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Harding Distinguished Postgraduate Scholars Programme

 


  Maximilian Kraus, mhgk4@cam.ac.uk

  Germany

  Engineering, Homerton College

  PhD thesis: Development of a Time-Dependent Random Ray Method for High-Accuracy Neutron Flux
  Simulations

  Research interests:
  1. Advanced nuclear reactor systems.
                                       2. Nuclear spacecraft propulsion.
                                       3. Computational reactor modelling.
                                       4. Stability analyses of dynamical systems.

My PhD focuses on developing a novel neutron transport method for transient neutron flux simulations. The neutron flux is the most essential quantity that characterises the behaviour of a nuclear reactor. Especially for the simulation of its time-dependent behaviour, which is crucial for safety assessment, significant simplifications are often applied to make the neutron transport equation accessible to numerical calculations at a reasonable computational cost. While these methods are proven tools for conventional power reactor modelling, they might not be adequate for all future innovative reactor concepts, often smaller in size with a complex geometry and diverse materials. My work will introduce a time-dependent neutron transport solver based on the novel random ray method, which is able to deliver high-accuracy results for nuclear engineering problems of any complexity.

Who or what inspired you to pursue your research interests?
I was inspired to pursue my research interests by the benefits that nuclear reactor systems offer for reducing greenhouse gas emissions in electricity generation while having a low environmental impact due to their high power density. Making a contribution to solving the climate and biodiversity crisis is my personal ambition since I have been involved with nature conservation societies for a long time. During my previous studies, I had the opportunity to investigate a broad variety of power sources and I found nuclear power systems to be the most promising option for delivering an answer to both aforementioned challenges.