Zobrazeno 1 - 10 of 21 pro vyhledávání: '"Peter B. Samuels"'
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Akademický článek
Energy Consumption and Greenhouse Gas Emissions of Nickel Products
Autor: Wenjing Wei, Peter B. Samuelsson, Anders Tilliander, Rutger Gyllenram, Pär G. Jönsson
Publikováno v: Energies, Vol 13, Iss 21, p 5664 (2020)
The primary energy consumption and greenhouse gas emissions from nickel smelting products have been assessed through case studies using a process model based on mass and energy balance. The required primary energy for producing nickel metal, nickel o
Externí odkaz: https://doaj.org/article/b746d61d2a234cecaaf599618cda06fd
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6
Diagnosis and management of arterial mural thromboemboli
Autor: Peter B. Samuels, David J. Katz
Publikováno v: The American Journal of Surgery. 134:209-213
Twelve cases are presented in which peripheral or cerebral ischemia without obvious cause was the presenting complaint. Aneurysm or stenosing or ulcerative plaques were the underlying lesion in the arterial tree. Peripheral ischemia in the presence o
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a85ff6c2540cc83def75de3a011e851
https://doi.org/10.1016/0002-9610(77)90346-4
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9
Akademický článek
Using Statistical Modeling to Predict the Electrical Energy Consumption of an Electric Arc Furnace Producing Stainless Steel
Autor: Leo S. Carlsson, Peter B. Samuelsson, Pär G. Jönsson
Publikováno v: Metals, Vol 10, Iss 1, p 36 (2019)
The non-linearity of the Electric Arc Furnace (EAF) process and the correlative behavior between the process variables impose challenges that have to be considered if one aims to create a statistical model that is relevant and useful in practice. In
Externí odkaz: https://doaj.org/article/d4f35e6a44f14784a00468d3e6820b6a
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10
Akademický článek
Predicting the Electrical Energy Consumption of Electric Arc Furnaces Using Statistical Modeling
Autor: Leo S. Carlsson, Peter B. Samuelsson, Pär G. Jönsson
Publikováno v: Metals, Vol 9, Iss 9, p 959 (2019)
Statistical modeling, also known as machine learning, has gained increased attention in part due to the Industry 4.0 development. However, a review of the statistical models within the scope of steel processes has not previously been conducted. This
Externí odkaz: https://doaj.org/article/98603dc823514913ada763dd191586a8
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