Surrogate · Nuclear
Gaussian Process Regression for Nuclear
Apply the gaussian process regression to real nuclear problems — in the browser, with AI assistance.
GPs model outputs as draws from a distribution over functions, giving both predictions and calibrated uncertainty for expensive simulations.
In nuclear, teams face challenges like neutron transport, thermal-hydraulics, safety margins. The gaussian process regression directly supports use cases such as reactor kinetics, shielding attenuation, decay-heat modeling, and PolySim's AI Copilot can recommend settings and catch common setup errors before you run.
Typical Nuclear use cases
- Reactor kinetics
- Shielding attenuation
- Decay-heat modeling
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