A sensitivity quantification approach to significance analysis of thrusters in dynamic positioning operations. (1st March 2021)
- Record Type:
- Journal Article
- Title:
- A sensitivity quantification approach to significance analysis of thrusters in dynamic positioning operations. (1st March 2021)
- Main Title:
- A sensitivity quantification approach to significance analysis of thrusters in dynamic positioning operations
- Authors:
- Wang, Chunlin
Li, Guoyuan
Skulstad, Robert
Cheng, Xu
Osen, Ottar
Zhang, Houxiang - Abstract:
- Abstract: The safety of offshore operations is highly dependent on the dynamic positioning (DP) capability of a vessel. Meanwhile, DP capability comes down to the ability of the thrust generated by thrusters to counteract environmental forces. Therefore, it is significant to investigate which thrusters are important to the position-keeping ability of vessels. However, complex environmental factors make the investigation of thrusters' importance more complicated. Hence, this paper proposes a new method to identify the influence of each thruster on vessel's station-keeping capability in different sea states. The station-keeping capability is quantified by a defined synthesized positioning ability criterion comprised by vessel position, heading angle, and consumed power. Through the comparison of different machine learning approaches, support vector machine (SVM) is used for building a surrogate model between DP capability and thrusters. In order to determine the most sensitive thruster in the whole process of vessel operation, an improved sensitivity analysis (SA) called 'PAWN' is employed along with statistical analysis to evaluate the significance of thrusters from different perspectives. Seventeen cases are investigated with respect to different thruster failures in various sea states. The results show the proposed method is able to identify the significance of each thruster in different scenarios. Highlights: A data-driven structure is proposed for data analysis andAbstract: The safety of offshore operations is highly dependent on the dynamic positioning (DP) capability of a vessel. Meanwhile, DP capability comes down to the ability of the thrust generated by thrusters to counteract environmental forces. Therefore, it is significant to investigate which thrusters are important to the position-keeping ability of vessels. However, complex environmental factors make the investigation of thrusters' importance more complicated. Hence, this paper proposes a new method to identify the influence of each thruster on vessel's station-keeping capability in different sea states. The station-keeping capability is quantified by a defined synthesized positioning ability criterion comprised by vessel position, heading angle, and consumed power. Through the comparison of different machine learning approaches, support vector machine (SVM) is used for building a surrogate model between DP capability and thrusters. In order to determine the most sensitive thruster in the whole process of vessel operation, an improved sensitivity analysis (SA) called 'PAWN' is employed along with statistical analysis to evaluate the significance of thrusters from different perspectives. Seventeen cases are investigated with respect to different thruster failures in various sea states. The results show the proposed method is able to identify the significance of each thruster in different scenarios. Highlights: A data-driven structure is proposed for data analysis and modelling of significance of thrusters for dynamically positioned vessels. Taking advantage of a surrogate model, sensitivity analysis coupled with statistical analysis can be employed to comprehensively analyze the significance of thrusters in dynamical positioning operations. Experimental results from different dynamical positioning scenarios verify the effectiveness of the proposed method in quantifying the significance of thrusters. … (more)
- Is Part Of:
- Ocean engineering. Volume 223(2021)
- Journal:
- Ocean engineering
- Issue:
- Volume 223(2021)
- Issue Display:
- Volume 223, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 223
- Issue:
- 2021
- Issue Sort Value:
- 2021-0223-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-03-01
- Subjects:
- Dynamic positioning capability -- Sensitivity analysis -- Statistical analysis -- Thruster failures
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.2021.108659 ↗
- 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:
- 15942.xml