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Abstract In this paper, a case-study of SR-30 small scale straight turbojet engine with centrifugal compressor, reverse annular combustion chamber and axial turbine is conducted and serves as a pre-cursor for the development of Compressor Design tool. The first stage involves conducting experiments using SR-30 gas turbine engine to obtain operational characteristics from 45000–80000 RPM. The centrifugal compressor consists of 9 primary and 9 secondary blades with temperature and pressure probes at the inlet and exhaust locations of the compressor. A 1D thermodynamic analysis is conducted and an analytical framework is developed to obtain the compressor map at various mass flow rates and at various ambient pressure and temperature conditions. The second stage involves conducting numerical analysis and simulations using Bladegen and ANSYS CFX to obtain the obtain the efficiency parameters of the existing design. Using Bladegen, 12 different parameters such as blade angles, incidence angles, loss factors etc. are identified to refine design parameters, optimize performance at various design, off-design, steady-state and transient conditions. The final stage involves a development of machine learning methodology to create a physics-based data-driven model for predicting operational efficiency using the experimental data and an explicit inverse aerodynamic design methodology is developed to obtain the centrifugal compressor design parameters. A first-of-its-kind python based Graphical User Interface (GUI) is created as a plug-and-play software to obtain the design and performance parameters of the centrifugal compressor based on numerical simulations and machine learning methodologies.
Raghu et al. (Mon,) studied this question.