Difference between revisions of "Sensitivity calculations"
(→Direct scoring instead of event based scoring) |
|||
| Line 1: | Line 1: | ||
| − | Serpent relies on the collision history based first order GPT equivalent implementation<ref name="GPT"/> 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<ref name="GPT"/><ref name="ValtavirtaBEPU18"/> 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. In the future these capabilities may be used for uncertainty propagation <ref name="UncReport18"> |
== Input == | == Input == | ||
Revision as of 16:41, 9 October 2018
Serpent relies on the collision history based first order GPT equivalent implementation[1][2] 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. In the future these capabilities may be used for uncertainty propagation Cite error: Closing </ref> missing for <ref> tag
[3]
- ^ Cite error: Invalid
<ref>tag; no text was provided for refs namedGPT - ^ Cite error: Invalid
<ref>tag; no text was provided for refs namedValtavirtaBEPU18 - ^ Aufiero, M., Martin, M. and Fratoni, M. "XGPT: Extending Monte Carlo Generalized Perturbation Theory capabilities to continuous-energy sensitivity functions." Ann. Nucl. Energy, 96 (2016) 295-306.
