Zobrazeno 1 - 10
of 1 404
pro vyhledávání: '"PEMs"'
Publikováno v:
Frontiers in Big Data, Vol 7 (2024)
This paper aims to evaluate the driving style effects, through the construction of driving cycles, on the polluting gases, in the context of urban freight transportation. For this, the method used was the construction of cycles through the Vehicle Sp
Externí odkaz:
https://doaj.org/article/11097a2cb80b41e9b44c6676792de817
Publikováno v:
Energies, Vol 17, Iss 21, p 5247 (2024)
From the collected data of the Central Register of Vehicles, an average of 15,000 vehicles were registered per month in the Greater Poland region in 2020–2022. It should be borne in mind that most of them were conventionally powered cars-spark-igni
Externí odkaz:
https://doaj.org/article/85f63f21d5724f58bb82110e45031d92
Autor:
Fayaz Ahmad Doobi, Fasil Qayoom Mir
Publikováno v:
Results in Surfaces and Interfaces, Vol 15, Iss , Pp 100218- (2024)
Fuel cells use proton exchange membranes (PEMs) to transform chemical energy into electricity. PEMs are selective barriers that permeates protons, obstructing gases and other species like electrons. A polymer electrolyte containing both positively an
Externí odkaz:
https://doaj.org/article/5c845f3b41b1450ea874faa8c9a13378
Publikováno v:
Atmosphere, Vol 15, Iss 8, p 956 (2024)
Diesel pallet trucks, a type of heavy-duty diesel trucks (HDDTs), have historically been a vital component in logistics and transport due to their high payload capacity. However, they also present significant challenges, particularly in terms of emis
Externí odkaz:
https://doaj.org/article/35fea863eab9443fbf9fdb60e9f7441d
Publikováno v:
Energies, Vol 17, Iss 14, p 3373 (2024)
Off-road machinery is one of the significant contributors to air pollution due to its large quantity. In this study, a deep learning model was developed to predict the transient engine emissions of CO, NO, NO2, and NOx, which are the main pollutants
Externí odkaz:
https://doaj.org/article/e0bfa0045ddc4207bbb28ea50bd7809a
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 5, Iss 3, Pp 1055-1075 (2023)
Predicting emissions for gas turbines is critical for monitoring harmful pollutants being released into the atmosphere. In this study, we evaluate the performance of machine learning models for predicting emissions for gas turbines. We compared an ex
Externí odkaz:
https://doaj.org/article/c60dbc9874b34e8eb8f721076c1f8ac7
Autor:
Felipe S. Frutuoso, Camila M.A.C. Alves, Saul L. Araújo, Daniel S. Serra, Ana Luiza B.P. Barros, Francisco S.Á. Cavalcante, Rinaldo S. Araújo, Nara A. Policarpo, Mona Lisa M. Oliveira
Publikováno v:
International Journal of Transportation Science and Technology, Vol 12, Iss 2, Pp 447-459 (2023)
Brazil is the 9th largest producer of vehicles in the world, with 62.7% of the global fleet of Flex-Fuel Vehicles (FFVs). These vehicles used in Brazil operate with E27 (anhydrous ethanol used for gasohol blending) or E100 hydrous ethanol or any blen
Externí odkaz:
https://doaj.org/article/7d2a712ecc244acca4c469d830086755
Autor:
Maksymilian Mądziel
Publikováno v:
Energies, Vol 17, Iss 12, p 2815 (2024)
Creating accurate emission models capable of capturing the variability and dynamics of modern propulsion systems is crucial for future mobility planning. This paper presents a methodology for creating THC and NOx emission models for vehicles equipped
Externí odkaz:
https://doaj.org/article/175c2c96c07b48e8a20c8bf1c48a02e0
Autor:
Maksymilian Mądziel
Publikováno v:
Energies, Vol 17, Iss 8, p 1850 (2024)
In response to increasingly stringent global environmental policies, this study addresses the pressing need for accurate prediction models of CO2 emissions from vehicles powered by alternative fuels, such as compressed natural gas (CNG). Through expe
Externí odkaz:
https://doaj.org/article/32c4488710d84a66b044699a13d286bb
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