Independent research on optimizing tritium breeding in tokamak fusion reactors using Monte Carlo simulations.
1. Overview
I conducted an independent research project focused on improving tritium breeding in tokamak fusion reactors. The work explored how breeder-blanket design choices could improve fuel sustainability and support the long-term feasibility of fusion energy.
2. Approach
I built Python-based Monte Carlo simulations around a custom 3D tokamak model and evaluated the effects of breeder-blanket material, thickness, and lithium enrichment. The main challenge was balancing simplified modeling assumptions with enough physical detail to compare design tradeoffs across thousands of simulation runs.
3. Results
The simulations produced comparative data on tritium production and self-sufficiency across candidate blanket configurations. The project strengthened my experience with computational modeling, Python data analysis, nuclear materials, and communicating technical results in a research paper.
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