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Abstract

Screw compressors are widely used in industries such as manufacturing, energy, and construction, contributing significantly to industrial electricity consumption. Despite the growing market, projected to reach $19.37 billion by 2030 at a CAGR of 6.5%, multi-stage screw compressors face operational challenges, including rotor deformation, limited bearing life, ineffective cooling, and condensate dropout in high-pressure applications. This research addresses these challenges by developing a comprehensive modelling framework to enhance the performance and economic viability of multi-stage screw compressors.

The proposed framework integrates a conventional chamber model with machine learning techniques to perform thermodynamic analysis and optimisation. Key parameters such as profile clearances, rotor geometry, and fluid injection are optimised for both individual and final stages using evolutionary and probabilistic methods, achieving high accuracy while reducing computational costs. Experimental validation was conducted on a prototype two-stage oil-flooded air screw compressor for water-well applications, demonstrating the reliability of the model.

In addition to performance optimisation, this study presents an extensive economic analysis comparing single-stage and multi-stage compressors for power ranges of 22–315 kW and delivery pressures of 6–12 bar. A cost-effective design incorporating advanced rotor profiles and optimised sealing and cooling systems was developed. Over a 10-year lifecycle, the two-stage compressor showed a 20–75% reduction in operational costs, significantly lowering lifecycle expenses compared to its single-stage counterpart.

This research contributes to screw compressor technology by addressing the limitations of multi-staging, providing a proven modelling and optimisation methodology, and demonstrating the economic benefits of multi-stage systems for industrial applications.

Publication Type:	Thesis (Doctoral)
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TH Building construction T Technology > TJ Mechanical engineering and machinery
Departments:	School of Science & Technology > Engineering School of Science & Technology > School of Science & Technology Doctoral Theses Doctoral Theses

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