Data-enhanced dynamic flight simulations for flight performance analysis

More often than not, airlines use aircraft in operating scenarios beyond their optimal design conditions, which negatively affects performance characteristics. These effects are statistically reflected flight operational data, indirectly constrained by air transportation management as well design. In this research, we develop a data-enhanced methodology for modeling dynamic simulations of to enable accurate estimation parameters. The relevant phases and constraints these determined employing supervised machine learning on the data. is demonstrated simulating flights across representative short-, medium-, long-haul sectors using data shared our airline partner. We compare fuel burn time calculation results with those from Bréguet range endurance equations, an available open-source model, reference validation. developed simulation model designed such way analysis even when high-fidelity force analyses control models absent, common preliminary frameworks. This will further incorporating into processes.