Prediction of extreme cargo ship panel stresses by using deconvolution
Smoothing
Data set
DOI:
10.3389/fmech.2022.992177
Publication Date:
2022-09-30T07:01:01Z
AUTHORS (3)
ABSTRACT
Extreme value predictions typically originate from certain functional classes of statistical distributions to fit the data and are subsequently extrapolated. This paper describes an alternative method for extrapolation that is based on intrinsic properties set itself does not pre-assume any class. The proposed novel can be utilized in engineering design. To illustrate this, this study uses two examples showcase advantages method. first example used synthetic a non-linear Duffing oscillator new second was actual container ship sailing between Europe America experiencing large deck panel stresses severe weather. In example, onboard measured were present study. represents real physical case challenging model due non-stationary highly natures wave-ship load responses. especially so extreme responses, where roles higher-order responses tend more prominent have higher contributions. prediction accuracy also validated versus Naess–Gaidai Finally, discusses methods generic smoothing distribution tail irregularities underlying scarcity set.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (34)
CITATIONS (47)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....