pyMAISE.datasets.load_xs

pyMAISE.datasets.load_xs()[source]

Load reactor physics data. There are 1000 samples with eight cross sections (XS) \([cm^{-1}]\) as inputs:

  • FissionFast: fast fission,

  • CaptureFast: fast capture,

  • FissionThermal: thermal fission,

  • CaptureThermal: thermal capture,

  • Scatter12: group 1 to 2 scattering,

  • Scatter11: group 1 to 1 scattering,

  • Scatter21: group 2 to 1 scattering,

  • Scatter22: group 2 to 2 scattering,

with output of \(k\), the neutron multiplication factor. This data was taken from [RSOGradyK19], a sensitivity analysis using the Shapley effect. The geometry of the problem is a pressurized water reactor (PWR) lattice based on the BEAVRS benchmark. The lattice utilizes quarter core symmetry in TRITON and is depleted to \(50~GWD/MTU\). The data was constructed using a two-step process:

  1. the uncertainty in the fundamental microscopic XS data was propagated,

  2. and these XSs were collapsed into a 2-group form using

\[\Sigma_x^g = \frac{\int_{\Delta E_g}dE\int_V\Sigma_{x, m}(E) \phi(r, E, t)dV}{\int_{\Delta E_g}dE\int_V\phi(r, E, t)dV}.\]

The Sampler module in SCALE was used for uncertainty propagation, and the 56-group XS and covariance libraries were used in TRITON to create 56-group homogeneous XSs using the above equation. The homogeneous XSs were then collapsed into a 2-group library. One thousand random samples were taken from the Sampler.

Returns:

  • data (xarray.DataArray) – Raw reactor physics data.

  • inputs (xarray.DataArray) – Cross sections.

  • outputs (xarray.DataArray) – \(k\), neutron multiplication factor, data.