Aejung Yoon
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Aejung Yoon has a total of 17 co-authors. Here are the top co-authors by number of shared publications:
- Mani Sankar
College of Computing and Information Sciences, University of Technology and Applied Sciences, Ibri 516, Oman
3 shared publications - H. A. Kumara Swamy
Department of Mathematics, School of Engineering, Presidency University, Bengaluru, India
2 shared publications N. Keerthi Reddy
Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
2 shared publications- Seong-Bhin Kim
Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
2 shared publications - Daud Mustafa Minhas
Industrial Security Lab, ZeMA—Center for Mechatronics and Automation Technology, D-66121 Saarbrücken, Germany
1 shared publication - Dohyun Kim
Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
1 shared publication
Latest Publications
- 1 June 2026
- Published by AIP Publishing in Physics of Fluids
- Vol. 38 (6)
Numerical study on choking onset of Hyperloop systems: Effect of blockage ratio
This study performs a numerical investigation into the choking onset of Hyperloop systems. As a pod travels through a near-vacuum tube, the bypass flow between the pod and tube walls accelerates, eventually reaching a choked state at the minimum bypass area (throat). Using a two-dimensional axisymmetric model, the choking onset—defined by the first occurrence of sonic flow at the throat—is analyzed across a blockage ratio (BR) range of 0.16–0.64. The numerical results indicate that the idealized isentropic limit underestimates the critical pod Mach number at the choking onset, with the discrepancy intensifying as BR increases. To account for this discrepancy, two effects are systematically analyzed: the upstream state change induced by the leading shock wave (LSW) ahead of the pod and the reduction in bypass area caused by boundary layer displacement on the pod and tube walls. At sufficiently low BR, the modified correlation incorporating only the LSW-induced upstream state change aligns reasonably well with the numerical results. However, the discrepancy between this LSW-only correlation and the numerical results intensifies as BR increases. Specifically, at the highest BR, the maximum deviation of −38% for the isentropic limit is reduced to +14.4% by accounting for the LSW effect and is ultimately reduced to +3.8% when the reduction in bypass area is additionally incorporated. These findings demonstrate that both effects must be considered to accurately predict the choking onset across a broad range of BR in Hyperloop systems.
- 1 June 2026
- Published by AIP Publishing in Physics of Fluids
- Vol. 38 (6)
Numerical study on choking onset of Hyperloop systems: Effect of blockage ratio
This study performs a numerical investigation into the choking onset of Hyperloop systems. As a pod travels through a near-vacuum tube, the bypass flow between the pod and tube walls accelerates, eventually reaching a choked state at the minimum bypass area (throat). Using a two-dimensional axisymmetric model, the choking onset—defined by the first occurrence of sonic flow at the throat—is analyzed across a blockage ratio (BR) range of 0.16–0.64. The numerical results indicate that the idealized isentropic limit underestimates the critical pod Mach number at the choking onset, with the discrepancy intensifying as BR increases. To account for this discrepancy, two effects are systematically analyzed: the upstream state change induced by the leading shock wave (LSW) ahead of the pod and the reduction in bypass area caused by boundary layer displacement on the pod and tube walls. At sufficiently low BR, the modified correlation incorporating only the LSW-induced upstream state change aligns reasonably well with the numerical results. However, the discrepancy between this LSW-only correlation and the numerical results intensifies as BR increases. Specifically, at the highest BR, the maximum deviation of −38% for the isentropic limit is reduced to +14.4% by accounting for the LSW effect and is ultimately reduced to +3.8% when the reduction in bypass area is additionally incorporated. These findings demonstrate that both effects must be considered to accurately predict the choking onset across a broad range of BR in Hyperloop systems.
- Open Access
Comparative Assessment of Supervised Machine Learning Models for Predicting Water Uptake in Sorption-Based Thermal Energy Storage
In this study, supervised machine learning (ML) regression models are employed to predict water uptake during the sorption process in a sorption reactor for thermal energy storage applications. Two main methods are used to study sorption storage systems: experimental studies and numerical simulations. Experimental studies involve physical testing and measurements but are often costly and time-consuming. Numerical simulations are more flexible and cost-effective, though they can require significant computational resources for large or complex systems. To address these challenges, researchers are increasingly employing various machine learning techniques, which offer strong potential for data analysis and predictive modeling. In this study, CFD-based sorption simulations are integrated with machine learning models to predict the spatiotemporal evolution of water uptake. Several ML techniques including support vector regression (SVR), Random Forest, XGBoost, CatBoost (gradient boosting decision trees), and multilayer perceptron neural networks (MLPs) are evaluated and compared. A fixed-bed reactor equipped with fins and tubes is considered within a closed adsorption thermal storage system. Numerical simulations are conducted for three different fin lengths (10 mm, 25 mm, and 35 mm) to generate a comprehensive dataset for training the ML models and capturing the complex temporal evolution of water uptake, thereby enabling predictions for unseen fin geometries. The results indicate that neural network-based models achieve superior predictive performance compared to the other methods. For water uptake training, the mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination are approximately 2.83, 4.37, and 0.91, respectively. The predicted water uptake shows close agreement with the numerical simulation results. For the prediction cases, the MAE, MSE, and values are approximately 1.13, 1.2, and 0.8, respectively. Overall, the study demonstrates that machine learning models can accurately predict water uptake beyond the training dataset, indicating strong generalization capability and significant potential for improving thermal management system design. Additionally, the proposed approach reduces simulation time and computational cost while providing an efficient and reliable framework for modeling complex sorption processes in thermal energy storage systems.Open AccessComparative Assessment of Supervised Machine Learning Models for Predicting Water Uptake in Sorption-Based Thermal Energy Storage
In this study, supervised machine learning (ML) regression models are employed to predict water uptake during the sorption process in a sorption reactor for thermal energy storage applications. Two main methods are used to study sorption storage systems: experimental studies and numerical simulations. Experimental studies involve physical testing and measurements but are often costly and time-consuming. Numerical simulations are more flexible and cost-effective, though they can require significant computational resources for large or complex systems. To address these challenges, researchers are increasingly employing various machine learning techniques, which offer strong potential for data analysis and predictive modeling. In this study, CFD-based sorption simulations are integrated with machine learning models to predict the spatiotemporal evolution of water uptake. Several ML techniques including support vector regression (SVR), Random Forest, XGBoost, CatBoost (gradient boosting decision trees), and multilayer perceptron neural networks (MLPs) are evaluated and compared. A fixed-bed reactor equipped with fins and tubes is considered within a closed adsorption thermal storage system. Numerical simulations are conducted for three different fin lengths (10 mm, 25 mm, and 35 mm) to generate a comprehensive dataset for training the ML models and capturing the complex temporal evolution of water uptake, thereby enabling predictions for unseen fin geometries. The results indicate that neural network-based models achieve superior predictive performance compared to the other methods. For water uptake training, the mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination are approximately 2.83, 4.37, and 0.91, respectively. The predicted water uptake shows close agreement with the numerical simulation results. For the prediction cases, the MAE, MSE, and values are approximately 1.13, 1.2, and 0.8, respectively. Overall, the study demonstrates that machine learning models can accurately predict water uptake beyond the training dataset, indicating strong generalization capability and significant potential for improving thermal management system design. Additionally, the proposed approach reduces simulation time and computational cost while providing an efficient and reliable framework for modeling complex sorption processes in thermal energy storage systems. - 16 September 2024
- Published by Elsevier in International Journal of Thermal Sciences
- Vol. 208, 109418
Study on the effect of condenser configuration of pulsating heat pipes for space applications
- 16 September 2024
- Published by Elsevier in International Journal of Thermal Sciences
- Vol. 208, 109418
Study on the effect of condenser configuration of pulsating heat pipes for space applications
- 1 March 2024
- Published by AIP Publishing in Physics of Fluids
- Vol. 36 (3)
Computational study of magneto-convective flow of aqueous-Fe3O4 nanoliquid in a tilted cylindrical chamber partially layered by porous medium: Entropy generation analysis
In various industrial applications, the main objective is to enhance thermal efficiency by minimizing the generation of entropy. Specifically, achieving optimal thermal efficiency in a tilted cylindrical chamber poses significant challenges due to the combined effects of tangential and normal gravity components. Our study focuses on the flow dynamics, thermal transport, and entropy generation of Fe3O4/H2O nanoliquid within a cylindrical annular enclosure by incorporating the synergistic effects of magnetic force, geometric inclination angle, and thickness of the porous region. The Brinkman–Forchheimer-extended Darcy model for ferrofluid motion and the one-equation model for heat transfer are applied in the porous region, while the conventional Navier–Stokes and energy equations are used in the fluid-only region. A series of computations is performed for various key parameters, such as Hartmann number (0≤Ha≤60), Darcy number (10−5≤Da≤10−1), porous layer thickness (0.1≤ε≤0.9), and angle of inclination (−60°≤γ≤60°). Our results reveal that the heat transport rate is enhanced by 48.6% with an increase in the Darcy number from 10−5 to 10−1. Moreover, the flow circulation and heat transport can be optimized by tilting the enclosure anticlockwise. It has been found that 91.8% of flow strength can be enhanced by rotating the enclosure from −60° to 60°. Finally, this study suggests that the inclination angle of 30° and a porous layer thickness of 0.3 emerge as the ideal configuration to obtain optimal performance, particularly for lower Hartmann and higher Darcy numbers. Our findings will provide insight into optimizing thermal processes in nanoliquid-filled enclosures subjected to magnetic force.
- 1 March 2024
- Published by AIP Publishing in Physics of Fluids
- Vol. 36 (3)
Computational study of magneto-convective flow of aqueous-Fe3O4 nanoliquid in a tilted cylindrical chamber partially layered by porous medium: Entropy generation analysis
In various industrial applications, the main objective is to enhance thermal efficiency by minimizing the generation of entropy. Specifically, achieving optimal thermal efficiency in a tilted cylindrical chamber poses significant challenges due to the combined effects of tangential and normal gravity components. Our study focuses on the flow dynamics, thermal transport, and entropy generation of Fe3O4/H2O nanoliquid within a cylindrical annular enclosure by incorporating the synergistic effects of magnetic force, geometric inclination angle, and thickness of the porous region. The Brinkman–Forchheimer-extended Darcy model for ferrofluid motion and the one-equation model for heat transfer are applied in the porous region, while the conventional Navier–Stokes and energy equations are used in the fluid-only region. A series of computations is performed for various key parameters, such as Hartmann number (0≤Ha≤60), Darcy number (10−5≤Da≤10−1), porous layer thickness (0.1≤ε≤0.9), and angle of inclination (−60°≤γ≤60°). Our results reveal that the heat transport rate is enhanced by 48.6% with an increase in the Darcy number from 10−5 to 10−1. Moreover, the flow circulation and heat transport can be optimized by tilting the enclosure anticlockwise. It has been found that 91.8% of flow strength can be enhanced by rotating the enclosure from −60° to 60°. Finally, this study suggests that the inclination angle of 30° and a porous layer thickness of 0.3 emerge as the ideal configuration to obtain optimal performance, particularly for lower Hartmann and higher Darcy numbers. Our findings will provide insight into optimizing thermal processes in nanoliquid-filled enclosures subjected to magnetic force.
- 18 December 2023
- Published by Springer Nature in Journal of Thermal Analysis and Calorimetry
- Vol. 149 (13) , 7025-7039
Impact of internal heat generation/absorption on MHD conjugate flow of aqueous-MWCNT nanofluid in a porous annulus
- 18 December 2023
- Published by Springer Nature in Journal of Thermal Analysis and Calorimetry
- Vol. 149 (13) , 7025-7039
Impact of internal heat generation/absorption on MHD conjugate flow of aqueous-MWCNT nanofluid in a porous annulus
- 30 October 2023
- Published by Emerald Publishing in International Journal of Numerical Methods for Heat & Fluid Flow
- Vol. 34 (1) , 203-230
Numerical investigation of nanofluid buoyant flow behavior and heat transfer characteristics in annular-shaped enclosure with internal baffle
Purpose: Natural convection in finite enclosures is a common phenomenon in various thermal applications. To provide the thermal design guidelines, this study aims to numerically explore the potential of using internal baffles and nanofluids to either enhance or suppress heat transport in a vertical annulus. Furthermore, the annular-shaped enclosure is filled with aqueous-silver nanofluid and the effects of five distinct nanoparticle shapes are examined. In addition, the influence of baffle design parameters, including baffle position, thickness and length, is thoroughly analyzed.Design/methodology/approach: The finite difference method is used in conjunction with the alternating direction implicit and successive line over relaxation techniques to solve nonlinear and coupled partial differential equations. The single phase model is used for nanofluid which is considered as a homogeneous fluid with improved thermal properties. The independence tests are carried out for assessing the sufficiency of grid size and time step for obtaining results accurately.Findings: The baffle dimension parameters and nanoparticle shape exhibit significant impact on the convective flow and heat transfer characteristics, leading to the following results: sphere- and blade-shaped nanoparticles demonstrate around 30% enhancement in the heat transport capability compared with platelet-shaped nanoparticles, which exhibit the least. When considering the baffle design parameter, either a decrease in the baffle length and thickness or an increase in baffle height leads to an improvement in heat transport rate. Consequently, a threefold increase in baffle height yields a 40% improvement in thermal performance.Originality/value: Understanding the impact of nanoparticle shapes and baffle design parameters on flow and thermal behavior will enable engineers to provide valuable insight on thermal management and overall system efficiency. Therefore, the current work focuses on exploring buoyant nanofluid flow and thermal mechanism in a baffled annular-shaped enclosure. Specifically, an internal baffle that exhibits conductive heat transfer through it is considered, and the impact of baffle dimensions (thickness, length and position) on the fluid flow behavior and thermal characteristics is investigated. In addition, the current study also addresses the influence of five distinct nanoparticle shapes (e.g. spherical, cylindrical, platelet, blade and brick) on the flow and thermal behavior in the baffled annular geometry. In addition to deepening the understanding of nanofluid behavior in a baffled vertical annulus, the current study contributes to the ongoing advancements in thermal applications by providing certain guidelines to design application-specific enclosures.
- 30 October 2023
- Published by Emerald Publishing in International Journal of Numerical Methods for Heat & Fluid Flow
- Vol. 34 (1) , 203-230
Numerical investigation of nanofluid buoyant flow behavior and heat transfer characteristics in annular-shaped enclosure with internal baffle
Purpose: Natural convection in finite enclosures is a common phenomenon in various thermal applications. To provide the thermal design guidelines, this study aims to numerically explore the potential of using internal baffles and nanofluids to either enhance or suppress heat transport in a vertical annulus. Furthermore, the annular-shaped enclosure is filled with aqueous-silver nanofluid and the effects of five distinct nanoparticle shapes are examined. In addition, the influence of baffle design parameters, including baffle position, thickness and length, is thoroughly analyzed.Design/methodology/approach: The finite difference method is used in conjunction with the alternating direction implicit and successive line over relaxation techniques to solve nonlinear and coupled partial differential equations. The single phase model is used for nanofluid which is considered as a homogeneous fluid with improved thermal properties. The independence tests are carried out for assessing the sufficiency of grid size and time step for obtaining results accurately.Findings: The baffle dimension parameters and nanoparticle shape exhibit significant impact on the convective flow and heat transfer characteristics, leading to the following results: sphere- and blade-shaped nanoparticles demonstrate around 30% enhancement in the heat transport capability compared with platelet-shaped nanoparticles, which exhibit the least. When considering the baffle design parameter, either a decrease in the baffle length and thickness or an increase in baffle height leads to an improvement in heat transport rate. Consequently, a threefold increase in baffle height yields a 40% improvement in thermal performance.Originality/value: Understanding the impact of nanoparticle shapes and baffle design parameters on flow and thermal behavior will enable engineers to provide valuable insight on thermal management and overall system efficiency. Therefore, the current work focuses on exploring buoyant nanofluid flow and thermal mechanism in a baffled annular-shaped enclosure. Specifically, an internal baffle that exhibits conductive heat transfer through it is considered, and the impact of baffle dimensions (thickness, length and position) on the fluid flow behavior and thermal characteristics is investigated. In addition, the current study also addresses the influence of five distinct nanoparticle shapes (e.g. spherical, cylindrical, platelet, blade and brick) on the flow and thermal behavior in the baffled annular geometry. In addition to deepening the understanding of nanofluid behavior in a baffled vertical annulus, the current study contributes to the ongoing advancements in thermal applications by providing certain guidelines to design application-specific enclosures.