A Hybrid Method to Evaluate Soil Liquefaction Potential of Seabed at Offshore Wind Farm in Taiwan

Yu-Shu Kuo, Kai-Jun Chong, Shang-Chun Chang, Juin-Fu Chai and Hui-Ting Hsu
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Yu-Shu Kuo: Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan 701, Taiwan
Kai-Jun Chong: Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan 701, Taiwan
Shang-Chun Chang: CECI Engineering Consultants, Taipei 114, Taiwan
Juin-Fu Chai: National Center for Research on Earthquake Engineering, Taipei 106, Taiwan
Hui-Ting Hsu: Department of Hydraulic and Ocean Engineering, National Cheng-Kung University, Tainan 701, Taiwan

Energies, 2021, vol. 14, issue 7, 1-18

Abstract: This paper undertakes liquefaction analysis with simplified procedures with standard penetration test (SPT) data and cone penetration test (CPT) data obtained from an offshore wind farm in the Changhua area. The soil liquefaction resistance calculated by the SPT-based simplified procedure suggested by the Japan Railway Association was in agreement with the laboratory results. The CPT is widely used in the site investigation of offshore wind farms. However, Taiwan’s registered professional engineers are still familiar with soil liquefaction analysis for offshore wind farms using SPT-based methods. Hence, a hybrid method that incorporates an SPT–CPT correlation into the New Japan Road Association (NJRA) method is proposed to evaluate the soil liquefaction potential for offshore wind farms in Taiwan. In the case studies of soil liquefaction with five groups of adjacent boreholes in Changhua’s offshore wind farms, the hybrid method shows that the soil liquefaction potential with CPT data is consistent with the results calculated with SPT-based simplified procedures. To quantify the risk of soil liquefaction, Monte Carlo simulation is used to calculate the uncertainty of CPT– q c for estimating the probability of soil liquefaction with the hybrid method.

Keywords: offshore wind farm; soil liquefaction; SPT–CPT correlation; Monte Carlo simulation; risk assessment (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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