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An Assessment of the Accuracy of SRD Methodologies ...
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The study evaluates whether three established soil resistance to driving (SRD) methods accurately predict offshore wind monopile installation: Alm and Hamre (2001), Toolan and Fox (1977), and Stevens et al. (1982). These methods were developed largely from oil-and-gas pile data, typically for piles much smaller than modern wind-farm monopiles.<br /><br />Researchers back-analysed 260 installation records from four offshore wind farms in the North and Irish Seas. The records covered varied soil profiles, driving conditions, penetration depths, and monopile diameters of 5.9–8.1 m. Using wave-equation analysis, they compared predicted and recorded blow counts and assessed prediction error with the normalized root mean square deviation (NRSMD).<br /><br />Across the full dataset, all three methods showed limited accuracy and substantial variability. Toolan and Fox produced the highest share of “good” matches (59%), while Stevens et al. had the lowest mean error (0.57, compared with 0.65 for Toolan and Fox and 0.72 for Alm and Hamre). Performance depended strongly on the project’s local ground conditions: results were generally better at two neighboring sites, but markedly poorer at another, where some methods predicted pile refusal. The study found no clear evidence that increasing pile diameter from 5.9 m to 8.0 m alone reduced accuracy.<br /><br />The authors conclude that existing formulations often provide poor drivability predictions for large offshore wind monopiles. Their limited, region-specific calibration data—drawn mainly from smaller oil-and-gas piles—may explain the shortcomings. They recommend developing SRD methods specifically for offshore wind, calibrated against larger and geographically broader monopile installation databases.
Keywords
offshore wind monopile
soil resistance to driving
drivability prediction
wave-equation analysis
blow count
installation records
normalized root mean square deviation
pile refusal
foundation engineering
offshore wind farms
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