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Session: Control of heat transfer I
Session starts: Wednesday 05 November, 10:20
Presentation starts: 10:20
Room: Lecture room A

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Eunseop Yeom ()
Heewook Jung ()
Yongbum Cho ()
Hoyoon Kim ()

Abstract:
The performance of a household refrigerator is highly influenced by the internal temperature distribution and the efficiency of airflow. In particular, uniform temperature distribution within the refrigerator plays a critical role in maintaining energy efficiency and preserving food freshness, making its optimization essential to meet consumer demands. Computational Fluid Dynamics (CFD) has long been a vital tool for visualizing thermal and flow fields and optimizing refrigerator designs. Oh, M. J. conducted a three-dimensional steady-state numerical simulation to analyze the characteristics of cold airflow inside a refrigerator, accurately modeling internal flow and heat transfer involving fan and evaporator operation. (1) Similarly, Yoo, J. H. carried out a steady-state simulation aimed at improving airflow uniformity by redesigning the air duct structure. (2) In addition, Wang, L. performed CFD simulations under transient conditions to evaluate three-dimensional airflow and temperature variation inside a freezer cabinet, thereby optimizing temperature uniformity and cooling performance while analyzing internal flow patterns and thermal behavior. (3) Recently, advances in artificial neural networks have opened new opportunities for refrigerator design optimization. AI models can learn from large-scale simulation data to identify optimal design parameters that maximize temperature uniformity and cooling efficiency. This study integrates conventional CFD techniques with AI-based design optimization methods to analyze internal temperature characteristics and propose optimal design solutions for improved refrigerator performance.