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Woo Chul Chung, Chungkuk Jin, MooHyun Kim and Sewon Kim
This study proposes a mooring design strategy for a submerged floating tunnel (SFT) subject to extreme waves and earthquakes. Several critical design parameters, such as submerged depth and mooring station interval, are taken into account. As a target st...
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Woo Chul Chung, Chungkuk Jin and MooHyun Kim
This study suggests a novel riser structural health monitoring methodology based on a dual algorithm (DA). In this method, the displacement tracing algorithm first traces the node displacement and tension up to the last sensor position called the target ...
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Do-Soo Kwon, Chungkuk Jin, MooHyun Kim and Weoncheol Koo
This paper presents a machine learning method for detecting the mooring failures of SFT (submerged floating tunnel) based on DNN (deep neural network). The floater-mooring-coupled hydro-elastic time-domain numerical simulations are conducted under variou...
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Chungkuk Jin, HanSung Kim, Moo-Hyun Kim and Kiseon Kim
This paper investigates the sensor-based monitoring feasibility of a bottom-set gillnet through time-domain dynamic simulations for various current and wave conditions and failure scenarios. The dimension and design parameters of the bottom-set gillnet w...
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