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    Wyświetlanie 1-3 z 3
    Tytuł:
    Radon intercomparison tests : Katowice, 2016
    Autorzy:
    Chałupnik, Stanisław
    Skubacz, Krystian
    Wysocka, Małgorzata
    Mazur, Jadwiga
    Bonczyk, Michał
    Kozak, Krzysztof
    Grządziel, Dominika
    Urban, Paweł
    Tchorz-Trzeciakiewicz, D.
    Kozłowska, Beata
    Walencik-Łata, Agata
    Podstawczyńska, Agnieszka
    Olszewski, Jerzy
    Bartak, Jakub
    Karpińska, Maria
    Wołoszczuk, Katarzyna
    Dohojda, Marek
    Nowak, Jakub
    Długosz-Lisiecka, Magdalena
    Foerster, Elisabeth
    Przylibski, Tadeusz A.
    Powiązania:
    https://bibliotekanauki.pl/articles/146183.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Chemii i Techniki Jądrowej
    Tematy:
    active monitors
    passive monitors
    Polish Radon Centre
    proficiency test
    radon
    Opis:
    At the beginning of the year 2016, the representatives of the Polish Radon Centre decided to organize proficiency tests (PTs) for measurements of radon gas and radon decay products in the air, involving radon monitors and laboratory passive techniques. The Silesian Centre for Environmental Radioactivity of the Central Mining Institute (GIG), Katowice, became responsible for the organization of the PT exercises. The main reason to choose that location was the radon chamber in GIG with a volume of 17 m3 , the biggest one in Poland. Accordingly, 13 participants from Poland plus one participant from Germany expressed their interest. The participants were invited to inform the organizers about what types of monitors and methods they would like to check during the tests. On this basis, the GIG team prepared the proposal for the schedule of exercises, such as the required level(s) of radon concentrations, the number and periods of tests, proposed potential alpha energy concentration (PAEC) levels and also the overall period of PT. The PT activity was performed between 6th and 17th June 2016. After assessment of the results, the agreement between radon monitors and other measurement methods was confirmed. In the case of PAEC monitors and methods of measurements, the results of PT exercises were consistent and confirmed the accuracy of the calibration procedures used by the participants. The results of the PAEC PTs will be published elsewhere; in this paper, only the results of radon intercomparison are described.
    Źródło:
    Nukleonika; 2020, 65, 2; 127-132
    0029-5922
    1508-5791
    Pojawia się w:
    Nukleonika
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    National comparison of methods for determination of radon in water
    Autorzy:
    Mazur, Jadwiga
    Kozak, Krzysztof
    Grządziel, Dominik
    Guguła, Szymon
    Mroczek, Mariusz
    Kozłowska, Beata
    Walencik-Łata, Agata
    Podgórska, Zuzanna
    Wołoszczuk, Katarzyna
    Przylibski, Tadeusz A.
    Kowalska, Agata
    Domin, Elżbieta
    Wysocka, Małgorzata
    Chałupnik, Stanisław
    Chmielewska, Izabela
    Długosz-Lisiecka, Magdalena
    Szajerski, Piotr
    Chau, Nguyen Dinh
    Krakowska, Paulina
    Pliszczyński, Tomasz
    Ośko, Jakub
    Dymecka, Małgorzata
    Mazurek, Daria
    Powiązania:
    https://bibliotekanauki.pl/articles/148272.pdf
    Data publikacji:
    2020
    Wydawca:
    Instytut Chemii i Techniki Jądrowej
    Tematy:
    AlphaGUARD monitor
    interlaboratory comparison
    LSC method
    radon in water
    Z-score value
    Opis:
    The article describes three interlaboratory experiments concerning 222Rn determination in water samples. The first two experiments were carried out with the use of artificial radon waters prepared by the Laboratory of Radiometric Expertise (LER), Institute of Nuclear Physics, Polish Academy of Sciences in Kraków in 2014 and 2018. The third experiment was performed using natural environment waters collected in the vicinity of the former uranium mine in Kowary in 2016. Most of the institutions performing radon in water measurements in Poland were gathered in the Polish Radon Centre Network, and they participated in the experiments. The goal of these exercises was to evaluate different measurement techniques used routinely in Polish laboratories and the laboratories’ proficiency of radon in water measurements. In the experiment performed in 2018, the reference values of 222Rn concentration in water were calculated based on the method developed at LER. The participants’ results appeared to be worse for low radon concentration than for high radon concentrations. The conclusions drawn on that base indicated the weaknesses of the used methods and probably the sampling. The interlaboratory experiments, in term, can help to improve the participants’ skills and reliability of their results.
    Źródło:
    Nukleonika; 2020, 65, 2; 77-81
    0029-5922
    1508-5791
    Pojawia się w:
    Nukleonika
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Using Artificial Neural Networks for predicting ship fuel consumption
    Autorzy:
    Nguyen, Van Giao
    Sakthivel, Rajamohan
    Rudzik, Krzysztof
    Kozak, Janusz
    Sharma, Prabhakar
    Pham, Nguyen Dang Khoa
    Nguyen, Phuoc Quy Phong
    Nguyen, Xuan Phuong
    Powiązania:
    https://bibliotekanauki.pl/articles/32918813.pdf
    Data publikacji:
    2023
    Wydawca:
    Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
    Tematy:
    artificial neural network
    fuel management
    marine engine
    ship fuel consumption
    energy efficiencys
    Opis:
    In marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types of ships. Most traditional statistical methods do not consider these factors when predicting marine vessel fuel consumption. With technological development, different statistical models have been developed for estimating fuel consumption patterns based on ship data. Artificial Neural Networks (ANN) are some of the most effective artificial methods for modelling and validating marine vessel fuel consumption. The application of ANN in maritime transport improves the accuracy of the regression models developed for analysing interactive relationships between various factors. The present review sheds light on consolidating the works carried out in predicting ship fuel consumption using ANN, with an emphasis on topics such as ANN structure, application and prediction algorithms. Future research directions are also proposed and the present review can be a benchmark for mathematical modelling of ship fuel consumption using ANN.
    Źródło:
    Polish Maritime Research; 2023, 2; 39-60
    1233-2585
    Pojawia się w:
    Polish Maritime Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-3 z 3

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