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Wyszukujesz frazę "marine condition" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Statistical Studies on Marine Accidents Happened on the Bohai Sea
Autorzy:
Wu, Z.
Zhao, J.
Li, G.
Powiązania:
https://bibliotekanauki.pl/articles/116959.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Marine Accidents
Ship Accidents
Marine Traffic Accidents
Chinese Navigable Waterways
Weather Condition
Decision Making Process
Human Factor
Statistical Study
Opis:
a statistical study is carried out on the basis of information of marine traffic accidents occurred from 1996 to 2005 on the Bohai Sea. The time distribution and geographic distribution of the marine traffic accidents, as well as the relationships between the accidents and weather condition, type of accidents area, accident category, size of ships are analyzed, which provide references for adopting safety decision-making and take relative precautionary measures to avoid and decrease occurrence of accidents.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2008, 2, 2; 183-186
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multiparameter approximation model of temperature conditions of marine diiesel generator sets, based on Markov chain Monte Carlo
Autorzy:
Myrhorod, V.
Hvozdeva, I.
Budashko, V.
Powiązania:
https://bibliotekanauki.pl/articles/24201416.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
marine diesel engine
Markov chain Monte Carlo
temperature condition
multi-parameter approximation model
marine diesel generator
markov model
diagnostics
technical diagnostics
Opis:
In the article we propose a multi-parameter approximation model, based on Markov chain Monte Carlo, which describes the relationship between the temperature regime, operating conditions and electromechanical parameters of marine diesel generator sets. The approximation model is constructed on the basis of the analysis of experimental data of the exhaust gases temperature of marine diesel generator sets in their long-term operation. As a statistical model of random processes of temperature deviations from the approximation model, a Markov process model is proposed that takes into account the possible correlation of the initial data. Since the measuring channels of modern diagnostic systems are digital, due to discretization in time and level, the studied processes form a Markov chain, which makes it possible to establish the important features of such processes. The use of approximation models ensures the stationarity conditions and the correctness of the proposed Markov model in the conditions of multi-mode operation of marine diesel generator sets. The proposed multi-parameter approximation model, based on Markov chain Monte Carlo, allows you to take into account random perturbations that lead to a random change in the output coordinates of the diagnostic object. The proposed improvement of the model makes it possible to ensure its adequacy to real processes of changing the parameters of the temperature regimes of marine diesel generator sets. The proposed multi-parameter approximation model, based on Markov chain Monte Carlo, can be used in the systems of technical diagnostics of marine diesel generator sets in order to increase the reliability of diagnostic conclusions.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2022, 16, 4; 779--784
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Marine Navigation Using Expert System
Autorzy:
Nikitakos, N.
Fikaris, G.
Powiązania:
https://bibliotekanauki.pl/articles/117046.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
marine navigation
Expert System
Safety of Navigation
Weather Condition
Loading Condition
decision support system (DSS)
Case Based Reasoning (CBR)
Computer Simulation
Opis:
A ship’s autopilot adjustment is a matter of utmost importance since it affects its safety, command as well as fuel and time efficiency. A number of methods have been developed in order to cope with this issue usually based on models that simulate the weather conditions and adjust the device accordingly. Some of them have a considerable degree of success but none dealt with the problem completely. The main obstacles are the difficulty of simulating the infinite weather and loading conditions and to properly represent them with mathematical equations or rules. This paper describes a method of selecting the best out of a pre-existing set of configurations, taking into account any weather situation, loading condition and type of ship. Moreover, the selected configuration can improve itself during the entire life cycle of the vessel, since it fine tunes its properties for better results. This approach uses Case Based Reasoning as its core technology and is a part of a hybrid system that analyses and solves prefixed problems of maritime interest.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 3; 251-259
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Radar observation of wind farms in various weather conditions
Autorzy:
Stupak, T.
Świerczyński, S.
Wąż, M.
Powiązania:
https://bibliotekanauki.pl/articles/949946.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
marine radars
radar observation
radar
wind farms
weather condition
CARPET 2
ship position
ship position mark
Opis:
This article presents a calculation of condition detection wind farm by ship’s radar. The authors used computer programme CARPET 2 for simulation different propagation condition. Wind farm echoes are visible in significant distance and can be advantage to ship position mark.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2020, 14, 2; 325-329
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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