Temat: natural gas networks - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Application of pipelines made with Thermoflex® technology for natural gas and carbon dioxide transportation
Autorzy:: Włodek, T.
Ławski, Ł.
Powiązania:: https://bibliotekanauki.pl/articles/299241.pdf
Data publikacji:: 2013
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: thermoflex
natural gas transportation
pipelines
CO2
carbon dioxide
CO2 transportation
natural gas networks
new materials
Opis:: The main issue related to pipeline transportation of hydrocarbons (natural gas, oil) and chemical substances (e.g. carbon dioxide) is to get the best transportation efficiency, taking into account economic and technological aspects. The paper presents the possibility of using pipelines made with the Thermoflex® technology for the transportation of natural gas and carbon dioxide. Pipelines made with this technology can be used for transportation of natural gas from wellsites to natural gas mines installations. Thermoflex pipeline time of instalation is shorter compared to steel pipeline, this issue has great significance in the perspective of future exploitation of natural gas from unconventional reservoirs in Poland. Pipes made using this technology with new polymeric materials are characterized by much lower pressure drop along the pipeline compared to the steel pipelines, much higher maximum operating pressure range compared to polyethylene pipes, better thermal insulation compared to steel, high corrosion resistance and lower installation and operating costs. This paper presents the construction of the pipelines made using Thermoflex® technology, possibilities of applications and comparative examples of simulations of pressure drop and temperature for steel pipelines and made with Thermoflex® technology for the transport of natural gas and carbon dioxide.
Źródło:: AGH Drilling, Oil, Gas; 2013, 30, 1; 287-296
2299-4157
2300-7052
Pojawia się w:: AGH Drilling, Oil, Gas
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Reducing pollution levels generated by short sea shipping : use of Bayesian networks to analyse the utilization of liquefied natural gas as an alternative fuel
Autorzy:: Molina Serrano, Beatriz
González Cancelas, Nicoleta
Soler Flores, Francisco
Powiązania:: https://bibliotekanauki.pl/articles/246442.pdf
Data publikacji:: 2019
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Tematy:: Bayesian networks
graph theory
artificial network
European Union
Short Sea Shipping
liquefied natural gas
Opis:: Pollution adjacent to the continent's shores has increased in the last decades, so it has been necessary to establish an energy policy to improve environmental conditions. One of the proposed solution was the search of alternative fuels to the commonly used in Short Sea Shipping to reduce pollution levels in Europe. Studies and researches show that liquefied natural gas could meet the European Union environmental requirements. Even environmental benefits are important; currently there is not significant number of vessels using it as fuel. Moreover, main target of this article is exposing result of a research in which a methodology to establish the most relevant variables in the decision to implement liquefied natural gas in Short Sea Shipping has been development using data mining. A Bayesian network was constructed because this kind of network allows to get graphically the relationships between variables and to determine posteriori values that quantify their contributions to decision-making. Bayesian model has been done using data from some European countries (European Union, Norway and Iceland) and database was generated by 35 variables classified in 5 categories. Main obtained conclusion in this analysis is that variables of transport and international trade and economy and finance are the most relevant in the decision-making process when implementing liquefied natural gas. Even more, it can be stablish that capacity of liquefied natural gas regasification terminals under construction and modal distribution of water cargo transportation continental as the most decisive variables because they are the root nodes in the obtained network.
Źródło:: Journal of KONES; 2019, 26, 1; 147-158
1231-4005
2354-0133
Pojawia się w:: Journal of KONES
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Forecasting of the daily demand for natural gas in rural households using the methods of artificial intelligence. Part I. Forecasting using artificial neural networks
Prognozowanie dobowego zapotrzebowania na gaz ziemny wiejskich gospodarstw domowych przy wykorzystaniu metod sztucznej inteligencji. Cz. 1. Prognozowanie przy wykorzystaniu sztucznych sieci neuronowych
Autorzy:: Nęcka, K.
Trojanowska, M.
Małopolski, J.
Powiązania:: https://bibliotekanauki.pl/articles/334058.pdf
Data publikacji:: 2015
Wydawca:: Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Maszyn Rolniczych
Tematy:: natural gas
short-term forecasts
artificial neural networks
gaz ziemny
prognoza krótkookresowa
sztuczna sieć neuronowa
Opis:: The paper determines daily forecast demands for natural gas using artificial neural networks (MLPs). The influence of net-work structure, the type of activation function and the training process used on the quality of prediction were studied. It was found that the quality of forecasts was highly influenced by the network training algorithm. The smallest errors of the ex-pired forecasts (MAPE 5-6%) were obtained using the BFGS algorithm.
W trakcie badań wyznaczano dobowe prognozy zapotrzebowania na gaz ziemny z wykorzystaniem sztucznych sieci neuronowych MLP. Przebadano wpływ struktury sieci, rodzaju funkcji aktywacji oraz zastosowanego procesu uczenia sieci na jakość predykcji. Stwierdzono, że na jakość prognoz duży wpływ ma algorytm uczenia sieci. Najmniejsze błędy prognoz wygasłych (MAPE rzędu 5-6%) uzyskano stosując algorytm BFGS.
Źródło:: Journal of Research and Applications in Agricultural Engineering; 2015, 60, 2; 62-64
1642-686X
2719-423X
Pojawia się w:: Journal of Research and Applications in Agricultural Engineering
Dostawca treści:: Biblioteka Nauki

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