Development of an efficient immersed-boundary method with subgrid-scale models for conjugate heat transfer analysis using large eddy simulation

Lee, Sangjoon; Hwang, Wontae

doi:10.1016/j.ijheatmasstransfer.2019.01.019

Cited by 7 publications

(5 citation statements)

References 40 publications

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“…A convection correction factor (τ) was introduced to maintain the second-order accuracy at the interface, and effective thermal conductivity was introduced to satisfy continuity of the heat flux at the interface. An explanation of how to determine each factor according to the interface configuration in the cell can be found in [25,30].…”

Section: Methodsmentioning

confidence: 99%

Fully Coupled Large Eddy Simulation of Conjugate Heat Transfer in a Ribbed Channel with a 0.1 Blockage Ratio

2021

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Large eddy simulations are performed to analyze the conjugate heat transfer of turbulent flow in a ribbed channel with a heat-conducting solid wall. An immersed boundary method (IBM) is used to determine the effect of heat transfer in the solid region on that in the fluid region in a unitary computational domain. To satisfy the continuity of the heat flux at the solid–fluid interface, effective conductivity is introduced. By applying the IBM, it is possible to fully couple the convection on the fluid side and the conduction inside the solid and use a dynamic subgrid scale model in a Cartesian grid. The blockage ratio (e/H) is set at 0.1, which is typical for gas turbine blades. Through conjugate heat transfer analysis, it is confirmed that the heat transfer peak in front of the rib occurs because of the impinging of the reattached flow and not the influence of the thermal boundary condition. When the rib turbulator acts as a fin, its efficiency and effectiveness are predicted to be 98.9% and 8.32, respectively. When considering conjugate heat transfer, the total heat transfer rate is reduced by 3% compared with that of the isothermal wall. The typical Biot number at the internal cooling passage of a gas turbine is <0.1, and the use of the rib height as the characteristic length better represents the heat transfer of the rib.

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Section: Methodsmentioning

confidence: 99%

Fully Coupled Large Eddy Simulation of Conjugate Heat Transfer in a Ribbed Channel with a 0.1 Blockage Ratio

2021

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“…For the performance evaluation within the design space D × S, we use a full, non-linear, incompressible Navier-Stokes equation solver with subgrid-scale modeling proposed by Lee & Hwang [36]. Although the solver includes a heat transfer analysis module, which we may consider for later optimization, in this present study, we only utilize and focus on its momentum solution (i.e., drag force).…”

Section: Flow Simulationmentioning

confidence: 99%

“…In this work, we use 𝑐 = 0.07, following the previous results from Vreman [45] and our a priori tests of turbulent channel flows at 𝑅𝑒 𝜏 = 180. Although several dynamic models that internally determine 𝑐 in terms of time [36,44] can be considered to improve the model's autonomy, we decided to maintain the constant model coefficient to avoid its recalculation at every time step, as it significantly increases the total computation time and aggravates the time-efficiency of the optimization.…”

Section: Governing Equationsmentioning

confidence: 99%

“…As a result, the cross-sectional area remains consistently 2𝑋 3 . The grid dependency of the current method for turbulent channel flows was studied by Lee & Hwang [36] at a similar Reynolds number of 𝑅𝑒 𝜏 = 150. Our a priori tests at 𝑅𝑒 𝜏 = 180 without riblets also reveal a convergence trend (with respect to the grid size) of the computed mean streamwise velocity gradient at each channel wall ( 𝜕𝑢 1 /𝜕𝑥 2 )| 𝑤 to its theoretical value, equal to 𝑅𝑒 𝜏 , under the current non-dimensionalization based on 𝜌, 𝑢 𝜏 , and 𝜍.…”

Section: Computational Domain Setup Andmentioning

confidence: 99%

“…It is noted that any length value given in wall units in a dimensionless manner, e.g., 𝜉 + , should be expressed as 𝜉 + /𝑅𝑒 𝜏 in the computational domain, as 𝜍 serves as the reference scale. The spatial differentiation and time integration are conducted using the finite volume method of Kim et al [40], which is based on a second-order central difference method for space and a semi-implicit fractional-step method for time [36]. The time step interval is controlled by the Courant-Friedrichs-Lewy (CFL) condition, where the maximum CFL number is empirically chosen to be three.…”

Section: Computational Domain Setup Andmentioning

confidence: 99%

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Bayesian-Optimized Riblet Surface Design for Turbulent Drag Reduction via Design-by-Morphing With Large Eddy Simulation

Lee,

Moazam Sheikh,

Lim

et al. 2024

Journal of Mechanical Design

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A computational approach is presented for optimizing new riblet surface designs in turbulent channel flow for drag reduction, utilizing Design-by-Morphing (DbM), Large Eddy Simulation (LES), and Bayesian Optimization (BO). The design space is generated using DbM to include a variety of novel riblet surface designs, which are then evaluated using LES to determine their drag-reducing capabilities. The riblet surface geometry and configuration are optimized for maximum drag reduction using the mixed-variable Bayesian optimization (MixMOBO) algorithm. A total of 125 optimization epochs are carried out, resulting in the identification of 3 optimal riblet surface designs that are comparable to or better than the reference drag reduction rate of 8 %. The Bayesian-optimized designs commonly suggest riblet sizes of around 15 wall units, relatively large spacing compared to conventional designs, and spiky tips with notches for the riblets. Our overall optimization process is conducted within a reasonable physical time frame with up to 12-core parallel computing and can be practical for fluid engineering optimization problems that require high-fidelity of computational design before materialization.

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An Immersed Boundary Method for Conjugate Heat Transfer Involving Melting/Solidification

Ahn

Song

Lee

2023

Int. J. Aeronaut. Space Sci.

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Development of an efficient immersed-boundary method with subgrid-scale models for conjugate heat transfer analysis using large eddy simulation

Cited by 7 publications

References 40 publications

Fully Coupled Large Eddy Simulation of Conjugate Heat Transfer in a Ribbed Channel with a 0.1 Blockage Ratio

Fully Coupled Large Eddy Simulation of Conjugate Heat Transfer in a Ribbed Channel with a 0.1 Blockage Ratio

Bayesian-Optimized Riblet Surface Design for Turbulent Drag Reduction via Design-by-Morphing With Large Eddy Simulation

An Immersed Boundary Method for Conjugate Heat Transfer Involving Melting/Solidification

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