Optimization of a coupled vane compressor

• Main Author: Ng, Han Rong
• Other Authors: Ooi Kim Tiow
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2020
• Subjects: Engineering::Mechanical engineering
• Online Access: https://hdl.handle.net/10356/139273
• Institution: Nanyang Technological University

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.