| 000 | 02018nam a2200241 a 4500 | ||
|---|---|---|---|
| 001 | vtls000075728 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204539.0 | ||
| 008 | 131025t2013 my da f abm 000 0 eng d | ||
| 020 | _aTHE0003558(Local) | ||
| 039 | 9 |
_a201905152110 _bzulaiha _y201310251054 _znabilah |
|
| 040 | _aUMP | ||
| 090 | _aTJ260 .A97 2013 rs Bc. | ||
| 100 | 0 | _aAzri Marmoh | |
| 245 | 1 | 0 |
_aOptimal design of heat recovery system / _cAzri Marmoh |
| 260 |
_aKuantan, Pahang : _bUMP, _c2013 |
||
| 300 |
_axv, 72 p. : _bill. ; _c30 cm. + _e1 CD-ROM |
||
| 502 | _aProject paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang – 2013 | ||
| 504 | _aBibliography : p. 48-51 | ||
| 520 | 3 | _aHigh energy usage has been a huge problem in all areas of the chemical industry. With the growing awareness of green engineering, energy usage needs to be reduced by some means. This study explains how energy usage is reduced through atechnique called process integration which is achieved through mathematical programming. Software called Generalized Algebraic Modeling System (GAMS) is used to do the mathematical programming. Although many methods can be used, this paper covers the usage of Linear Programming (LP) to reduce energy usage. An ethylbenzene plant in Korea was used as a case study (Yoon et al., 2007) to verify the model developed. Transportation model was used as the mathematical model to solve this problem. The procedures involved 3 steps, (1) data extraction from the process data, (2) superstructure representation, and (3) mathematical modeling. The simulation results produced by GAMS were analysed based on three important criteria to select the valid match ups between hot streams and cold streams. As a result, usage of cooling and heating utility was reduced by 79.3% and 28.2% respectively. | |
| 650 | 0 | _aHeat recovery | |
| 999 |
_aVIRTUA40 _c3904 _d3910 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*9992 | ||