The topic addressed deals with the determination of adjoint parameters for instrumentation relevance. This is a crucial subject for comprehension of subcritical levels in the frame of safety analysis. Indeed, such states require interpretation and raw data cannot be processed as such. To do so, the transcription of core reactivity through instrumentation located in the reactor periphery is considered with the use of MSM factors [1],[2]. We implement this method inside a TRIPOLI4® [3] sequence in order to establish predictive mapping of MSM factors and figure out optimal position for instrumentation location at the beginning of reactor operations.
Firstly, MSM factors are introduced, along with the designer point of view for geometry construction based on ROOT package [4]. At this point, the methodology of TRIPOLI4® calculation is explained in detail, including the sequencing associated to and how the Green Functions are performed within TRIPOLI4®.
In this second part and within the verification framework, the previous method is extended to a “fictitious core” developed in TechnicAtome for Monte Carlo [5] calculation and for different core pattern loadings. After the completion of these numerical validations gained on a High Performing Cluster, the method is then expanded to critical mock up [6] and challenged to recent experimental results for validation. The comparisons end up with a good agreement between predictive calculation and experimental values of reactivity worth.
Finally the document ends with a mid-term projection for outlooks and improvements, for ensuring an enhancement of the safety approach. Several items are discussed especially, fine tuning for the spatial meshing (regarding instrumentation size) and the impact on TRIPOLI4® Monte Carlo code with the development of new features. Then, the authors focus on sensitivity effect concerning delayed neutron spectrum and kinetics parameters. As a conclusion, this paper proposes to validate the method exposed in the near future, using experimental data coming from many years of critical mock up operations.
The impact of surface morphology on the erosion of metallic surfaces – Modelling with the 3D Monte-Carlo code ERO2.0
