Numerical and theoretical investigations of heat transfer characteristics in helium-xenon cooled microreactor core

Helium-xenon cooled microreactors are a vital technological solution for portable nuclear reactor power sources.To exam-ine the convective heat transfer behavior of helium-xenon gas mixtures in a core environment,numerical simulations are conducted on a cylindrical coolant channel and its surrounding solid regions.Validated numerical methods are used to determine the effect and mechanisms of power and its distribution,inlet temperature and velocity,and outlet pressure on the distribution and change trend of the axial Nusselt number.Furthermore,a theoretical framework that can describe the effect of power variation on the evolution of the thermal boundary layer is employed to formulate an axial distribution cor-relation for the Nusselt number of the coolant channel,under the assumption of a cosine distribution for the axial power.Based on the simulation results,the correlation coefficients are determined,and a semi-empirical relationship is identified under the corresponding operating conditions.The correlation derived in this study is consistent with the simulations,with an average relative error of 5.3%under the operating conditions.Finally,to improve the accuracy of the predictions near the entrance,a segmented correlation is developed by combining the Kays correlation with the aforementioned correlation.The new correlation reduces the average relative error to 2.9%and maintains satisfactory accuracy throughout the entire axial range of the channel,thereby demonstrating its applicability to turbulent heat transfer calculations for helium-xenon gas mixtures within the core environment.These findings provide valuable insights into the convective heat transfer behavior of a helium-xenon gas mixture in a core environment.

Dynamic evaluation of a scaled-down heat pipe-cooled system during start-up/shut-down processes using a hardware-in-the-loop test approach

Micro-mobile heat pipe-cooled nuclear power plants are promising candidates for distributed energy resource power genera-tors and can be flexibly deployed in remote places to meet increasing electric power demands.However,previous steady-state simulations and experiments have deviated significantly from actual micronuclear system operations.Hence,a transient analysis is required for performance optimization and safety assessment.In this study,a hardware-in-the-loop(HIL)approach was used to investigate the dynamic behavior of scaled-down heat pipe-cooled systems.The real-time features of the HIL architecture were interpreted and validated,and an optimal time step of 500 ms was selected for the thermal transient.The power transient was modeled using point kinetic equations,and a scaled-down thermal prototype was set up to avoid mod-eling unpredictable heat transfer behaviors and feeding temperature samples into the main program running on a desktop PC.A series of dynamic test results showed significant power and temperature oscillations during the transient process,owing to the inconsistency of the rapid nuclear reaction rate and large thermal inertia.The proposed HIL approach is stable and effective for further studying of the dynamic characteristics and control optimization of solid-state small nuclear-powered systems at an early prototyping stage.

Differential expression of glial cell line-derived neurotrophic factor splice variants in the mouse brain

Glial cell line-derived neurotrophic factor(GDNF) plays a critical role in neuronal survival and function. GDNF has two major splice variants in the brain,α-pro-GDNF and β-pro-GDNF, and both isoforms have strong neuroprotective effects on dopamine neurons. However, the expression of the GDNF splice variants in dopaminergic neurons in the brain remains unclear. Therefore, in this study, we investigated the mRNA and protein expression of α-and β-pro-GDNF in the mouse brain by real-time quantitative polymerase chain reaction, using splice variant-specific primers, and western blot analysis. At the mRNA level,β-pro-GDNF expression was significantly greater than that of α-pro-GDNF in the mouse brain. In contrast, at the protein level,α-pro-GDNF expression was markedly greater than that of β-pro-GDNF. To clarify the mechanism underlying this inverse relationship in mRNA and protein expression levels of the GDNF splice variants, we analyzed the expression of sorting protein-related receptor with A-type repeats(SorLA) by real-time quantitative polymerase chain reaction. At the mRNA level, SorLA was positively associated with β-pro-GDNF expression, but not with α-pro-GDNF expression. This suggests that the differential expression of α-and β-pro-GDNF in the mouse brain is related to SorLA expression. As a sorting protein, SorLA could contribute to the inverse relationship among the mRNA and protein levels of the GDNF isoforms. This study was approved by the Animal Ethics Committee of Xuzhou Medical University, China on July 14, 2016.