EventsThe 1st International Online Conference on Aerospace
Published
This submission belongs to the session S2. Sustainable Propulsion & Energy Systems of the event The 1st International Online Conference on Aerospace
Published date
13 Apr, 2026
Academic Editor
author-avatarStephen Whitmore
Citation
Carlos Ávila Catalán, Jorge Saavedra García, Luis Cadarso Morga, Balancing the Environmental Trade-off: Simultaneous Minimization of Carbon and Nitrogen Emissions in Novel Aero-Engine Cycles, in Proceedings of The 1st International Online Conference on Aerospace, 16 April–17 April 2026, MDPI: Basel, Switzerland
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Balancing the Environmental Trade-off: Simultaneous Minimization of Carbon and Nitrogen Emissions in Novel Aero-Engine Cycles

1. Department of Signal Theory and Communications and Telematic Systems and Computation, Fuenlabrada School of Engineering, Rey Juan Carlos University, Fuenlabrada, 28943, Spain, Spain
Abstract

The aviation sector faces an urgent mandate to decarbonize while simultaneously limiting the emission of harmful pollutants. This work presents a Mixed-Integer Nonlinear Programming (MINLP) framework for the design of next-generation gas turbine engines, specifically targeting the trade-off between CO₂ reduction and NOx mitigation. The model encompasses advanced architectures featuring Rotating Detonation Combustion (RDC), intercooling, heat recuperation, and three-stream flow management, enabling transitions from conventional Joule–Brayton to complex Joule–Humphrey cycles.

The modeling framework integrates semi-empirical correlations linking local thermodynamic conditions—specifically flame temperature and residence time—to NOx formation rates via the Zeldovich mechanism, while CO₂ emissions are minimized through specific fuel consumption optimization. These emission models are coupled with a rigorous thermodynamic cycle solver, yielding a bi-objective formulation that simultaneously minimizes the two primary environmental contributors over a representative cruise mission, without the confounding influence of weight penalties.

Optimization is performed using a Multi-Start Physics-Acquainted Branch and Bound (MS-PABnB) algorithm, which exploits interdependencies among binary architectural decisions to efficiently navigate the non-convex design space. Pareto fronts are generated for three thrust classes (10 kN, 30 kN, 50 kN), strictly quantifying the environmental cost of disparate architectural choices. Our results demonstrate that Optimized Novel Architecture Engine Designs (ONAEDs) can unlock unique design points where advanced cooling and reheating strategies mitigate the traditional penalty of rising NOx associated with high-efficiency cycles, offering a pathway toward truly sustainable propulsion.

Keywords
Sustainable Propulsion
Multi-Objective Optimization
Advanced Gas Turbines
Emissions Reduction
MINLP
INDUSTRIAL APPLICATION OF PARAMETRIC CONCEPTUAL LOADS LOOP
Interpretable Machine Learning for Nonlinear Control via Kolmogorov–Arnold Decomposition