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Reliability of extreme wave prediction methods
Author(s)
Date Issued
2015-07-15
Date Available
2019-05-13T09:37:44Z
Abstract
Extreme wave parameters are used for engineering design in our seas and oceans, yet the methods used to determine them are non-standardized and can give highly variable output. With increased commercial activity in the marine sector, the importance of accurate extreme wave parameter determination has become increasingly apparent. This is particularly the case for marine renewable structures where even small over-predictions in design parameters can affect the whole feasibility of the project. This paper addresses the methods of extreme wave prediction currently in use, with a view to selecting the optimal method for the prediction of extreme wave conditions (Hs, Hmax and Tz) in coastal Irish waters. The paper identifies pitfalls and drawbacks of current extreme prediction methods, with particular attention given to the use of limited in time buoy data from coastal locations where development is to take place. In addition a new methodology of determining extreme wave periods, that is the wave periods occurring coincidentally with the most extreme wave heights, is established. This is important as the destructive energy of a wave is dependent on the wave period. By estimating the extreme wave energy and significant wave height, it is possible to formulate a method of reliably approximating the likely coincident wave period.
Type of Material
Conference Publication
Copyright (Published Version)
2015 the Authors
Language
English
Status of Item
Not peer reviewed
Journal
12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015
Conference Details
12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015, Vancouver, Canada, July 12-15 2015
ISBN
9780888652454
This item is made available under a Creative Commons License
File(s)
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Name
Paper_254_Barker.pdf
Size
309.7 KB
Format
Adobe PDF
Checksum (MD5)
93912d0f10f088827e8bd8261465283c
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