Difference between revisions of "Sensitivity calculations"
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Serpent relies on the collision history based first order GPT equivalent implementation (cite to Manu's paper) to calculate sensitivities of various responses to various perturbations. As a simple example, the sensitivity of the effective multiplication factor to the different nuclear cross sections can be calculated. | Serpent relies on the collision history based first order GPT equivalent implementation (cite to Manu's paper) to calculate sensitivities of various responses to various perturbations. As a simple example, the sensitivity of the effective multiplication factor to the different nuclear cross sections can be calculated. | ||
Revision as of 13:58, 4 May 2017
Serpent relies on the collision history based first order GPT equivalent implementation (cite to Manu's paper) to calculate sensitivities of various responses to various perturbations. As a simple example, the sensitivity of the effective multiplication factor to the different nuclear cross sections can be calculated.
Contents
Implementation
Input
Adding a response
set sensresp NAME FLAG
Where the different response names and flags are as follows
Adding a perturbation
set senspert NAME FLAG
Where the different perturbation names and flags are as follows
| NAME | explanation of NAME | FLAG | explanation of FLAG |
| xs | perturbation of basic cross sections | 0/1 | OFF/ON |
| chi | perturbation of fission spectrum | 0/1 | OFF/ON |
| nubar | perturbation of fission nubar | 0/1 | OFF/ON |
| eleg | perturbation of Legendre moments of elastic scattering angular distribution |
0/1/2/3/4/5/6/7 | Number of Legendre moments to perturb. |
set senspert zai all
Additional options
Number of latent generations.
IFP chain length.
Response based tallying or event based tallying.
Event bank.
