Master Thesis GPU-Accelerated Particle Simulation for OpenFOAM

Job Description

In many industrial and research applications, tracking millions of particles within a fluid flow is essential, but current CPU-based methods are too slow. This project offers an exciting opportunity to break that bottleneck by building a state-of-the-art solver that leverages the massive power of modern GPUs to accelerate simulations by orders of magnitude. Join us in developing a cutting-edge tool that integrates directly with the industry-standard Computational Fluid Dynamics (CFD) software OpenFOAM, and make a significant impact on what's possible in computational science.

• As a part of your Master thesis, you will conduct a literature review on state-of-the-art methods for Lagrangian Particle Tracking, GPU computing in CFD and particle-wall interaction.
• You will develop a high-performance particle tracking solver using Python and the NVIDIA Warp framework to run on the GPU.
• In addition, you will implement a method for collision detection with complex 3D geometries and create a pre-processing pipeline to prepare simulation data (e.g., flow fields and meshes) from OpenFOAM for the GPU.
• Furthermore, you will integrate the new solver into a standard OpenFOAM workflow, establishing a seamless data exchange.
• Last but not least, you will validate and benchmark your solver's performance against OpenFOAM's native tools, quantifying the massive speedup.

Qualifications

• Education: Master studies in the field of Engineering, Physics or comparable
• Experience and Knowledge: profound knowledge of and experience in numerical simulation methods, as well as a solid understanding of continuum mechanics; very good programming skills in Python; initial experience with OpenFOAM, NVIDIA Warp and ParaView is desirable; ideally, initial experience with Git and working on HPC clusters
• Personality and Working Practice: you are able to proactively develop new ideas, find solutions independently and complete tasks efficiently, demonstrating a high degree of self-motivation
• Work Routine: partially mobile working possible, ideally with 3 - 4 office days per week
• Languages: business fluent in English and good in German

Additional Information

Start: according to prior agreement
Duration: 6 months

Requirement for this thesis is the enrollment at university. Please attach your CV, transcript of records, examination regulations and if indicated a valid work and residence permit.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need further information about the job?
Alexander Fuchs (Functional Department)
+49 711 811 93399

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