Detail publikace

Assessment of URANS-Type Turbulent Flow Modeling of a Single Port Submerged Entry Nozzle (SEN) for Thin Slab Continuous Casting (TSC) Process

VAKHRUSHEV, A. KARIMI-SIBAKI, E. WU, M. LUDWIG, A. NITZL, G. TANG, Y. HACKL, G. WATZINGER, J. BOHÁČEK, J. KHARICHA, A.

Anglický název

Assessment of URANS-Type Turbulent Flow Modeling of a Single Port Submerged Entry Nozzle (SEN) for Thin Slab Continuous Casting (TSC) Process

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

en

Originální abstrakt

The numerical methods based on the unsteady Reynolds-averaged Navier–Stokes (URANS) equations are robust tools to model the turbulent flow for the industrial processes. They allow an acceptable grid resolution along with reasonable calculation time. Herein, the URANS approach is validated against a water model experiment for the special single port submerged entry nozzle (SEN) design used in the thin slab casting (TSC) process. A 1-to-2 under-scaled water model was constructed, including the SEN, mold, and strand Plexiglas segments. Paddle-type sensors were instrumented to measure the submeniscus velocity supported by videorecording of the dye injections to provide both qualitative and quantitative verification of the SEN flow simulations. Two advanced URANS-type models (realizable k–ε and shear stress transport k–ω) were applied to calculate velocity pattern on meshes with various resolutions. An oscillating single jet flow was detected in the experiment, which the URANS simulations initially struggled to reflect. The dimensionless analysis of the mesh properties and corresponding adjustment of the boundary layers inside the SEN allowed to resolve the flow pattern. The performed fast Fourier transform (FFT) verified a good numerical prediction of the flow frequency spectrum. The corresponding simulation strategy is proposed for the industrial CC process using the URANS approach.

Anglický abstrakt

The numerical methods based on the unsteady Reynolds-averaged Navier–Stokes (URANS) equations are robust tools to model the turbulent flow for the industrial processes. They allow an acceptable grid resolution along with reasonable calculation time. Herein, the URANS approach is validated against a water model experiment for the special single port submerged entry nozzle (SEN) design used in the thin slab casting (TSC) process. A 1-to-2 under-scaled water model was constructed, including the SEN, mold, and strand Plexiglas segments. Paddle-type sensors were instrumented to measure the submeniscus velocity supported by videorecording of the dye injections to provide both qualitative and quantitative verification of the SEN flow simulations. Two advanced URANS-type models (realizable k–ε and shear stress transport k–ω) were applied to calculate velocity pattern on meshes with various resolutions. An oscillating single jet flow was detected in the experiment, which the URANS simulations initially struggled to reflect. The dimensionless analysis of the mesh properties and corresponding adjustment of the boundary layers inside the SEN allowed to resolve the flow pattern. The performed fast Fourier transform (FFT) verified a good numerical prediction of the flow frequency spectrum. The corresponding simulation strategy is proposed for the industrial CC process using the URANS approach.

Klíčová slova anglicky

Thin slab casting; submerged entry nozzle; OpenFOAM; water model; URANS; submeniscus velocity

Vydáno

16.02.2024

Nakladatel

Springer Nature

ISSN

1073-5615

Ročník

55

Číslo

2

Strany od–do

891–904

Počet stran

14

BIBTEX


@article{BUT188155,
  author="Petr {Dyntera} and Alexander {Vakhrushev} and Ebrahim {Karimi-Sibaki} and Menghuai {Wu} and Andreas {Ludwig} and Gerald {Nitzl} and Yong {Tang} and Gernot {Hackl} and Josef {Watzinger} and Jan {Boháček} and Abdellah {Kharicha},
  title="Assessment of URANS-Type Turbulent Flow Modeling of a Single Port Submerged Entry Nozzle (SEN) for Thin Slab Continuous Casting (TSC) Process",
  year="2024",
  volume="55",
  number="2",
  month="February",
  pages="891--904",
  publisher="Springer Nature",
  issn="1073-5615"
}