• Proceedings of KOSOMES biannual meeting
• /
• 2018.06a
• /
• pp.61-61
• /
• 2018

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2017.11a
• /
• pp.247-247
• /
• 2017

연안선은 국제항해 선박에 비해 상대적으로 사고의 위험성은 높으나 이에 대응할 훈련기반이 취약하다. 본 연구에서는 연안선의 화재 및 퇴선상황에서의 승무원의 행동특성을 모델링하고 연안선 환경과 특성에 맞는 CBT용 훈련 프로그램을 개발함으로써 비상시 연안선 승무원의 사고대응 능력을 제고하고자 한다. 특히 이를 위해 연안 여객선에서 여객 대피를 위해 필요한 요소를 검토하여 개선점을 파악하여 프로그램 개발에 반영하고자 한다.

• Proceedings of KOSOMES biannual meeting
• /
• 2017.04a
• /
• pp.42-42
• /
• 2017

• Proceedings of KOSOMES biannual meeting
• /
• 2017.04a
• /
• pp.62-62
• /
• 2017

• Proceedings of KOSOMES biannual meeting
• /
• 2018.06a
• /
• pp.31-31
• /
• 2018

• Proceedings of KOSOMES biannual meeting
• /
• 2018.06a
• /
• pp.30-30
• /
• 2018

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2016.05a
• /
• pp.178-180
• /
• 2016

연안선은 중 대형선에 비하여 사고의 위험이 높고 작업 환경이나 안전에 대한 시스템적인 완성도가 매우 취약하다. 또한 바쁜 운항 스케줄과 승무원의 자질등의 여건으로 인하여 비상대응훈련이 잘 시행이 되지 않는 것이 현실이다. 여기에 현재 시행중인 훈련에 대한 시나리오도 중 대형선의 시나리오를 가지고 수정해서 사용하는 경우가 많고 본선에 적합하지 않는 훈련 시나리오를 가지고 훈련을 하는 경우도 많다. 본 연구는 이러한 문제점을 개선하고 연안선의 현실에 맞는 시나리오를 개발 및 자발적 참여유도를 통하여 연안선에서 시행되는 훈련의 효과를 증대시키고 나아가 안전한 해양문화에 이바지하는데 그 의의가 있다.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.7
• /
• pp.870-874
• /
• 2018

In the worst maritime accidents, people should abandon ship, but ship structures are narrow and complex and operation takes place on rough seas, so escape is not easy. In particular, passengers on cruise ships are untrained and varied, making evacuation prospects worse. In such a case, the evacuation management of the crew plays a very important role. If a rescuer enters a ship at distress and conducts rescue activities, which zones represent the most effective entry should be examined. Generally, crew and rescuers take the shortest route, but if an accident occurs along the shortest route, it is necessary to select the second-best alternative. To solve this situation, this study aims to calculate evacuation routes using Q-Learning of Reinforcement Learning, which is a machine learning technique. Reinforcement learning is one of the most important functions of artificial intelligence and is currently used in many fields. Most evacuation analysis programs developed so far use the shortest path search method. For this reason, this study explored optimal paths using reinforcement learning. In the future, machine learning techniques will be applicable to various marine-related industries for such purposes as the selection of optimal routes for autonomous vessels and risk avoidance.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.22 no.5
• /
• pp.410-416
• /
• 2016

After the Sewol Ferry accident, the importance of maritime safety has been emphasized in Korea. In particular, educational and experience training are not only being conducted for maritime personnel but also in schools and at maritime-related organizations in order to broadly instill maritime safety awareness. Based on SOLAS regulations, safety education for sailors conducted every 10 days passenger boats, and fire-fighting drills and abandon-ship training should be conducted once a month on merchant ships. After the Sewol Ferry accident, the maximum number of trainees was reduced from 40 to 20 in order to improve the effectiveness of these training sessions by requiring all trainees to participate in the actual training. The current training process consists of two steps: textbook-based theoretical training and actual practice. Current training environment provides limited capability from human and facility recourses which limit the numbers of trainee participated and system operation time. By introducing the simulation training, it will improve the trainee skill and performance prior to the on-site training and allow the more effective and rapid progress on actual practice. Therefore, it will be proposed the three-step training method in order to improve the effectiveness on fire-fighting drill in Maritime Safety Education on this study. This study suggests a three step training method that would increase the efficiency of maritime safety education. An image-training step to enhance individual task awareness and equipment usage via simulation techniques after theoretical training has been added. To implement this simulation, a virtual training session will be conducted before actual training, based on knowledge obtained from theoretical training, which is expected to increase the speed with which trainees can adapt during the practical training session. In addition, due to the characteristics of the simulation, repeated training is possible for reaction drills in emergency circumstances and other various scenarios that are difficult to replicate in actual training. The efficiency of training is expected to improve because trainees will have practiced before practical training takes place, which will decrease the time needed for practical training and increase the number of training sessions that can be executed, increasing the efficiency of training overall. This study considers development methods for fire-fighting drill simulations using virtual reality techniques.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.30 no.2
• /
• pp.200-208
• /
• 2024

The occurrence a fire on a training ship with a large number of people on board can lead to severe casualties. Hence the Seafarers' Act and Safety Life At Sea(SOLAS) emphasizes the importance of the abandon ship drill. Therefore, in this study, the training ship of Mokpo National Maritime University, Segero, which has a large number of people on board, was selected as the target ship and the likelihood and severity of fire accidents on each deck were predicted through the preliminary hazard analysis(PHA) qualitative risk assessment. Additionally, assuming a fire in a high-risk area, a simulation of evacuation time and population density was performed to quantitatively predict the risk. The the total evacuation time was predicted to be the longest at 501s in the meal time scenario, in which the population distribution was concentrated in one area. Depending on the scenario, some decks had relatively high population densities of over 1.4pers/m², preventing stagnation in the number of evacuees. The results of this study are expected to be used as basic data to develop training scenarios for training ships by quantifying evacuation time and population density according to various evacuation scenarios, and the research can be expanded in the future through comparison of mathematical models and experimental values.