Projects per year
Abstract
This paper presents a rapid method for the evaluation of ship grounding risk and the estimation of avoidance action in real operational conditions. The approach makes use of big data analytics from Automatic Identification System (AIS), nowcast and General Bathymetric Chart of the Oceans (GEBCO) to generate potential grounding scenarios. Following the identification of potential grounding scenarios, a Fluid Structure Interaction (FSI) model is adopted to simulate grounding avoidance actions that account for the influence of surrounding water and ship controlling devices in 6- DoF. Application for the case of a passenger ship operating under ice free conditions in the Gulf of Finland demonstrates the potential of the method for the development of improved decision support systems and operational practices.
Original language | English |
---|---|
DOIs | |
Publication status | Published - 21 Sept 2022 |
MoE publication type | Not Eligible |
Event | SNAME Maritime Convention - Houston, United States Duration: 26 Sept 2022 → 29 Sept 2022 https://web.cvent.com/event/742733d5-d310-4259-8003-0d1caacee4f8/summary |
Conference
Conference | SNAME Maritime Convention |
---|---|
Abbreviated title | SMC |
Country/Territory | United States |
City | Houston |
Period | 26/09/2022 → 29/09/2022 |
Internet address |
Keywords
- 6-DoF maneuvering model
- big data analytics
- grounding risk
- Gulf of Finland
- machine learning
- ship safety
- simplified FSI
Fingerprint
Dive into the research topics of 'A Predictive Analytics Method for the Avoidance of Ship Grounding in Real Operational Conditions'. Together they form a unique fingerprint.Projects
- 1 Finished
-
FLARE: FLooding Accident REsponse
Hirdaris, S. (Principal investigator), Zhang, M. (Project Member) & Matusiak, J. (Project Member)
31/05/2019 → 30/11/2022
Project: EU: Framework programmes funding