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Heavy duty F-Class gas turbine Digital Twin model for performance prediction and optimization

Nicola Varallo

Heavy duty F-Class gas turbine Digital Twin model for performance prediction and optimization.

Rel. Daniela Anna Misul, Simone Salvadori. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica, 2025

Abstract:

This project is carried out through a collaboration between Polytechnic of Tu- rin and EthosEnergy S.P.A., a company specialized in turbomachinery desi- gn, production, and maintenance of turbomachinery components. The aim of this study is the development of a Digital Twin model of an existing Heavy- Duty gas turbine to predict performance at all operating points and to optimise operation. The final objective is achieved using AxSTREAM, which includes various tools to design, analyze, and optimise the turbomachine. The AxSLICE tool is used to import the 3D geometry of the blades in the main software to create the preliminary model of both the compressor and the tur- bine. The mass flow rate, power, and other thermodynamic parameters can be obtained and compared with real data through Meanline (1D) and Streamline (2D) analysis of these preliminary models using AxSTREAM ION. This soft- ware allows the integration of different models facilitating the data exchange between them in order to accurately replicate the real behavior of the turbogas plant. At the end of the project, it is possible to develop the compressor operating points map, taking into account the cooling mass flow rate, focusing on the variation of the IGV opening angle under different operating conditions.

Relatori: Daniela Anna Misul, Simone Salvadori
Anno accademico: 2024/25
Tipo di pubblicazione: Elettronica
Numero di pagine: 70
Informazioni aggiuntive: Tesi secretata. Fulltext non presente
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Meccanica
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-33 - INGEGNERIA MECCANICA
Aziende collaboratrici: EthosEnergy Italia Spa
URI: http://webthesis.biblio.polito.it/id/eprint/35037
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