This thesis presents a methodology for reverse engineering and simulating a turbofan engine using only publicly available data, with a focus on performance modeling. The goal is to develop an accurate simulation model without proprietary manufacturer data, enabling cost-effective integration in FNPT (Flight and Navigation Procedures Trainer) simulators. The study outlines turbofan theory, covering key performance parameters, off-design behavior, and control systems. The methodology involves data collection from Type Certificate Data Sheets (TCDS), the ICAO Aircraft Engine Emissions Databank, and other sources. A design point analysis estimates the engine’s thermodynamic properties, followed by off-design calibration using scaled component maps and transient modeling. To validate the approach, the CFM56-5B4 engine is simulated in MATLAB/Simulink and Gas turbine Simulation Program (GSP). Transient response, thrust, and fuel consumption are compared against two flight tests. Results confirm that the model meets EASA CS- FSTD(A) accuracy requirements for FNPT simulators. The proposed framework provides a scalable solution for turbofan simulation, reducing reliance on costly manufacturer data. Future work may expand the model to other engines, enhance transient fidelity, and integrate malfunction simulations.
Questa tesi presenta una metodologia per il reverse engineering e la simulazione di un motore turbofan utilizzando esclusivamente dati pubblicamente disponibili, con un focus sulla modellazione delle prestazioni. L’obiettivo è sviluppare un modello di simulazione accurato senza dati proprietari dei produttori, consentendo un’integrazione economica nei simulatori FNPT (Flight and Navigation Procedures Trainer). Lo studio introduce la teoria dei motori turbofan, analizzando i parametri di prestazione, il comportamento off-design e i sistemi di controllo. La metodologia prevede la raccolta dati da Type Certificate Data Sheets (TCDS), ICAO Aircraft Engine Emissions Databank e altre fonti. Un’analisi del punto di progetto stima le proprietà termodinamiche del motore, seguita da una calibrazione off-design con mappe dei componenti scalate e modellazione transitoria. Per validare l’approccio, il motore CFM56-5B4 è simulato in MATLAB/Simulink e Gas turbine Simulation Program (GSP). Risposta transitoria, spinta e consumo di carburante vengono confrontati con due test di volo. I risultati confermano che il modello soddisfa i requisiti di accuratezza EASA CS-FSTD(A) per i simulatori FNPT. Il framework proposto offre una soluzione scalabile per la simulazione dei motori turbofan, riducendo la dipendenza dai costosi dati dei produttori. Gli sviluppi futuri potrebbero espandere il modello ad altri motori, migliorare la fedeltà delle simulazioni transitorie e integrare la simulazione delle anomalie.
Reverse engineering and simulation of an existing turbofan engine with sparse input data
SMURRA, TIBERIO ANTONIO
2023/2024
Abstract
This thesis presents a methodology for reverse engineering and simulating a turbofan engine using only publicly available data, with a focus on performance modeling. The goal is to develop an accurate simulation model without proprietary manufacturer data, enabling cost-effective integration in FNPT (Flight and Navigation Procedures Trainer) simulators. The study outlines turbofan theory, covering key performance parameters, off-design behavior, and control systems. The methodology involves data collection from Type Certificate Data Sheets (TCDS), the ICAO Aircraft Engine Emissions Databank, and other sources. A design point analysis estimates the engine’s thermodynamic properties, followed by off-design calibration using scaled component maps and transient modeling. To validate the approach, the CFM56-5B4 engine is simulated in MATLAB/Simulink and Gas turbine Simulation Program (GSP). Transient response, thrust, and fuel consumption are compared against two flight tests. Results confirm that the model meets EASA CS- FSTD(A) accuracy requirements for FNPT simulators. The proposed framework provides a scalable solution for turbofan simulation, reducing reliance on costly manufacturer data. Future work may expand the model to other engines, enhance transient fidelity, and integrate malfunction simulations.File | Dimensione | Formato | |
---|---|---|---|
2025_04_Smurra.pdf
accessibile in internet solo dagli utenti autorizzati
Descrizione: Tesi
Dimensione
2.23 MB
Formato
Adobe PDF
|
2.23 MB | Adobe PDF | Visualizza/Apri |
I documenti in POLITesi sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/10589/235128