Multi-objective optimization to increase the performance of a toroidal propeller

Abstract

This thesis focuses on optimizing the performance of toroidal propellers using Computational Fluid Dynamics (CFD) and Fluid-Structure Interaction (FSI). The study aims to enhance propulsion efficiency, reduce noise emissions, and ensure structural reliability. Toroidal propellers, characterized by their closed-loop blade design, offer unique advantages over conventional propellers, including reduced tip vortex formation and improved noise performance. The research begins with an overview of the historical evolution of propeller technology, emphasizing the renewed interest in propeller-based systems due to environmental and economic considerations. It highlights the potential of toroidal propellers to integrate the benefits of tandem and contracted and loaded tip (CLT) designs, addressing common challenges such as tip vortex intensity and aerodynamic inefficiencies. The optimization methodology incorporates advanced multi-objective techniques, including differential evolution algorithms and Pareto-front analysis. Objectives include maximizing efficiency, and maintaining structural integrity. Constraints and design variables are carefully defined, and metamodeling techniques like are used to reduce computational demands. A key component of the research is the optimization process, which employs the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). This algorithm is used for multi-objective optimization, balancing trade-offs between propulsion efficiency, thrust enhancement, and structural reliability. The NSGA-II method efficiently explores the design space, identifying Pareto-optimal solutions that satisfy the constraints and objectives. This approach ensures a diverse set of solutions, providing valuable insights into the trade-offs involved in propeller design. Blade parameterization and mesh generation are discussed in detail, with specific attention to the unique geometry of toroidal propellers. The research highlights the importance of accurate spatial discretization for reliable CFD and FSI analyses. The aerodynamic solver utilizes RANS-based methods to evaluate flow characteristics, while turbulence modeling techniques, including the k-omega SST model, are applied to improve prediction accuracy. FSI analysis is employed to assess the interplay between aerodynamic forces and structural responses. The finite element solver considers material properties, boundary conditions, and stress criteria to ensure structural reliability under operational loads. The results demonstrate significant improvements in performance metrics, including higher propulsion efficiency, reduced noise emissions, and enhanced structural stability. The thesis concludes that toroidal propellers represent a promising advancement in propulsion technology, capable of addressing modern aviation challenges. The findings provide a framework for future research and practical applications, contributing to the development of efficient and sustainable propeller systems. In this study, three new parameters required in the design of the toroidal propeller were determined as design variables and multi-objective optimization was performed. The effects of 3 different parameters on the target thrust increase, efficiency increase and stress reduction were examined and the findings were shared.