Study of the thermo-mechanical performances of the EU-DEMO Water-Cooled Lead Lithium Left Outboard Blanket segment

The development of a sound conceptual design for the Water-Cooled Lead Lithium Breeding Blanket (WCLL BB) is pivotal to make a breakthrough towards the selection of the driver blanket concept for the EU-DEMO. To this goal, a research campaign has been launched over the last years at the University of Palermo, in close cooperation with ENEA Brasimone, under the umbrella of EUROfusion. In this frame, the analysis of the thermo-mechanical behaviour of the WCLL Left Outboard Blanket (LOB) segment is being performed. In a first phase, the assessment of the segment's overall structural performances was addressed, allowing the investigation of its global response under the selected loading scenarios. On this basis, the local structural analysis of the central region and of the upper and lower regions presenting geometric discontinuities (namely those regions where the stiffeners numbers changes) is presented in this paper, with the aim of assessing in detail their structural behaviour under the nominal BB operating conditions as well as steady-state accidental loading scenarios. Adopting the sub-modelling technique, the displacement field calculated in previous LOB global structural analysis can be mapped and applied at the boundaries of each local model. Moreover, it is possible to include there some structural details missing in the global analysis, like the Segment Box cooling channels. In this way, it is possible to study the thermo-mechanical behaviour of these regions in detail, assuming at the borders the mechanical action of the rest of the structure. The assessment has been performed in compliance with the RCC-MRx code, adopting the set of criteria on the basis of the nature of the considered loading scenario. The obtained results showed a promising structural behaviour of the segment and highlighted the necessity to revise the attachment system layout, which originates excessive deformation leading to the prediction of high stress.