Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network. (1st April 2021)
- Record Type:
- Journal Article
- Title:
- Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network. (1st April 2021)
- Main Title:
- Fragility assessment approach of deepwater drilling risers subject to harsh environments using Bayesian regularization artificial neural network
- Authors:
- Zhang, Nan
Chang, Yuanjiang
Shi, Jihao
Chen, Guoming
Zhang, Shenyan
Cai, Baoping - Abstract:
- Abstract: The drilling risers are the most critical and vulnerable connection of floating drilling platform and subsea wellhead. In order to improve the operation efficiency, the operators have attempted to suspend the drilling operations and keep the drilling risers connected to the wellhead to survive in the storm, thus the fragility of the drilling risers under storm is of paramount importance to drilling operations. This paper is aimed at proposing an efficient and robust BRANN-based non-intrusive approach for the fragility assessment of the deepwater drilling riser subject to storms. The proposed approach, which could effectively reflect the non-linear relationship between the input and output data, can generate thousands of non-numerical data under limited Finite Element Analysis (FEA) of the drilling risers, while the Monte Carlo Simulation (MCS) could be further incorporated to calculate the fragility curve. A case study was conducted to demonstrate the characteristics with respect to significantly computational reduction of the proposed approach compared to the conventional MCS method, and the proposed approach was verified to be robust and efficient in assessing the fragility of the drilling risers under storms. The related conclusions could be used to provide reference for operations of drilling risers under harsh environment. Highlights: A BRANN-based methodology for the fragility assessment of the deepwater drilling riser subject to storms is proposed. A robustAbstract: The drilling risers are the most critical and vulnerable connection of floating drilling platform and subsea wellhead. In order to improve the operation efficiency, the operators have attempted to suspend the drilling operations and keep the drilling risers connected to the wellhead to survive in the storm, thus the fragility of the drilling risers under storm is of paramount importance to drilling operations. This paper is aimed at proposing an efficient and robust BRANN-based non-intrusive approach for the fragility assessment of the deepwater drilling riser subject to storms. The proposed approach, which could effectively reflect the non-linear relationship between the input and output data, can generate thousands of non-numerical data under limited Finite Element Analysis (FEA) of the drilling risers, while the Monte Carlo Simulation (MCS) could be further incorporated to calculate the fragility curve. A case study was conducted to demonstrate the characteristics with respect to significantly computational reduction of the proposed approach compared to the conventional MCS method, and the proposed approach was verified to be robust and efficient in assessing the fragility of the drilling risers under storms. The related conclusions could be used to provide reference for operations of drilling risers under harsh environment. Highlights: A BRANN-based methodology for the fragility assessment of the deepwater drilling riser subject to storms is proposed. A robust and efficient BRANN-DMs-Deterministic model for fragility assessment is developed. A case study of a deepwater drilling riser in South China Sea is performed. The fragility curves of the deepwater drilling riser subject to storms are derived with the proposed approach. … (more)
- Is Part Of:
- Ocean engineering. Volume 225(2021)
- Journal:
- Ocean engineering
- Issue:
- Volume 225(2021)
- Issue Display:
- Volume 225, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 225
- Issue:
- 2021
- Issue Sort Value:
- 2021-0225-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04-01
- Subjects:
- Deepwater drilling riser -- Bayesian regularization artificial neuron network -- Fragility assessment -- Non-intrusive model -- Limit state equations -- Logistic regression
Ocean engineering -- Periodicals
Ocean engineering
Periodicals
620.4162 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00298018 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.oceaneng.2021.108793 ↗
- Languages:
- English
- ISSNs:
- 0029-8018
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6231.280000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16034.xml