Ulsan National Institute of Science and Technology · 工学
Professor Young-Bin Park's research lab specializes in advanced functional nanomaterials and their applications in thermal management and structural health monitoring. The lab focuses on developing high-performance nanofluids, such as CuO-graphene oxide nanocomposite nanofluids, for enhanced heat transfer in boiling applications, aiming to improve critical heat flux and thermal conductivity. Additionally, the lab pioneers non-destructive, self-sensing structural health monitoring systems using electrical resistance imaging and convolutional neural networks for carbon fiber-reinforced plastics, enabling real-time damage detection and localization. These interdisciplinary efforts bridge materials science, nanotechnology, and smart structural systems.
Figures are computed from collected data and may differ slightly.
Copper oxide nanoparticles nanofluids (CuO-NPs-NF) are promising candidates for pool boiling critical heat flux (CHF) applications due to their multifaceted advantages like easy tunability, eco-friendliness, cost-effectiveness, easy chemical modification and higher thermal conductivities. In addition, entrapping the CuO-NPs in/on to graphene oxide (GO) improves the CHF values compared to CuO-NPs alone. This paper reports a high performance hybrid NFs based on CuO and GO nanocomposites (CuO:GO-NC
In this study, advanced structural health monitoring (SHM) using a non-destructive self-sensing methodology was proposed for large-sized carbon fiber-reinforced plastic (CFRP). Cyclic point bending tests were performed on three types of CFRPs. The damage severity identification and localization were classified and investigated using four different convolutional neural network (CNN) architectures. Electrical resistance images were used to train each CNN architecture for damage analysis. An optimi
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