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:
-
- 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}
}
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Figures / Tables:
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:
3-dimensional environmental contours based on a direct sampling method for structural reliability analysis of ships and offshore structures
journal, May 2018
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Alternative approaches to develop environmental contours from metocean data
journal, October 2018
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- Journal of Ocean Engineering and Marine Energy, Vol. 4, Issue 4
A Survey of WEC Reliability, Survival and Design Practices
journal, December 2017
- Coe, Ryan; Yu, Yi-Hsiang; van Rij, Jennifer
- Energies, Vol. 11, Issue 1
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
Figures / Tables found in this record:
Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.