Python-Based Performance and Emissions Analysis of Turbojet and Turbofan Engines

This study provides systematic computational analysis of turbojet and turbofan propulsion system performance and emissions characteristics using simulation modeling developed in Python programming language. Simulations were carried out using pyCycle software developed by NASA with the capability to simulate thermodynamic cycles of propulsion systems. Design-point and parametric analysis were also conducted to investigate the impact of major parameters like the compressor pressure ratio and turbine inlet temperature on engine performance. The model of turbojet and turbofan were created with component-level accuracy including the compressor, combustor, turbine, fan, and nozzle modules. The models were solved to convergence with state-of-the-art nonlinear solver algorithms interfaced with OpenMDAO. Results indicate that the turbofan engine achieves significantly higher thrust and greater fuel efficiency than the turbojet, with a 69.5% improvement in thrust and a 54.9% reduction in thrust-specific fuel consumption (TSFC) at the design point. Computation of emissions was conducted from calculated fuel mass flow rates and considering CO₂ production. The results indicate that the turbofan engine produces 13% less CO₂ per hour and nearly 49% less CO₂ per unit of thrust than the turbojet, validating the environmental benefits of high-bypass turbofan configurations. The study confirms the applicability of Python-based simulation frameworks for accurate propulsion system performance and emissions prediction. Future work will focus on incorporating alternative fuel models and predictive NOₓ emission calculations to expand the environmental impact assessment capabilities.