Development of a drift-flux model based core thermal-hydraulics code for efficient high-fidelity multiphysics calculation Article Swipe
Jaejin Lee
,
Alberto Facchini
,
Han Gyu Joo
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.net.2019.04.002
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1016/j.net.2019.04.002
The methods and performance of a pin-level nuclear reactor core thermal-hydraulics (T/H) code ESCOT employing the drift-flux model are presented. This code aims at providing an accurate yet fast core thermal-hydraulics solution capability to high-fidelity multiphysics core analysis systems targeting massively parallel computing platforms. The four equation drift-flux model is adopted for two-phase calculations, and numerical solutions are obtained by applying the Finite Volume Method (FVM) and the Semi-Implicit Method for Pressure-Linked Equation (SIMPLE)-like algorithm in a staggered grid system. Constitutive models involving turbulent mixing, pressure drop, and vapor generation are employed to simulate key phenomena in subchannel-scale analyses. ESCOT is parallelized by a domain decomposition scheme that involves both radial and axial decomposition to enable highly parallelized execution. The ESCOT solutions are validated through the applications to various experiments which include CNEN 4 × 4, Weiss et al. two assemblies, PNNL 2 × 6, RPI 2 × 2 air-water, and PSBT covering single/two-phase and unheated/heated conditions. The parameters of interest for validation include various flow characteristics such as turbulent mixing, spacer grid pressure drop, cross-flow, reverse flow, buoyancy effect, void drift, and bubble generation. For all the validation tests, ESCOT shows good agreements with measured data in the extent comparable to those of other subchannel-scale codes: COBRA-TF, MATRA and/or CUPID. The execution performance is examined with a mini-sized whole core consisting of 89 fuel assemblies and for an OPR1000 core. It turns out that it is about 1.5 times faster than a subchannel code based on the two-fluid three field model and the axial domain decomposition scheme works as well as the radial one yielding a steady-state solution for the OPR1000 core within 30 s with 104 processors. Keywords: Drift-flux model, Reactor core thermal-hydraulics, Subchannel analysis, Massively parallel execution, SIMPLEC
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.net.2019.04.002
- OA Status
- diamond
- Cited By
- 10
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2939441303
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2939441303Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1016/j.net.2019.04.002Digital Object Identifier
- Title
-
Development of a drift-flux model based core thermal-hydraulics code for efficient high-fidelity multiphysics calculationWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-04-09Full publication date if available
- Authors
-
Jaejin Lee, Alberto Facchini, Han Gyu JooList of authors in order
- Landing page
-
https://doi.org/10.1016/j.net.2019.04.002Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1016/j.net.2019.04.002Direct OA link when available
- Concepts
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Multiphysics, Thermal hydraulics, Domain decomposition methods, Mechanics, Buoyancy, Turbulence, Light-water reactor, Grid, Computer science, Pressure drop, Nuclear engineering, Simulation, Computational science, Thermodynamics, Engineering, Heat transfer, Finite element method, Physics, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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10Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 2, 2023: 2, 2022: 2, 2021: 2Per-year citation counts (last 5 years)
- References (count)
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30Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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