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Modelling of Tritium Breeding in Molten Salt Reactors

Nuclear fusion is considered a clean energy source: it emits no CO2 and leaves little radioactive waste. It is important to start paving the path toward nuclear fusion whilst simultaneously moving away from fossil fuels and carbon emissions.
One of the challenges of nuclear fusion is the lack of tritium, which, together with deuterium makes up its fuel. This research is focused on utilizing one current method of nuclear fission technology, namely molten salt reactors, to generate at least the initial loads of tritium for the first fusion reactors.
Current research is primarily focused on providing tritium during the nuclear fusion reaction. However, it is also necessary to have a tritium supply whenever we start up a nuclear fusion reactor.
The largest source of tritium is the CANDU nuclear fission reactor. A typical 500 MW CANDU produces 130 g of tritium annually as a biproduct of power generation. However, a future commercial fusion power plant is expected to consume 300 g of tritium per day to produce 800 MW.
Thus, this research explores the possibility of breeding tritium in other fission reactors, in particular molten salt reactors (MSR).
MCNP4C was used to simulate a simple Molten Salt Reactor setting with 61 molten salt fuel channels and applying a molten salt blanket to study how the presence of specific elements in the blanket affects tritium production, as well as criticality.
The study relies on nuclear data from the National Nuclear Data Center (NNDC), and Oak Ridge National Laboratory (ORNL) as benchmark to verify the accuracy of the results.
The calculated output of tritium is 325 g/year for a 100 MW (th) reactor, which is considered a positive outcome that opens the door for more research in this direction. / Thesis / Master of Applied Science (MASc)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/29291
Date January 2023
CreatorsAl-Zubaidi, Hadeel
ContributorsBuijs, Adriaan, Engineering Physics
Source SetsMcMaster University
LanguageEnglish
Detected LanguageEnglish
TypeThesis

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