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Title: Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

Abstract

Abstract not provided.

Authors:
 [1];  [1];  [1];  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1237665
Alternate Identifier(s):
OSTI ID: 1359711; OSTI ID: 1427239; OSTI ID: 1512898
Report Number(s):
SAND-2015-5328J; SAND-2015-1444J; SAND-2015-9228J
Journal ID: ISSN 0029-8018; PII: S0029801815006721
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Ocean Engineering
Additional Journal Information:
Journal Volume: 112; Journal Issue: C; Journal ID: ISSN 0029-8018
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 42 ENGINEERING; inverse FORM; principal component analysis; environmental contours; extreme sea state characterization

Citation Formats

Eckert-Gallup, Aubrey C., Sallaberry, Cédric J., Dallman, Ann R., and Neary, Vincent S.. Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states. United States: N. p., 2016. Web. doi:10.1016/j.oceaneng.2015.12.018.
Eckert-Gallup, Aubrey C., Sallaberry, Cédric J., Dallman, Ann R., & Neary, Vincent S.. Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states. United States. https://doi.org/10.1016/j.oceaneng.2015.12.018
Eckert-Gallup, Aubrey C., Sallaberry, Cédric J., Dallman, Ann R., and Neary, Vincent S.. Wed . "Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states". United States. https://doi.org/10.1016/j.oceaneng.2015.12.018. https://www.osti.gov/servlets/purl/1237665.
@article{osti_1237665,
title = {Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states},
author = {Eckert-Gallup, Aubrey C. and Sallaberry, Cédric J. and Dallman, Ann R. and Neary, Vincent S.},
abstractNote = {Abstract not provided.},
doi = {10.1016/j.oceaneng.2015.12.018},
journal = {Ocean Engineering},
number = C,
volume = 112,
place = {United States},
year = {Wed Jan 06 00:00:00 EST 2016},
month = {Wed Jan 06 00:00:00 EST 2016}
}

Journal Article:

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Figures / Tables:

Figure 1 Figure 1: Representation of data density for four study sites (a) NDBC 46212, (b) NDBC 46022, (c) NDBC 51202, (d) NDBC 46050.

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Works referencing / citing this record:

Alternative approaches to develop environmental contours from metocean data
journal, October 2018

  • Manuel, Lance; Nguyen, Phong T. T.; Canning, Jarred
  • Journal of Ocean Engineering and Marine Energy, Vol. 4, Issue 4
  • DOI: 10.1007/s40722-018-0123-0

A Survey of WEC Reliability, Survival and Design Practices
journal, December 2017

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  • Energies, Vol. 11, Issue 1
  • DOI: 10.3390/en11010004

Characterization of Extreme Wave Conditions for Wave Energy Converter Design and Project Risk Assessment
journal, April 2020

  • Neary, Vincent S.; Ahn, Seongho; Seng, Bibiana E.
  • Journal of Marine Science and Engineering, Vol. 8, Issue 4
  • DOI: 10.3390/jmse8040289