Sensitivity analysis of parameters influencing the ice–seabed interaction in sand by using extreme learning machine

Hamed Azimi and Hodjat Shiri ()
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Hamed Azimi: Memorial University of Newfoundland
Hodjat Shiri: Memorial University of Newfoundland

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2021, vol. 106, issue 3, No 25, 2307-2335

Abstract: Abstract Ice gouging problem is a significant challenge threatening the integrity of subsea pipelines in the Arctic (e.g., Beaufort Sea) and even non-Arctic (e.g., Caspian Sea) offshore regions. Determining the seabed response to ice scour through the subgouge soil deformations and the keel reaction forces are important aspects for a safe and cost-effective design. In this study, the subgouge soil deformations and the keel reaction forces were simulated by the extreme learning machine (ELM) for the first time. Nine ELM models (ELM 1–ELM 9) were developed using the key parameters governing the ice–seabed interaction. The number of neurons in the hidden layer was optimized and the best activation function for the ELM network was identified. The premium ELM model, resulting in the lowest level of inaccuracy and complexity and the highest level of correlation with experimental values was identified by performing a sensitivity analysis. The gouge depth ratio and the shear strength of the seabed soil were found to be the most influential input parameters affecting the subgouge soil deformations and the keel reaction forces. A set of the ELM-based equations were proposed to approximate the ice gouging parameters. The uncertainty analysis showed that the premium ELM model slightly underestimated the subgouge soil deformation.

Keywords: Ice–seabed interaction; Sandy seabed; Extreme learning machine; Sensitivity analysis; Uncertainty analysis (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:106:y:2021:i:3:d:10.1007_s11069-021-04544-9

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DOI: 10.1007/s11069-021-04544-9

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