Optimization of a coupled vane compressor

In this project a heuristic multi-objective algorithm has been employed to optimize the performance of the novel coupled vane compressor to improve its mechanical and volumetric efficiencies. The novel vane compressor was designed to reduce the material used for fabrication and have better energy co...

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Номзүйн дэлгэрэнгүй
Үндсэн зохиолч: Ng, Han Rong
Бусад зохиолчид: Ooi Kim Tiow
Формат: Final Year Project (FYP)
Хэл сонгох:English
Хэвлэсэн: Nanyang Technological University 2020
Нөхцлүүд:
Онлайн хандалт:https://hdl.handle.net/10356/139273
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author Ng, Han Rong
author2 Ooi Kim Tiow
author_facet Ooi Kim Tiow
Ng, Han Rong
author_sort Ng, Han Rong
collection NTU
description In this project a heuristic multi-objective algorithm has been employed to optimize the performance of the novel coupled vane compressor to improve its mechanical and volumetric efficiencies. The novel vane compressor was designed to reduce the material used for fabrication and have better energy consumptions as compared to its peers in the rotary compressor family. This will consequently bolster the impediment of global warming in the world where there is ever-growing demand for compressors. The study links a genetic algorithm optimization technique called the NSGA-II, in the field of evolutionary algorithms, with the mathematical models of the compressor. Therefore, tuning of some statistical parameters used in the GA algorithm is required in order to achieve the pareto optimal front and a good spread of solutions with less computational time. The results show that the GA has been successful applied to improve the performance of the coupled vane compressor. Indeed, such an algorithm, can be used in other multi-objective engineering problems.
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spelling ntu-10356/1392732023-03-04T19:54:55Z Optimization of a coupled vane compressor Ng, Han Rong Ooi Kim Tiow School of Mechanical and Aerospace Engineering mktooi@ntu.edu.sg Engineering::Mechanical engineering In this project a heuristic multi-objective algorithm has been employed to optimize the performance of the novel coupled vane compressor to improve its mechanical and volumetric efficiencies. The novel vane compressor was designed to reduce the material used for fabrication and have better energy consumptions as compared to its peers in the rotary compressor family. This will consequently bolster the impediment of global warming in the world where there is ever-growing demand for compressors. The study links a genetic algorithm optimization technique called the NSGA-II, in the field of evolutionary algorithms, with the mathematical models of the compressor. Therefore, tuning of some statistical parameters used in the GA algorithm is required in order to achieve the pareto optimal front and a good spread of solutions with less computational time. The results show that the GA has been successful applied to improve the performance of the coupled vane compressor. Indeed, such an algorithm, can be used in other multi-objective engineering problems. Bachelor of Engineering (Mechanical Engineering) 2020-05-18T07:54:11Z 2020-05-18T07:54:11Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/139273 en A202 application/pdf Nanyang Technological University
spellingShingle Engineering::Mechanical engineering
Ng, Han Rong
Optimization of a coupled vane compressor
title Optimization of a coupled vane compressor
title_full Optimization of a coupled vane compressor
title_fullStr Optimization of a coupled vane compressor
title_full_unstemmed Optimization of a coupled vane compressor
title_short Optimization of a coupled vane compressor
title_sort optimization of a coupled vane compressor
topic Engineering::Mechanical engineering
url https://hdl.handle.net/10356/139273
work_keys_str_mv AT nghanrong optimizationofacoupledvanecompressor