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The analysis and simulation of aircraft engine behavior have garnered significant attention in the aeronautical industry, primarily due to its implications for performance, maintenance, safety, and sustainability. Our work successfully showcases the efficacy of utilizing time series data collected from our aircraft engines to construct a digital twin capable of dynamically emulating their real-time behavior. We then introduce a new methodology to model the physical engine's degradation and meticulously monitor its evolution over time. By continuously analyzing the simulated data against real-world performance measurements, our approach offers valuable insights into the engine's long-term behavior and health trajectory.