Abstract
The optimization process of compressors is usually regarded as a ‘black-box’ problem, in which the mathematical form underlying the relationship between design parameters and the design objective is impractical and costly to be obtained. To solve the ‘black-box’ problem, Bayesian optimization has been proven as an accurate and efficient method. However, the application of such a method in the design of compressors is rarely discussed, particularly no work has been reported in terms of the positive displacement type compressor. Therefore, this paper aims to introduce the Bayesian optimization to the design of positive displacement compressors through the optimization process of the novel limaçon compressor. In this paper, a two-stage optimization process is presented, in which the first stage optimizes the geometric parameters as per design requirements and the second stage focuses on revealing an optimum setting of port geometries that improves machine performance. A numerical illustration is offered to prove the validity of the presented approach.
Highlights
In compressor design, information solely obtained from the simulation of the mathematical model is usually insufficient to reflect the thorough relationship between the design parameters and design objective in terms of performance
Silva and Dutra [6] used the genetic optimization algorithm to find an optimum piston trajectory that maximizes the performance of the reciprocating compressor
The Bayesian optimization technique is applied in a two-stage optimization process of the limaçon compressor, where the first stage determines the size of the compressor as per design requirements and the second stage aims to optimize the setting of the port to improve machine performance
Summary
Information solely obtained from the simulation of the mathematical model is usually insufficient to reflect the thorough relationship between the design parameters and design objective in terms of performance. The authors reported that the optimum piston trajectory reduces the losses from the heat transfer and leakage, increasing the thermodynamic efficiency from 88.3% to 92.1% and the volumetric efficiency from 70.9% to 72%. In their latest work, Aw and Ooi [7] presented a comprehensive review of the previous investigation conducted on sliding-vane and rolling piston compressors. It is worth mentioning that the process executed by the compressor is rather intricate, and the mathematical expression underlying such a process is impractical to be obtained, leading to the optimization of the compressor becomes a ‘black-box’ problem For this kind of optimization problem, iterative methods such as direct-search or gradient-search are generally time-consuming and costly. Based on the result of the first stage, the second stage is intended to reveal the parameters of the port geometry, which contains the angular location, angular width, and the length of the port, that can maximize the machine performance, such as the isentropic efficiency and the volumetric efficiency
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