(Created blank page)
 
Line 1: Line 1:
 +
                               
 +
==Abstract==
  
 +
Small strain shear modulus 𝐺 preferred reference method for 𝐺 is an important parameter for design of foundations of fixed offshore structures. The is the seismic velocity test (SVT) performed as part of a seismic cone penetration test (SCPT). SVTs provide in-situ 𝐺 values for discrete depth sections of SCPTs.  This paper focusses on added value achieved by (1) generation of 15 million synthetic 𝐺 (2) a 𝐺 profiles to 50 m depth and zonation map for the IJmuiden Ver Wind Farm Sites Alpha and Beta (offshore Netherlands). The synthetic 𝐺 profiles were derived from a data set of 51 SCPT profiles, 250 CPT profiles and 2D UHR seismic reflection traces along survey track lines spaced at about 70 m. The quality of the SCPT data and UHR seismic reflection data was stateof-the-art (as of 2021). The data process included the use of a (1) multi fidelity data fusion statistical framework and (2) machine learning by a convolutional neural network. The synthetic 𝐺 data were the basis for the 𝐺 zonation map used to enhance an integrated ground model for the wind farm sites. Particularly, the map can be used to quickly identify and constrain areas which are favourable and challenging for design of monopiles and other common foundation types typically considered for offshore wind turbines.

Revision as of 11:01, 7 June 2024

Abstract

Small strain shear modulus 𝐺 preferred reference method for 𝐺 is an important parameter for design of foundations of fixed offshore structures. The is the seismic velocity test (SVT) performed as part of a seismic cone penetration test (SCPT). SVTs provide in-situ 𝐺 values for discrete depth sections of SCPTs. This paper focusses on added value achieved by (1) generation of 15 million synthetic 𝐺 (2) a 𝐺 profiles to 50 m depth and zonation map for the IJmuiden Ver Wind Farm Sites Alpha and Beta (offshore Netherlands). The synthetic 𝐺 profiles were derived from a data set of 51 SCPT profiles, 250 CPT profiles and 2D UHR seismic reflection traces along survey track lines spaced at about 70 m. The quality of the SCPT data and UHR seismic reflection data was stateof-the-art (as of 2021). The data process included the use of a (1) multi fidelity data fusion statistical framework and (2) machine learning by a convolutional neural network. The synthetic 𝐺 data were the basis for the 𝐺 zonation map used to enhance an integrated ground model for the wind farm sites. Particularly, the map can be used to quickly identify and constrain areas which are favourable and challenging for design of monopiles and other common foundation types typically considered for offshore wind turbines.

Back to Top

Document information

Published on 07/06/24
Submitted on 07/06/24

Volume Emerging technologies in site characterization for Offshore Wind Towers, 2024
DOI: 10.23967/isc.2024.240
Licence: CC BY-NC-SA license

Document Score

0

Views 0
Recommendations 0

Share this document

Keywords

claim authorship

Are you one of the authors of this document?