Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions
Also available in printed version
| Auteur principal: | |
|---|---|
| Autres auteurs: | |
| Format: | Doctoral thesis |
| Langue: | anglais |
| Publié: |
Universiti Teknologi Malaysia
2025
|
| Sujets: | |
| Accès en ligne: | https://utmik.utm.my/handle/123456789/51484 |
| Abstract | Abstract here |
| _version_ | 1854975090572132352 |
|---|---|
| author | Nor Atiqah Zolpakar |
| author2 | Normah Mohd. Ghazali, supervisor |
| author_facet | Normah Mohd. Ghazali, supervisor Nor Atiqah Zolpakar |
| author_sort | Nor Atiqah Zolpakar |
| description | Also available in printed version |
| format | Doctoral thesis |
| id | utm-123456789-51484 |
| institution | Universiti Teknologi Malaysia |
| language | English |
| publishDate | 2025 |
| publisher | Universiti Teknologi Malaysia |
| record_format | dspace |
| record_pdf | Abstract |
| spelling | utm-123456789-514842025-08-21T06:43:45Z Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions Nor Atiqah Zolpakar Normah Mohd. Ghazali, supervisor Mechanical engineering Also available in printed version In today’s global concerns over the finite resources available, global warming, and the depletion of the ozone layer, thermoacoustic cooling is a potential technology to reduce or eliminate the usage of ozone depleting refrigerant. The absence of refrigerants in the thermoacoustic refrigeration systems presents an attractive solution to these issues. However, the low performance characteristic of the systems needs to be addressed if they are to be seriously considered. This thesis presents the optimization of the thermoacoustic refrigerator using Single objective Genetic Algorithm (GA) and Multi-objective Genetic Algorithm (MOGA) to optimize the coefficient of performance (COP) of the system. Thermoacoustic parameters, geometric and operating parameters, are interdependent. Thus, the ability of genetic algorithm to optimize many parameters simultaneously is important which involves a global searching method to solve this problem. The parameters of the stack included in the algorithm are the stack length, stack centre position, plate spacing, drive ratio, and Prandtl number of the working fluid. A test rig was developed and experiments were conducted to compare the effects of the stack length, centre position, and plate spacing of the thermoacoustic refrigerator, with that obtained from the optimized outcomes from MOGA. In addition, three types of the stack geometry are investigated; parallel, spiral and celcor. By using MOGA, the COP obtained is 1.35 which is lower compared with GA which is 1.93 but at the same time, the cooling load obtained by using MOGA is 6.33 Watt which is higher compared 3.56 Watt that obtained by using GA. Results showed that MOGA has the ability to come out with higher cooling load and COP by fine tuning the parameters to produce the optimum system compared with previous optimization works. MOGA showed a possible 58 percent higher in cooling load and 12 percent in COP. The experimental results support the MOGA optimization outcomes by achieving highest temperature difference at both end of stack which is 18.1ºC and confirmed that values other than the optimized stack length, stack centre position, and the stack separation gap, did not give the desired high performance of the thermoacoustic refrigerator fahmimoksen UTM 200 p. Thesis (Ph.D (Kejuruteraan Mekanikal)) - Universiti Teknologi Malaysia, 2016 2025-03-14T04:44:40Z 2025-03-14T04:44:40Z 2016 Doctoral thesis https://utmik.utm.my/handle/123456789/51484 vital:106366 valet-20180101-144351 ENG Closed Access UTM Complete Unpublished Completion application/pdf Universiti Teknologi Malaysia |
| spellingShingle | Mechanical engineering Nor Atiqah Zolpakar Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions |
| thesis_level | PhD |
| title | Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions |
| title_full | Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions |
| title_fullStr | Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions |
| title_full_unstemmed | Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions |
| title_short | Optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi-objective functions |
| title_sort | optimization of a standing wave thermoacoustic refrigrator using genetic algorithm with multi objective functions |
| topic | Mechanical engineering |
| url | https://utmik.utm.my/handle/123456789/51484 |
| work_keys_str_mv | AT noratiqahzolpakar optimizationofastandingwavethermoacousticrefrigratorusinggeneticalgorithmwithmultiobjectivefunctions |