A Smart Risk Assessment Tool for Decision Support during Ship Evacuation
In case of a ship emergency situation and during its evolvement that might result in an evacuation, the master and the bridge command team of a ship have to continuously assess risk. This is a very complex procedure, as crucial decisions concerning safety are made under time pressure. The use of a d...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/5/1014 |
| _version_ | 1827741067486691328 |
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| author | Nikolaos P. Ventikos Alexandros Koimtzoglou Konstantinos Louzis Nikolaos Themelis Marios-Anestis Koimtzoglou |
| author_facet | Nikolaos P. Ventikos Alexandros Koimtzoglou Konstantinos Louzis Nikolaos Themelis Marios-Anestis Koimtzoglou |
| author_sort | Nikolaos P. Ventikos |
| collection | DOAJ |
| description | In case of a ship emergency situation and during its evolvement that might result in an evacuation, the master and the bridge command team of a ship have to continuously assess risk. This is a very complex procedure, as crucial decisions concerning safety are made under time pressure. The use of a decision-support tool would have a positive effect on their performance, resulting in an improvement in the way ships are evacuated. The purpose of this paper is to present the PALAEMON smart risk assessment platform (SRAP). SRAP is a real-time risk assessment platform developed to assist the decision-making process of the master and bridge command team of a ship regarding the evacuation process. Its purpose is to provide decision support for the following aspects: (1) the decision to sound the general alarm (GA) following an accident, (2) monitoring the progress of the mustering process in order to take any additional actions, and (3) the decision to abandon the ship or not. SRAP dynamically assesses the risk to the safety of the passengers and crew members in the different phases of the evacuation process, so one model in the form Bayesian networks (BNs) was developed for each stage of the evacuation process. The results of a case study that was implemented reflect how various parameters such as injuries, congestion, and the functionality of the ship’s systems affect the outcome of each model. |
| first_indexed | 2024-03-11T03:36:51Z |
| format | Article |
| id | doaj.art-d0ec60d9f6044bd4a18e125b1c3e4c53 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-11T03:36:51Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-d0ec60d9f6044bd4a18e125b1c3e4c532023-11-18T02:00:01ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-05-01115101410.3390/jmse11051014A Smart Risk Assessment Tool for Decision Support during Ship EvacuationNikolaos P. Ventikos0Alexandros Koimtzoglou1Konstantinos Louzis2Nikolaos Themelis3Marios-Anestis Koimtzoglou4School of Naval Architecture and Marine Engineering, National Technical University of Athens (NTUA), 157 80 Athens, GreeceSchool of Naval Architecture and Marine Engineering, National Technical University of Athens (NTUA), 157 80 Athens, GreeceSchool of Naval Architecture and Marine Engineering, National Technical University of Athens (NTUA), 157 80 Athens, GreeceSchool of Naval Architecture and Marine Engineering, National Technical University of Athens (NTUA), 157 80 Athens, GreeceSchool of Naval Architecture and Marine Engineering, National Technical University of Athens (NTUA), 157 80 Athens, GreeceIn case of a ship emergency situation and during its evolvement that might result in an evacuation, the master and the bridge command team of a ship have to continuously assess risk. This is a very complex procedure, as crucial decisions concerning safety are made under time pressure. The use of a decision-support tool would have a positive effect on their performance, resulting in an improvement in the way ships are evacuated. The purpose of this paper is to present the PALAEMON smart risk assessment platform (SRAP). SRAP is a real-time risk assessment platform developed to assist the decision-making process of the master and bridge command team of a ship regarding the evacuation process. Its purpose is to provide decision support for the following aspects: (1) the decision to sound the general alarm (GA) following an accident, (2) monitoring the progress of the mustering process in order to take any additional actions, and (3) the decision to abandon the ship or not. SRAP dynamically assesses the risk to the safety of the passengers and crew members in the different phases of the evacuation process, so one model in the form Bayesian networks (BNs) was developed for each stage of the evacuation process. The results of a case study that was implemented reflect how various parameters such as injuries, congestion, and the functionality of the ship’s systems affect the outcome of each model.https://www.mdpi.com/2077-1312/11/5/1014marine evacuationrisk assessmentrisk modelsBayesian networkspassenger ships |
| spellingShingle | Nikolaos P. Ventikos Alexandros Koimtzoglou Konstantinos Louzis Nikolaos Themelis Marios-Anestis Koimtzoglou A Smart Risk Assessment Tool for Decision Support during Ship Evacuation Journal of Marine Science and Engineering marine evacuation risk assessment risk models Bayesian networks passenger ships |
| title | A Smart Risk Assessment Tool for Decision Support during Ship Evacuation |
| title_full | A Smart Risk Assessment Tool for Decision Support during Ship Evacuation |
| title_fullStr | A Smart Risk Assessment Tool for Decision Support during Ship Evacuation |
| title_full_unstemmed | A Smart Risk Assessment Tool for Decision Support during Ship Evacuation |
| title_short | A Smart Risk Assessment Tool for Decision Support during Ship Evacuation |
| title_sort | smart risk assessment tool for decision support during ship evacuation |
| topic | marine evacuation risk assessment risk models Bayesian networks passenger ships |
| url | https://www.mdpi.com/2077-1312/11/5/1014 |
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