NEAMS IRP challenge problem 1: Flexible modeling for heat transfer for low-to-high Prandtl number fluids for applications in advanced reactors

Igor A. Bolotnov, Arsen S. Iskhakov, Tri Nguyen, Cheng Kai Tai, Ralph Wiser, Emilio Baglietto, Nam Dinh, Dillon Shaver, Elia Merzari

Research output: Contribution to journalArticlepeer-review

Abstract

The adoption of liquid metals and molten salts as coolant fluids in advanced reactor designs has challenged traditional turbulence and heat transfer models because of different convective heat transfer characteristics from water. The challenge is exacerbated by the yet-to-be-understood mixed convection regime, which is crucial to passive heat removal. The NEAMS IRP Challenge Problem 1 (CP1) project aims to facilitate scale-flexible heat transfer models that can serve for broader applications in reactor thermal–hydraulic analysis. CP1 research activities include direct numerical simulation (DNS) and the development of advanced turbulence modeling techniques. The DNS efforts study the low- and high-Prandtl mixed convection in the identified canonical flow scenario, from which the fundamental understanding on the effect of buoyancy on turbulence and heat transfer is investigated. The CP1 modeling endeavors aim at advancement of the present engineering models and the employment of the data driven (DD) methods for the turbulence modeling. In the engineering model concentration, the performance of the current CFD models is assessed in the non-unitary Prandtl flows to gain physical understanding of their shortcomings. A framework for model error prediction and error propagation estimation is also established. A DD RANS framework is developed for the frozen prediction of Reynolds stress and turbulent heat flux based on the polynomial tensor representation of the respective quantities. The DD framework showed satisfactory performance over the k-τ model in the forced and mixed convection cases.

Original languageEnglish (US)
Article number113467
JournalNuclear Engineering and Design
Volume428
DOIs
StatePublished - Nov 2024

All Science Journal Classification (ASJC) codes

  • Nuclear and High Energy Physics
  • General Materials Science
  • Nuclear Energy and Engineering
  • Safety, Risk, Reliability and Quality
  • Waste Management and Disposal
  • Mechanical Engineering

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