Hybrid Parabolic Interpolation – Artificial Neural Network Method (HPI-ANNM) for long-term extreme response estimation of steel risers
This paper presents a computer efficient approach to evaluate the multi-dimensional integral found in the evaluation of the long-term extreme response of marine structures. The proposed method is a hybrid combination of two numerical procedures. The first one consists of a parabolic interpolation scheme used to obtain the statistical parameters describing the short-term peaks probability distribution of the time-series responses, designated as PIM (Parabolic Interpolation Method), which reduces the total number of short-term structural analyses. The second one is an Artificial Neural Network-based surrogate model which is used to obtain long response time histories based on short finite element-based simulations. The approach is named as HPI-ANNM (Hybrid Parabolic Interpolation – Artificial Neural Network Method). The efficiency and accuracy of the proposed hybrid method is compared with the complete long-term integration method in the analysis of 100-yr characteristic values of cross-section utilization ratios of a Steel Catenary Riser (SCR) connected to a semi-submersible platform in deep water.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/01411187
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Supplemental Notes:
- Abstract reprinted with permission of Elsevier.
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Authors:
- Monsalve-Giraldo, J S
- Cortina, Jo�o P R
- de Sousa, Fernando J M
- Videiro, Paulo M
- Sagrilo, Luis V S
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References; Tables;
- Pagination: pp 221-234
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Serial:
- Applied Ocean Research
- Volume: 76
- Publisher: Elsevier
- ISSN: 0141-1187
- Serial URL: https://www.sciencedirect.com/journal/applied-ocean-research
Subject/Index Terms
- TRT Terms: Neural networks; Offshore structures; Steel structures; Structural analysis
- Uncontrolled Terms: Steel catenary risers
- Subject Areas: Bridges and other structures; Design; Marine Transportation;
Filing Info
- Accession Number: 01675902
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 24 2018 10:06AM