A Framework for Medium-Fidelity Ducted Fan Design Optimisation

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A Framework for Medium-Fidelity Ducted Fan Design Optimisation

Application of a Throughflow Solver in a Genetic Algorithm for Fast Optimisation

Master Thesis (2025)

Author(s)

T.S. Vermeulen (TU Delft - Aerospace Engineering)

Contributor(s)

Wilfried Visser – Mentor (TU Delft - Flight Performance and Propulsion)

Tomas Sinnige – Mentor (TU Delft - Flight Performance and Propulsion)

N.J. Wood – Mentor (GKN Aerospace Services Limited)

G La Rocca – Graduation committee member (TU Delft - Flight Performance and Propulsion)

A Sciacchitano – Graduation committee member (TU Delft - Aerodynamics)

Faculty

Aerospace Engineering

Optimization Genetic Algorithm - GA Design Optimization Multi Objective Optimization Genetic Algorithm Optimization Conceptual Aircraft Design Electric Ducted Fans Aircraft Propulsion Ducted Fan Optimization Framework U-NSGA-III Pymoo Propulsion Optimization MTFLOW Multi-passage ThroughFLOW Single Objective Optimization Flight Path Optimization Single Point Optimization

To reference this document use:

https://resolver.tudelft.nl/uuid:21c8fb7b-f2d5-4c79-a43c-367cc1537764

More Info

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Publication Year

2025

Language

English

Graduation Date

04-09-2025

Awarding Institution

Delft University of Technology

Programme

['Aerospace Engineering']

Faculty

Aerospace Engineering

Reuse Rights

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Abstract

This thesis presents a new medium-fidelity ducted fan analysis code, to bridge the current gap in compressible-flow analysis methods. The existing Multi-passage ThroughFLOW software is integrated into a unified code to extend its capabilities. This unified code forms part of a newly developed ducted fan optimisation framework that utilises a modern genetic algorithm. Validation against experimental data shows a significantly improved accuracy in both thrust and power coefficient modelling compared to currently used panel methods.

The optimisation framework is applied to several case studies, demonstrating the capabilities of the developed tools. Propulsor efficiency improvements up to 10% are obtained, with significant associated frontal area reductions. Single-objective and multi-objective single-point optimisations were demonstrated, and suggestions are made to improve the flight profile multi-point optimisation.

The framework's robustness and computational efficiency can make it suitable for broader applications, including multidisciplinary optimisation and integration into complete aircraft design workflows.
Related dataset 4TU.ResearchData: https://doi.org/10.4121/efc63362-65e5-4c5d-b787-27e44dafa52a

Files

Thesis_TSVermeulen_Final.pdf

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