کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
827660 | 1470223 | 2016 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An analytical method to assess the damage and predict the residual strength of a ship in a shoal grounding accident scenario
ترجمه فارسی عنوان
یک روش تحلیلی برای ارزیابی آسیب و پیش بینی قدرت باقی مانده یک کشتی در یک سناریوی حادثه زمین زاویه ای
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کلمات کلیدی
پای چوبه دار، استحکام باقی مانده، روش تحلیلی ساده، شبیه سازی عددی، تجزیه و تحلیل آسیب،
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی (عمومی)
چکیده انگلیسی
In this paper, a simplified analytical method used to predict the residual ultimate strength of a ship hull after a shoal grounding accident is proposed. Shoal grounding accidents always lead to severe denting, though not tearing, of the ship bottom structure, which may threaten the global hull girder resistance and result in even worse consequences, such as hull collapse. Here, the degree of damage of the bottom structure is predicted by a series of analytical methods based on the plastic-elastic deformation mechanism. The energy dissipation of a ship bottom structure is obtained from individual components to determine the sliding distance of the seabed obstruction. Then, a new approach to assess the residual strength of the damaged ship subjected to shoal grounding is proposed based on the improved Smith's method. This analytical method is verified by comparing the results of the proposed method and those generated by numerical simulation using the software ABAQUS. The proposed analytical method can be used to assess the safety of a ship with a double bottom during its design phase and predict the residual ultimate strength of a ship after a shoal grounding accident occurs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Ocean Engineering and Science - Volume 1, Issue 2, April 2016, Pages 167-179
Journal: Journal of Ocean Engineering and Science - Volume 1, Issue 2, April 2016, Pages 167-179
نویسندگان
Sun Bin, Hu Zhiqiang, Wang Jin, Yu Zhaolong,