TY - JOUR
T1 - Hurricane wind disaster assessment methods on coastal structures based on area and radial distribution integration
AU - Ren, Hehe
AU - Ke, Shitang
AU - Dudhia, Jimy
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/12/15
Y1 - 2022/12/15
N2 - Early studies have shown that hurricane disaster assessment indicators that only consider the intensity-related single factor cannot well represent the actual degree of damage caused by hurricanes to coastal structures. In the current study, for hurricane wind damage, in addition to the three wind disaster index formulas (corresponding to the wind resistance characteristics of infrastructures in developed, developing, and underdeveloped regions, respectively) that are related to hurricane intensity, the spatial scale characteristics of hurricanes are also considered. Thus, two kinds of hurricane wind disaster assessment methods by combing the wind disaster index and spatial scale of hurricanes are carried out, area and radial integration, respectively. Compared with the traditional single-factor evaluation index, the method based on area integral can more accurately characterize the degree of hurricane wind disaster. However, the peripheral small wind speed of the hurricane has a greater impact on wind disaster assessment; for medium-strength and intense hurricanes, the highest proportion is up to 61.5–67.7%; and that of weak hurricanes is up to 85.7–94.1%. To solve the challenging problems of hurricanes with small wind speed but the large size and large wind speed but small size, the area integral method with the concept of cut-in wind speed is introduced. The impact of small wind speed on wind disaster assessment is significantly reduced; the highest proportion of medium-strength and intense hurricanes is 14.5–22.5%, and that of weak hurricanes is 27.5–33.3%. Because the three-dimensional wind field is not easy to capture, the structure along the coastline is the most severely damaged, and the linear radial integral is less sensitive to small wind speeds than the quadratic area integral, a hurricane wind disaster assessment method based on radial integral is proposed. The results show that the method has good spatial region insensitivity. Both methods show that the numerical results can accurately represent the hurricane wind disaster when the horizontal grid size is 185 m or 555 m. However, the wind disaster assessment trends of the two methods are not linear because of the asymmetry of the hurricane structure. The two hurricane wind disaster assessment methods proposed in this study can better reflect the degree of disaster. For the comprehensive hurricane wind disaster assessment for large-scale wind farms in the deep sea, the area-based method can be used; for the infrastructure structures along the coastline, the radial-based method is more suitable. Since the measured meteorological data contain different characteristic radius and the corresponding wind speed of hurricanes, the method based on radial integral is more practical.
AB - Early studies have shown that hurricane disaster assessment indicators that only consider the intensity-related single factor cannot well represent the actual degree of damage caused by hurricanes to coastal structures. In the current study, for hurricane wind damage, in addition to the three wind disaster index formulas (corresponding to the wind resistance characteristics of infrastructures in developed, developing, and underdeveloped regions, respectively) that are related to hurricane intensity, the spatial scale characteristics of hurricanes are also considered. Thus, two kinds of hurricane wind disaster assessment methods by combing the wind disaster index and spatial scale of hurricanes are carried out, area and radial integration, respectively. Compared with the traditional single-factor evaluation index, the method based on area integral can more accurately characterize the degree of hurricane wind disaster. However, the peripheral small wind speed of the hurricane has a greater impact on wind disaster assessment; for medium-strength and intense hurricanes, the highest proportion is up to 61.5–67.7%; and that of weak hurricanes is up to 85.7–94.1%. To solve the challenging problems of hurricanes with small wind speed but the large size and large wind speed but small size, the area integral method with the concept of cut-in wind speed is introduced. The impact of small wind speed on wind disaster assessment is significantly reduced; the highest proportion of medium-strength and intense hurricanes is 14.5–22.5%, and that of weak hurricanes is 27.5–33.3%. Because the three-dimensional wind field is not easy to capture, the structure along the coastline is the most severely damaged, and the linear radial integral is less sensitive to small wind speeds than the quadratic area integral, a hurricane wind disaster assessment method based on radial integral is proposed. The results show that the method has good spatial region insensitivity. Both methods show that the numerical results can accurately represent the hurricane wind disaster when the horizontal grid size is 185 m or 555 m. However, the wind disaster assessment trends of the two methods are not linear because of the asymmetry of the hurricane structure. The two hurricane wind disaster assessment methods proposed in this study can better reflect the degree of disaster. For the comprehensive hurricane wind disaster assessment for large-scale wind farms in the deep sea, the area-based method can be used; for the infrastructure structures along the coastline, the radial-based method is more suitable. Since the measured meteorological data contain different characteristic radius and the corresponding wind speed of hurricanes, the method based on radial integral is more practical.
KW - Area integral
KW - Hurricane
KW - Radial integral
KW - Spatial characteristics
KW - Wind disaster assessment
UR - https://www.scopus.com/pages/publications/85140262411
U2 - 10.1016/j.oceaneng.2022.112804
DO - 10.1016/j.oceaneng.2022.112804
M3 - Article
AN - SCOPUS:85140262411
SN - 0029-8018
VL - 266
JO - Ocean Engineering
JF - Ocean Engineering
M1 - 112804
ER -