التفاصيل البيبلوغرافية
| العنوان: |
Methods for Fitting the Limit State Function of the Residual Strength of Damaged Ships |
| المؤلفون: |
Zhiyao Zhu, Huilong Ren, Xiuhuan Wang, Nan Zhao, Chenfeng Li |
| المصدر: |
Journal of Marine Science and Engineering; Volume 10; Issue 1; Pages: 102 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2022 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
limit state function, longitudinal strength, least-squares method, moving least-squares method, radial basis function neural network method, weighted piecewise fitting method |
| جغرافية الموضوع: |
agris |
| الوصف: |
The limit state function is important for the assessment of the longitudinal strength of damaged ships under combined bending moments in severe waves. As the limit state function cannot be obtained directly, the common approach is to calculate the results for the residual strength and approximate the limit state function by fitting, for which various methods have been proposed. In this study, four commonly used fitting methods are investigated: namely, the least-squares method, the moving least-squares method, the radial basis function neural network method, and the weighted piecewise fitting method. These fitting methods are adopted to fit the limit state functions of four typically sample distribution models as well as a damaged tanker and damaged bulk carrier. The residual strength of a damaged ship is obtained by an improved Smith method that accounts for the rotation of the neutral axis. Analysis of the results shows the accuracy of the linear least-squares method and nonlinear least-squares method, which are most commonly used by researchers, is relatively poor, while the weighted piecewise fitting method is the better choice for all investigated combined-bending conditions. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
Ocean Engineering; https://dx.doi.org/10.3390/jmse10010102 |
| DOI: |
10.3390/jmse10010102 |
| الاتاحة: |
https://doi.org/10.3390/jmse10010102 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.8B90542D |
| قاعدة البيانات: |
BASE |