skip to main content


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

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. These environmental contours are characterized by combinations of significant wave height (H s) and either energy period (T e) or peak period (T p) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is a standard design practice for generating environmental contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. As a result, these modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for determining design loads for marine structures.
 [1] ;  [1] ;  [1] ;  [1]
  1. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Report Number(s):
SAND-2015-5328J; SAND-2015-1444J
Journal ID: ISSN 0029-8018; PII: S0029801815006721
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Ocean Engineering
Additional Journal Information:
Journal Volume: 112; Journal Issue: C; Journal ID: ISSN 0029-8018
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)
Country of Publication:
United States
54 ENVIRONMENTAL SCIENCES; 42 ENGINEERING; inverse FORM; principal component analysis; environmental contours; extreme sea state characterization
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1237665; OSTI ID: 1359711