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• W2980759852 abstract "In this study, calculation of the performance of an axial compressor from a twin-shaft industrial gas turbine (IGT) is carried out through a semi-empirical modelling framework. The modelling framework considers a flow analysis represented through theoretical air velocity diagrams in the multi-stage axial compressor. Design parameters, such asblade angle and annulus geometry across the different stages comprising the multi-stage axial compressor, are considered for the development of the modelling framework. Stagewise data generated through a High-Fidelity Design Tool (HFDT) during compressor simulation are considered for the validation of the modelling framework. The data comprise flow rate, rotational speed, inlet guide vane (IGV) position, variable stator guide vanes (VGVs) position, temperature, and pressure ratio across the different stages. The results demonstrate that it is possible for the developed modelling framework to predict the increase of pressure and temperature across the different stages of the compressor in a way similar to HFDT. Capability of the modelling framework to predict the effect of IGV position outside its nominal schedule on stage compressor performance is demonstrated through the construction of an overall compressor map and individual stage characteristic maps. In addition, the effect of a hypothetical VGV mechanism malfunction situation on stagewise pressure ratio is predicted. The effect of fouling which impacts the turning of the air passing through the blades in the axial compressor that lead to compressor performance deterioration is also predicted. This study couples the fundamental principles of axial compressors and a semiempirical modelling to include more physics into the low fidelity modelling framework." @default.
• W2980759852 created "2019-10-25" @default.
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• W2980759852 date "2019-09-16" @default.
• W2980759852 modified "2023-10-16" @default.
• W2980759852 title "Performance Calculation of a Multi-Stage Axial Compressor through a Semi-Empirical Modelling Framework" @default.
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• W2980759852 doi "https://doi.org/10.33737/gpps19-bj-123" @default.
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