Investigating thermal stratification in the upper plenum of a Sodium Fast Reactor (SFR) is currently a technology gap in SFR safety analysis. Understanding thermal stratification will promote safe operation of the SFR before its commercial deployment. Stratified layers of liquid sodium with a large vertical temperature gradient could be established in the upper plenum of an SFR during a down-power or a loss-of-flow transient. These stratified layers are unstable and could result in uncertainties for the core safety of an SFR. In order to predict the occurrence of the thermal stratification efficiently, we developed a 1-D transport model to estimate the temperature profile of the ambient fluid in the upper plenum. This model demands much less computational efforts than CFD codes and provides calculations with higher fidelity than historical system-level codes. Two flow conditions were considered separately in the current study depending on if in-vessel components are presented in the upper plenum. For the condition where in-vessel components, specifically the upper internal structure, are presented, we assumed that the impinging sodium was evenly dispersed in the ambient fluid within the distance between the bottom of the in-vessel
Thermal hydraulic behavior in the upper plenum of pool-type sodium-cooled fast reactors (SFRs) is a major concern, as many design challenges are concentrated in this region. As SFR designs aim for licensing and commercialization, it is important to accurately analyze and predict the thermal-hydraulic behavior in this region during accident scenarios, specifically thermal stratification.
Thermal stratification models are currently a major source of uncertainty in most system codes for all types of power plants. Most system codes, including SAS4A/SASSYS-1, a system level code developed by Argonne National Laboratory (Argonne), use very coarse meshes that cannot capture the complexities of the stratification phenomena. While the commonly employed lumped-volume based models for thermal stratification are able to run in a matter of seconds, they result in approximate results and can only handle simple cases. Other 2-D and 3-D methods, such as computational fluid dynamics (CFD) models, can analyze simple configurations with higher fidelity, but come with a relatively large computational expense. Finding a modeling solution that is both accurate and computationally efficient has proven difficult.
This paper provides details of a review and gap analysis of the various modeling approaches proposed to date and explores a path forward for future thermal stratification modeling efforts, with a focus on developing new models for the SAS4A/SASSYS-1 system code.
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