Public summary
A Master's student is sought to conduct a six-month thesis project focused on developing a multi-fidelity propeller optimization framework for hybrid-electric eVTOL aircraft. The project involves extending existing automated design workflows to integrate low- and high-fidelity aerodynamic and aeroacoustic models, with collaboration between a university aerodynamics team and a technical university. The role requires strong skills in aerodynamics, CFD, Python programming, and an interest in aeroacoustics, supporting efficient propeller designs across various flight conditions.
Location and work setup
- Location
- Ottobrunn
- Remote status
- Hybrid
- German requirement signal
- No German Required Detected
- Detected job language
- English
Responsibilities
Conduct literature review on propeller optimization and multi-fidelity approaches; familiarize with existing design optimization frameworks; integrate aeroacoustics prediction methods; develop strategies to combine low- and high-fidelity models into a multi-fidelity optimization workflow; update and unify geometry generation, CFD simulation, and post-processing; parametrize and optimize propeller designs; validate predictions against CFD reference solutions; undertake optimization studies for flight conditions; optionally use surrogate models to enhance optimization convergence; document methodology and findings in thesis report.
Qualifications
Enrollment in a Master's program in mechanical engineering, aerospace engineering, physics, or a related field at a technical university; familiarity with CAD and CFD software, ideally Siemens NX and Ansys Fluent; foundational knowledge of aircraft and propulsion aerodynamics; basic knowledge of numerical methods and optimization; strong Python programming skills; ability to work independently and collaboratively; good written and verbal English communication skills; interest in aeroacoustics and propeller noise prediction; prior exposure to Blade Element Momentum Theory, aeroacoustics prediction methods, HPC-based simulation workflows, and surrogate models is advantageous.