Bachelor / Master Thesis: Stability Investigations on an Adjoint CFD Solver for Turbomachinery Design - Inklusiver Job

Kennziffer – D MUC AEAB #UPLIFTYOURFUTURE Wir sind über 13.000. An 19 Standorten weltweit. Jedes dritte Flugzeug fliegt mit unserer Technologie. Immer effizienter, leiser, nachhaltiger. Wir gestalten die Zukunft der Luftfahrt. Was wir noch brauchen? Dich. Unser Team sucht Dich: Bachelor / Master Thesis: Stability Investigations on an Adjoint CFD Solver for Turbomachinery Design in München Kennziffer – D MUC AEAB Reduction of emissions, weight, and vibrations while increasing efficiency are goals for the design of the next generation of civil aircraft engines. To reach these technological goals, advanced aerodynamic designs of engine components need to be developed, which increase performance and yet fulfil multiple design constraints. While the single stage numerical optimization of a compressor or turbine is a mature technology, the optimization of multi-stages up to a full module or multiple modules is not. Due to the higher dimensional problem, it requires a gradient-based approach using the adjoint method to evaluate gradients of aerodynamic constraints and targets (efficiency, massflow, surge margin etc.) with respect to blade parameters (stagger angle, chord length, curvature etc.). However, our algorithmically differentied CFD solver faces sometimes instabilities when solving the adjoint system of equations. For this reason, stability methods are a prime subject for this study. In this project, a combination of various solution and stability methods must be studied on representative compressors and turbine test cases. The goal is to propose more efficient methods of stabilizing and accelerating the adjoint calculations while being as robust as the method currently in use. The researched methods would then be implemented in the adjoint CFD solver and their performance confirmed. Finally, a shape optimization employing the improved adjoint CFD solver will be carried out. STARKE AUFGABEN Get familiar with the adjoint method for aerodynamic optimization and stabilization methods for large PDE systems (e.g. Anderson Acceleration, Recursive Projection Method, Krylov Subspace methods, preconditioning) Benchmark existing methods using MTU’s computational and optimization tools Evaluate and compare methods such as RPM, GMRes, and Anderson Acceleration on compressor and turbine test cases Analyze performance and convergence behavior for each approach Develop and test improvements by tuning solver parameters or extending existing methods Implement the most promising stabilization method in our C++ adjoint CFD solver Validate the improved solver through benchmark and optimization studies BESTE VORAUSSETZUNGEN Excellent mathematical basis (especially linear algebra) Good programming skills in C++ and Python Comfortable in English for work environment Comfortable in Linux Environment is mandatory Basic knowledge of aerodynamics and CFD simulation process Idealerweise stehst du für einen Zeitraum von mindestens acht Wochen zur Verfügung. AUSGEZEICHNETES UMFELD Einblicke in die Luftfahrtbranche und Jobs mit Verantwortung Teamspirit u.a. durch Studi-Netzwerk & Events Mentoring und individuelle Betreuung Flexible Arbeitszeitmodelle mit mobilem Arbeiten Kantine, Cafébar und Verkaufsshops Sportkooperation mit EGYM Wellpass & Betriebssportgruppen Top-Anbindung durch Pendlerbus, Parkhaus, E-Ladestation STARTKLAR? Dann gib deiner Bewerbung Schub und schick uns deine Unterlagen (Lebenslauf, Notenübersicht der Hochschule, Schulabschlusszeugnis sowie eine aktuelle Immatrikulation) online. Gleich jetzt, gleich hier. Wir freuen uns auf Dich Recruitingteam