Park Hyungoo

Dr. Park Hyungoo

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 September 2025 in Ocean Engineering
Verified
Journal Article
Closed access
PHPark Hyungoo
Park Hyungoo
YPYoung-Soo Park
Young-Soo Park
SPSangwon Park
Sangwon Park
Wonsik KangWonsik Kang
Wonsik Kang
Daewon KimDaewon Kim
Daewon Kim
DCDae-Yul Chong
Dae-Yul Chong

1 September 2024 in Journal of Navigation
Verified
Journal Article
Closed access
PDF file
PHPark Hyungoo
Park Hyungoo
Youngsoo ParkYoungsoo Park
Youngsoo Park
SPSangwon Park
Sangwon Park
DCDae-Yul Chong
Dae-Yul Chong
WKWonsik Kang
Wonsik Kang
DKDaewon Kim
Daewon Kim
Among maritime accidents, fishing vessel collisions are particularly prone to both high frequency and severity. This study aims to identify the correlation between effective collision speed (Delta-V) and the severity of hull damage in fishing vessel collisions. Using data from collisions in South Korea, the study examines the influence of collision-related factors including Delta-V, collision location, collision subject, collision angle and the hull material of the impacted vessel on the extent of vessel damage. Statistical analyses and binary logistic regression were employed to assess trends and relationships between these variables. The findings confirm direct associations between hull damage severity and factors such as tonnage, collision location, the striking vessel and the extent of hull damage.


21 October 2026 in Ocean Engineering
Verified
Journal Article
Closed access
PHPark Hyungoo
Park Hyungoo
YPYoungsoo Park
Youngsoo Park
SPSangwon Park
Sangwon Park
DKDaewon Kim
Daewon Kim
HSHiroaki SETA
Hiroaki SETA
Wonsik KangWonsik Kang
Wonsik Kang

Verified
Journal Article
Open access
PDF file
PHPark Hyungoo
Park Hyungoo
SPSangwon Park
Sangwon Park
Youngsoo ParkYoungsoo Park
Youngsoo Park
SOSewoong Oh
Sewoong Oh
Daewon KimDaewon Kim
Daewon Kim
Vessel traffic services (VTSs) in ports require interpretable information on vessel approaches and travel times where shared fairways branch toward multiple destinations. This study presents a gate-based Bayesian method for VTS decision support in Busan North Port. Automatic Identification System (AIS) and Port Management Information System (PORT-MIS) records from September 2024 to August 2025 were linked. Density-based clustering of turning locations and examination of traffic functions informed the placement of 22 virtual gates. A Bayesian network with 20 binary gate-passage variables was constructed from 7194 inbound trajectories. The probability of shared-fairway passage given a passenger-terminal approach was approximately 99.9%, whereas the reverse conditional probability was 20.55%. These results distinguish shared passage locations associated with a known approach from approaches associated with an observed passage. Three illustrative routes had annual mean travel times of 6.22, 6.52, and 13.38 min. Speed-conditioned travel-time probabilities were estimated from the data. On the main-fairway route, arrival in less than 6 min had a probability of 91.01% at departure speeds of 10–<12 kts. The method provides location-specific passage probabilities and route-specific travel-time information for interpreting observed traffic. Validation of predictive performance and benefits for controller decision-making remains necessary.