Multi-mission Constraint-Oriented Optimization Methodology for Turboshaft–Turbofan Conversion Engine Performance Parameter Matching

A simulation-based optimization method for matching turboshaft–turbofan conversion-engine performance across multiple aircraft missions improved a calculated comprehensive performance index by approximately 65.9% over a baseline design. The study, published in the International Journal of Aeronautical and Space Sciences , examined a variable-configuration propulsion concept intended for next-generation stop-rotor and folding tiltrotor aircraft. The result is a model-based performance estimate rather than a measurement from an operating aircraft or flight test.

The researchers first analyzed the engine’s structural configuration and operating principles. They then developed a component-level performance simulation model that can evaluate steady-state characteristics in both turboshaft and turbofan modes. Building on that model, they created a multi-mission performance-matching and optimization framework connected to aircraft mission profiles.

Ground takeoff and high-altitude cruise served as the two target operating conditions, with power, thrust and specific fuel consumption included as constraints. The objective was to identify a suitable combination of engine parameters that could satisfy these conditions across the two operating modes. Solving the resulting optimization problem was computationally difficult because the model’s variables were strongly coupled and the resolution process was complex.

The authors introduced the Octopus Optimization Algorithm, or OOA, to search for the constrained parameter match. In the study’s simulation results, the OOA-optimized scheme produced an approximately 65.9% improvement in the comprehensive performance index relative to the baseline design. This figure describes the study’s calculated composite index; it does not represent an independently reported 65.9% increase in thrust, a reduction in specific fuel consumption, or a measured flight-performance gain.

The study also compared OOA’s computational time with that of the Sparrow Search Algorithm and Particle Swarm Optimization. Under the reported test conditions, OOA reduced computation time by at least 49% compared with those two algorithms. The authors therefore characterized OOA as more applicable and efficient for the particular multi-constrained, variable-configuration engine parameter-matching problem they studied.

The supplied evidence does not establish that the same computational advantage would occur for every propulsion design.

Subject of Research: Simulation-based multi-mission performance matching and optimization of a turboshaft–turbofan conversion engine

Article Title: Multi-mission Constraint-Oriented Optimization Methodology for Turboshaft–Turbofan Conversion Engine Performance Parameter Matching

Article References: Li, Z., Wang, Y., Chen, H., & Zhang, H. (2026). Multi-mission Constraint-Oriented Optimization Methodology for Turboshaft–Turbofan Conversion Engine Performance Parameter Matching. International Journal of Aeronautical and Space Sciences. https://doi.org/10.1007/s42405-026-01309-1

Image Credits: AI Generated

DOI: 10.1007/s42405-026-01309-1

Keywords: aero engines, turboshaft engines, turbofan engines, aircraft propulsion, multi-mission optimization, constraint optimization, Octopus Optimization Algorithm, specific fuel consumption, tiltrotor aircraft, computational engineering, Multi-mission, Constraint-Oriented