Opportunities for PhD student position in Neutron noise-based core monitoring in Small Modular Reactors
Major responsibilities
As a PhD student, you will develop, implement and test a neutron noise-based methodology for core monitoring and diagnostics applicable to small modular reactors. Your responsibilities also include taking courses for your doctoral education.
The position generally also includes teaching on Chalmers’ undergraduate level or performing other duties corresponding to 20 per cent of working hours.
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A PhD position in reactor physics is offered in the group ‘reactor physics, modeling and safety’ and relates to projects within the Swedish competence centre ANItA (Academic-industrial Nuclear technology Initiative to Achieve a sustainable energy future) integrating Swedish technical and nontechnical expertise of Uppsala University, Chalmers, KTH, Vattenfall, Uniper, Fortum, Westinghouse Electric Sweden, Studsvik Nuclear and the Swedish Energy Agency in nuclear technology and engineering.
Collaborative research, development and education of the centre aim to create a Swedish knowledge and competence base needed for the introduction of novel nuclear power technologies such as Small Modular Reactors (SMRs) and providing relevant information, in particular, to policymakers for timely decisions on the future Swedish energy generation mix.
Within ANItA, the leading universities in Sweden collaborate with leading Nordic companies in the nuclear energy sector offering together a unique research environment and industrial application potential for doctoral students and postdocs with good opportunities for international partnership.
The PhD project is planned to investigate a technique for core monitoring and diagnostics applicable in future SMRs.
The technique will rely on the analysis of reactor neutron noise, i.e., the small, stationary fluctuations of the neutron flux in the reactor core. These fluctuations are always present and are related to different types of physical phenomena.
Following the evolution of neutron noise in time allows to identify and correct promptly possible perturbations that might negatively impact the operation and safety of the plant.
The technique will make use of neutron noise computational tools to study the system response to perturbations and a machine learning algorithm for the inverse problem that determines the perturbations given the system response.
The outcome of this project will ultimately support the design of SMRs, before their construction and exploitation. The project will also result in the establishment of state-of-art competences in core monitoring on the long term.
FURTHER INFO: https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=10918