Development of Empirical Formulas for Approximate Spectral Moment Based on Rain-Flow Counting Stress-Range Distribution

Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in compar...

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Bibliographic Details
Main Authors: Seockhee Jun, Jun-Bum Park
Format: Article
Language:English
Published: The Korean Society of Ocean Engineers 2021-08-01
Series:한국해양공학회지
Subjects:
Online Access:https://www.joet.org/journal/view.php?doi=10.26748/KSOE.2021.014
Description
Summary:Many studies have been performed to predict a reliable and accurate stress-range distribution and fatigue damage regarding the Gaussian wide-band stress response due to multi-peak waves and multiple dynamic loads. So far, most of the approximation models provide slightly inaccurate results in comparison with the rain-flow counting method as an exact solution. A step-by-step study was carried out to develop new approximate spectral moments that are close to the rain-flow counting moment, which can be used for the development of a fatigue damage model. Using the special parameters and bandwidth parameters, four kinds of parameter-based combinations were constructed and estimated using the R-squared values from regression analysis. Based on the results, four candidate empirical formulas were determined and compared with the rain-flow counting moment, probability density function, and root mean square (RMS) value for relative distance. The new approximate spectral moments were finally decided through comparison studies of eight response spectra. The new spectral moments presented in this study could play an important role in improving the accuracy of fatigue damage model development. The present study shows that the new approximate moment is a very important variable for the enhancement of Gaussian wide-band fatigue damage assessment.
ISSN:1225-0767
2287-6715