Session: 06-03 Pressure gain combustion and propulsion cycles I

Submission Number: 176756

Multi-Objective and Multi-Point Optimization of Advanced Gas Turbine Architectures for Mission-Wide Performance 

The continuous pursuit of higher efficiency and lower environmental impact in aviation propulsion motivates the exploration of alternative thermodynamic cycles and engine configurations. In this work, an enhanced multi-architecture gas turbine model is analyzed and optimized, capable of generating a wide range of engine configurations, from conventional two-shaft turbofans to advanced concepts incorporating intercooling, recuperation, and reheating. Building upon previous work, where a multi-architecture modeling framework achieved up to a 3.3-percentage-point efficiency improvement over conventional power plants, this research further investigates optimization strategies for next-generation engines. The integration of rotating detonation-based reheating chambers increases power density, enabling compact architectures that maintain thrust levels while reducing engine size, offering potential benefits in mass reduction, lower drag, and broader aircraft compatibility.

To systematically explore the design space and balance competing performance targets, a comprehensive multi-objective, multi-point optimization framework is developed. This formulation aims to simultaneously maximize efficiency and minimize system weight, supported by an in-house weight estimation methodology. Unlike traditional single-point optimizations focused on cruise performance, the framework adopts a multi-point strategy encompassing take-off, climb, and cruise conditions, ensuring consistent performance across the mission envelope. The model is formulated as a mixed-integer nonlinear programming problem comprising both continuous and discrete variables that define key architectural features, including total engine mass flow, the presence of secondary and tertiary streams, overall pressure ratio, turbine inlet temperature, the fraction of air being reheated and the sizing of the heat exchanger. The optimization algorithm is evaluated simultaneously at various operating points, each assigned a specific weighting within the objective function and specific constraints to reflect its relative importance. In addition, to promote the identification of the system global optimum, the routine employs multi-start global search algorithm specifically adapted to handle the problem’s high dimensionality and inherent non-convexity. Results show that the proposed framework effectively identifies architectures offering superior efficiency–weight trade-offs compared to conventional high-bypass turbofans. The multi-point approach also uncovers design synergies and trade-offs that remain hidden in single-point analyses. Once key architectural parameters, such as core size, bypass ratio, and recuperator dimensions, are established, the model can be embedded in a control system to determine optimal operating conditions that minimize fuel consumption throughout the flight envelope. This integrated approach allows the same mathematical model to support both conceptual design and in-flight operational optimization by deciding the combination of fuel injections, core and tertiary flow distributions that meet the required thrust along each point of the flight envelope while minimizing the fuel consumption, ensuring consistent energy management throughout the mission.

The findings of this study demonstrate that the proposed methodology identifies engine architectures with superior efficiency–weight trade-offs relative to conventional high-bypass turbofans, while enabling dynamic control strategies that further enhance mission efficiency. The multi-point optimization also uncovers design synergies and performance trade-offs that remain hidden under single-point analyses, providing valuable insights into conceptual aeroengine design. The jointly optimized architectures and power plant control during the mission deliver improved performance across all flight segments, scalability for diverse applications, and enhanced deployability for both aeronautical and distributed energy systems.

Presenting Author: Carlos Avila Catalan Universidad Rey Juan Carlos

Presenting Author Biography: Carlos Ávila Catalán earned both his Bachelor’s and Master of Science degrees in Aerospace Engineering from Rey Juan Carlos University (URJC) in Madrid, where he also worked as a research assistant on projects involving engine modeling and optimization. This early research experience laid the foundation for his current work as a Ph.D. candidate at URJC.
His doctoral research focuses on the development and optimization of thermodynamic models for gas turbines, aiming to advance cleaner and more efficient propulsion technologies. Alongside his thesis, Carlos is actively involved in experimental testing campaigns at the university’s Supersonic Wind Tunnel (LEAT), where he combines aerodynamic experimentation with computational modeling to understand better and improve propulsion system performance.

Authors:

Carlos Avila Catalan Universidad Rey Juan Carlos
Jorge Saavedra Universidad Rey Juan Carlos
Luis Cadarso Universidad Rey Juan Carlos