Axpo Power AG

Company

Axpo is driven by a single purpose – to enable a sustainable future through innovative energy solutions. As Switzerland's largest producer of renewable and nuclear energy and an international leader in energy trading and the marketing of solar and wind power, we combine the experience and expertise of more than 5000 employees driven by a passion for innovation, collaboration and impactful change. Through cutting-edge technologies, we innovate to meet the evolving needs of our customers in over 30 countries across Europe, the US and Asia.

Your responsibilities

In nuclear light-water reactors, deposition of trace substances dissolved in the reactor coolant occurs on the surface of fuel rods. Due to boiling, the solubility limit of various chemical compounds can be reached locally, which leads to the precipitation of dissolved substances. Such precipitations were observed in the Leibstadt nuclear power plant (KKL).

Axpo has a methodology to predict such depositions, based on subchannel-code simulations (with COBRA-TF) for the flow inside single fuel elements. However, the method and models should be improved and the process should be better automated. Comparing different designs and parameters will help to understand the underlying physical reasons for the processes that lead to precipitation. Furthermore, it allows to estimate the susceptibility of new fuel designs to such effects. Your work will improve the subchannel-code models of our fuel assemblies and the post-processing (Matlab or Python).

Your profile

• Knowledge of multiphase flows
• Coding skills (Python and Matlab)
• Interest to learn about subchannel-codes (any pre-knowledge is appreciated)
• Independent work attitude and approaching tasks with critical thinking.
• Written and spoken fluency in English (German is a plus).

We offer

You will have the opportunity to work alongside nuclear experts and apply your academic and research background in real industrial applications. In this project you will have the opportunity to work in a hybrid mode (office work in main headquarters in Baden and home-office). Depending on the outcome of the project, the internship could be extended by 6 months and/or a master thesis topic could be proposed.