Wyniki wyszukiwania - BazTech

1

Evaluation of near-collisions in the Tagus River Estuary using a marine traffic simulation model

Rong H., Teixeira A., Soares C. G.

Zeszyty Naukowe Akademii Morskiej w Szczecinie

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2015

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nr 43 (115)

68--78

EN

This paper evaluates near ship-ship collision situations in the Tagus River Estuary using a simulation model of ship navigation in restricted waters. The simulation model consists of a ship collision avoidance model based on the Artificial Potential Field (APF) method, which has been improved to account for the lateral distribution of traffic along the route, the ship type and length and speed development of the ships along the trajectory. AIS data of ships entering and leaving the port of Lisbon are analysed to obtain the main characteristics of traffic parameters used as input for the traffic simulation model, such as: the routes of the vessels, speed distribution along the routes, traffic density and characteristics of the ships in each route, among others. First, the improved model of ship navigation and the Monte Carlo simulation technique are used to simulate the marine traffic in the Tagus River Estuary. Then, the concept of “ship domain” is used as collision criterion to determine the number of near collisions and the locations where they are most likely to occur. Finally, the simulation results are compared to the ones obtained from raw AIS data to assess the capability of the simulation model for marine traffic risk analysis.

2

Analysis of the influence of waves in the occurrence of accidents in the Portuguese coast using bayesian belief networks

Antao P., Soares C. G.

Journal of KONBiN

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2010

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No. 1 (13)

105-116

EN

Sea and weather conditions are the second most frequent cause of accidents in Portuguese waters accounting for 23% of the occurrences. However due to lack of information in the Portuguese maritime accident database it is difficult to assess what this cause consists specifically, i.e., fog, large wave heights or other events. In the present study significant wave height data was introduced in a Bayesian Belief Network (BBN) model in order assess the correlation between their amplitude and certain accident typologies and related consequences (human injuries or fatalities). The results of different inferences of the BBN model show that through a simple modification of an accident model the influence of weather pattern can be assessed and specific risk factors can be identified.

PL

Stan morza i warunki atmosferyczne to druga z najczęściej występujących przyczyn wypadków na wodach terytorialnych Portugalii, odpowiedzialna za 23% zdarzeń. Ze względu na brak informacji w bazie danych o wypadkach morskich w Portugalii trudno jednak ocenić, co konkretnie stanowi o zaistnieniu wypadku: mgła, duża wysokość fal, czy też inne czynniki. W niniejszej pracy dokonano następującego zabiegu: do modelu opartego na sieci bayesowskiej (Bayesian Belief Network - BBN) wprowadzono dane o znaczącej wysokości fal, a to celem dokonania oceny korelacji między ich amplitudą, typologią wypadków określonego rodzaju, oraz wynikającymi konsekwencjami w postaci odniesionych przez ludzi obrażeń czy też wypadków śmiertelnych. Wyniki wnioskowania na bazie modelu BBN dowodzą, że dzięki prostej modyfikacji modelu wypadku można ocenić wpływ określonych warunków atmosferycznych na zaistnienie wypadku oraz zidentyfikować konkretne czynniki ryzyka.

3

Optimisation of the preventive maintenance plan of a series components system with Weibull hazard function

Duarte J. C., Soares C. G.

Journal of Polish Safety and Reliability Association

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2007

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Vol. 1

67--73

EN

In this paper we propose an algorithm to calculate the optimum frequency to perform preventive maintenance in equipment that exhibits Weibull hazard function and constant repair rate in order to ensure its availability. Based on this algorithm we have developed another one to solve the problem of maintenance management of a series system based on preventive maintenance over the different system components. We assume that all components of the system still exhibit Weibull hazard function and constant repair rate and that preventive maintenance would bring the system to the as good as new condition. The algorithm calculates the interval of time between preventive maintenance actions for each component, minimizing the costs, and in such a way that the total downtime, in a certain period of time, does not exceed a predetermined value.