"#for recirculation humidifier\n",
"# Result\n",
"z=math.log((ys_bar-y1)/(ys_bar-y2))*gs/k; #length of the chamber required\n",
"print \"\\n the length of the chamber required is :%f m\"%z\n",
"\n",
"#end"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\n",
" the length of the chamber required is :6.890939 m\n"
]
}
],
"prompt_number": 12
}
],
"metadata": {}
}
]
}
|