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Most of the reactor physics aspects of the various fuel cycles can be analyzed using simple methods of neutron physics and fuel burn-up.
Therefore, data will be analyzed using simple descriptive statistics.
When the samples have been imported into canvasDB the data can be analyzed using simple commands in R. We created two separate installations of canvasDB to test the performance in different situations (see Figure 2).
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Data obtained were analyzed using simple percentage and chi square statistical tools.
The relationships between CMV values and in situ measurements (compactness and deflection) for three layers were analyzed using simple linear regression analysis.
The approach is applied to achieve mass conservation with semi-Lagrangian schemes and its performance is analyzed using simple one-dimensional overlapping grids and a two-dimensional spherical Yin Yang grid.
The potential of this method is analyzed using simple assumed stress fields via (i) parametric studies and (ii) comparison with other available studies: a semi-analytical solution and a more general FEM solution of sheet buckling by the Asymptotic-Numerical Method (ANM).
The rainfall and temperature trends were analyzed using simple linear regression and standardized precipitation index (SPI).
Data were analyzed using simple descriptive statistics.
The data was analyzed using simple percentages and logistic regression.
Data was analyzed using simple statistics, and qualitative responses were thematically analyzed using QDA.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com