• 한국해양공학회지
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• 제38권5호
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• pp.269-281
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• 2024

Due to climate change, waves have become increasingly stronger, making the analysis of beach changes before and after typhoons crucial for addressing beach erosion. This study utilized low-cost, high-efficiency video monitoring to analyze beach changes at 14 locations along Korea's east coast before and after typhoon impacts. Shorelines were extracted from 180 s average orthoimages using the Pixel Intensity Moving Average Extraction technique, and beach areas were calculated. The study focused on the recovery period following typhoon-induced erosion. During Typhoon Goni (2015), erosion reached up to 38% at Bongpo Beach, with a maximum affected area of 7,741 m² at Goraebul Beach. Post-typhoon recovery exceeded 89%, with most beaches returning to pre-typhoon conditions. The erosion period averaged 7 d, while recovery took approximately 27 d. Erosion was significantly influenced by natural forces such as waves, tides, and wind. The erosion period showed minimal correlation with wave energy, whereas the recovery period exhibited some correlation. Further long-term analysis, incorporating additional wave data and typhoon impact periods, is needed. Future research will aim to collect extensive typhoon data to systematically analyze erosion and recovery cycles in relation to external forces.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• 한국해양학회지:바다
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• 제25권3호
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• pp.55-66
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• 2020

준관성주기파(NIW)는 주로 바람에 의해 생성되며, 해양 연직혼합에 중요한 요소이다. 태풍의 빠른 풍속과 이동경로에 따른 풍향변화는 NIW 생성에 충분한 조건을 제공한다. 본 연구에서는 동해 실시간 해황예보모형 출력자료를 이용하여 태풍의 영향으로 인한 NIW의 생성과 분포 그리고 동해 중규모 소용돌이가 NIW의 심층 전파에 주는 영향에 대해 검토하였다. 이용한 출력자료 기간은 2013년부터 2017년까지 총 5개년이며, 이 기간 중 동해에 강한 NIW에너지를 만든 3개 태풍(할롱, 고니, 차바)에 초점을 맞추었다. 태풍에 의한 NIW 변동을 검토하기 위하여 강제력으로 작용하는 태풍의 바람에너지유입(${\bar{W}}_I$)과 함께 NIW 에너지의 지표인 혼합층 및 심층 수평운동에너지(${\bar{HKE}}_{MLD}$, ${\bar{HKE}}_{DEEP}$)를 계산하였다. ${\bar{HKE}}_{MLD}$는 ${\bar{W}}_I$와 밀접한 관련을 보였으며 태풍 경로의 오른편에서 강하게 나타났다. ${\bar{HKE}}_{DEEP}$는 주로 동해 남부에서 패치형태로 강하게 나타났으며, 음의 상대 소용돌이도를 가지는 난수성 소용돌이와의 상관성이 확인되었다. NIW에너지에 태풍이 주는 영향을 확인하기 위해, 태풍이 없는 여름철과 12월의 에너지와 상호 비교하였다. 그 결과, 태풍에 의한 ${\bar{HKE}}_{MLD}$는 태풍이 없는 여름에 비해 2.5~5.7배, NIW가 가장 큰 12월 평균대비 0.4~1.0배였고, 태풍에 의한 ${\bar{HKE}}_{DEEP}$는 태풍이 없는 여름대비 1.2~1.6배, 12월 평균대비 0.8~1.0배로 태풍에 의한 NIW가 혼합층과 심층의 해양 연직혼합 모두에 상당한 영향을 줄 수 있음을 확인하였다.