Turbulence properties and distribution of local heat transfer coefficients around horizontal tubes in the SINQ rod bundle target for non-uniform inlet conditions

During regular operation of the SINQ (Swiss Spallation Neutron Source) target at Paul Scherrer Institut, a proton beam current of 1.5 mA (575 MeV) hits the target. Since an upgrade program of the PSI accelerator, which aims at improving operational reliability and at increasing beam intensities, has been successfully conducted, an increased proton beam current of 2 mA can be supplied to the SINQ target in the near future. As the maximum heat deposited in the target material would then reach 640 W/cm3, the thermal-hydraulic and structural behaviour of some target rods can be significantly affected. One way to verify the cooling principle and cooling mechanism of a single rod filled with lead at high power deposition are successive experimental investigations coupled with computational studies. Namely, it is of crucial importance to determine the convective heat transfer coefficient at various locations along a rod in a bundle, as well as to investigate thermalhydraulic and structural behaviour of the rod during transients, which include the phase-change of lead, for various cooling conditions and/or boiling phenomena. As the first experiment in a series, a heat transfer experiment for a simplified rod bundle has been conducted. In order to investigate the flow field and to estimate local (along the perimeter) single-phase heat transfer coefficients for rods in a bundle for non-uniform inlet conditions, an experimental mock-up has been designed. The inlet conditions can be varied by shifting the jet nozzle along the inlet of a bundle. The inlet velocity profile and turbulent properties are measured by a Hot Wire (HW). The local distribution of the heat transfer coefficient and local turbulent intensities are measured by a Hot Film (HF). The experimental results are analysed, extrapolated and mapped into the successive computational studies. The computational results are compared with real operational data. (author)