Internship about Investigation of CFD High-Fidelity Methods for Robust Data Generation

Job Description:

In order to support Flight Physics, Airbus Defence and Space is looking for a

I nternship about Investigation of CFD High-Fidelity Methods for Robust Data Generation (d/f/m)

Are you looking for an internship ? Then apply now! We look forward to you supporting us as an intern (d/f/m)!

• Location: Manching
  
• Start: a s soon as possible
  
• Duration: 3-6 months
  

Your location

Located about an hour’s drive north of Munich, Manching is an up-and-coming market town that offers a wide range of leisure and cultural activities. Here, you can enjoy the quality of life in the countryside while the pleasures of near-by cities are still within easy reach.

Your benefits

• Attractive salary and work-life balance with a 35-hour week (flexitime).
  
• A final thesis is possible after consultation with the department.
  
• Mobile working after agreement with the department.
  
• Traveling overseas or within Germany (team events) is possible after consultation and agreement from the department.
  
• International environment with the opportunity to network globally.
  
• Work with modern/diversified technologies.
  
• At Airbus, we see you as a valuable team member and you are not hired to brew coffee, instead you are in close contact with the interfaces and are part of our weekly team meetings.
  
• Opportunity to participate in the Generation Airbus Community to expand your own network.
  

General background and topic description

For the past decade, the Flight Physics department at Airbus DS has identified fuel slosh modeling as a strategic priority. As next-generation aircraft become increasingly agile and fuel mass ratios grow, the traditional "stationary fuel" approach-which relies on conservative and often inefficient assumptions regarding Center of Gravity (CoG)-is becoming obsolete.

To push the boundaries of aircraft maneuverability, payload flexibility, and flight control efficiency, Airbus is moving toward a multi-fidelity modeling approach. Our goal is to develop a spectrum of tools: from low-fidelity models for real-time "sloshing-in-the-loop" simulations, to mid-fidelity models for rapid estimation, and high-fidelity CFD models for precise offline analysis and system identification.

By accurately modeling these effects, we aim to reduce unnecessary conservatism in flight mechanics clearance, lower development costs, and enable flight control law designers to implement advanced methods that offset sloshing effects, ultimately enhancing aircraft stability and performance.

The primary objective of this project is to develop a standardized, robust pipeline for executing CFD simulations within the OpenFOAM framework. To ensure high-fidelity results, these simulations will be validated against empirical data acquired during our upcoming experimental campaign. Furthermore, the project will investigate the implementation of novel numerical methods, specifically SPH, FPM, different commercial and open-source versions, as a high-performance alternative to traditional solvers.

A critical requirement of this pipeline is its cleanliness and scalability, as the resulting simulation data will serve as a key deliverable for external partners to facilitate the generation of low-order models. It is expected that a conclusion on the viability of novel methods is made taking into consideration: Robustness, accuracy, computational efficiency, availability and cost.

Your main tasks and responsibilities may include:

1. Literature review on mesh-based and Lagrangian methods

2. CFD Pipeline Development

3. Experimental Validation using CFD4. Methodological Exploration (Mesh-based and Lagrangian methods)5. Data Generation for Model Training

• Currently pursuing a Master’s or PhD in Aerospace Engineering, Mechanical Engineering, Computational Fluid Dynamics (CFD), or a closely related computational science field
• Hands-on experience with OpenFOAM is highly desirable
• Proficiency in working within a Linux/Unix environment
• Strong scripting skills in Python for the development of automated simulation pipelines
• Ability to process and interpret large-scale CFD datasets
• Prior exposure to or a deep interest in meshless methods, i.e., Smoothed Particle Hydrodynamics (SPH)
• Experience in validating numerical models against experimental/empirical datasets

Please upload the following documents: cover letter, CV, relevant transcripts, enrollment certificate.

Not a 100% match? No worries! Airbus supports your personal growth.

Take your career to a new level and apply online now!

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:
Airbus Defence and Space GmbH

Employment Type:
Internship
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Experience Level:
Student

Job Family:
Support to Management

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