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Tracking and forecasting method and numerical simulation of high-risk ice in cold wave weather
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Na Zhang1, Shengkai Xu1, Ning Xu2, *, Litao Wang1, Anliang Wang3
Haiyang Xuebao | 2023, 45(2) : 110 - 117
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Haiyang Xuebao | 2023, 45(2): 110-117
• Article •
Tracking and forecasting method and numerical simulation of high-risk ice in cold wave weather
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Na Zhang1, Shengkai Xu1, Ning Xu2, *, Litao Wang1, Anliang Wang3
Affiliations
  • 1Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
  • 2National Marine Environmental Monitoring Center, Dalian 116023, China
  • 3National Marine Environmental Forecasting Center, Beijing 100081, China
Published: 2023-02-01 doi: 10.12284/hyxb2023015
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To provide technical support for sea ice environmental monitoring and dynamic risk early warning in the sea area of the proposed, under construction and built cold source water intake project in cold regions, a Lagrangian particle tracking prediction model under the sea ice ocean coupling condition is constructed in this paper. Taking the water intake of a nuclear power station in the Liaodong Bay as an example, the migration trajectories of high-risk ice blocks in 24 h, 48 h and 72 h under cold wave weather and the probability of entering the water intake are simulated and discussed. The results show that since the direction of the water intake is almost perpendicular to the flow direction and wind direction, less than 6% of the 1200 high-risk ice particles randomly released outside the water intake enter the water intake. It is found that most of the particles come from within 300 m near the water intake by identifying the particle color in different regions. The results of sensitivity analysis showed that when the number of released particles increased to 5 times, the conclusion remained unchanged. This study provides a new method for safety early warning of cold source water intake.

Liaodong Bay  /  cold source water intake  /  sea ice  /  coupling model  /  Lagrangian particle tracking model
Na Zhang, Shengkai Xu, Ning Xu, Litao Wang, Anliang Wang. Tracking and forecasting method and numerical simulation of high-risk ice in cold wave weather[J]. Haiyang Xuebao, 2023 , 45 (2) : 110 -117 . DOI: 10.12284/hyxb2023015
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Year 2023 volume 45 Issue 2
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Article Info
doi: 10.12284/hyxb2023015
  • Receive Date：2022-08-08
  • Online Date：2025-12-26
  • Published：2023-02-01
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History
  • Received：2022-08-08
  • Revised：2022-09-04
Funding
Affiliations
    1Tianjin Key Laboratory of Soft Soil Characteristics & Engineering Environment, Tianjin Chengjian University, Tianjin 300384, China
    2National Marine Environmental Monitoring Center, Dalian 116023, China
    3National Marine Environmental Forecasting Center, Beijing 100081, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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