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	Provedor de dados CIGR Journal (2) Autor Alimardani, Reza (1) Azadbakht, Mohsen (1) Ghajarjazi, Ehsan (1) Jafary, Ali (1) Taghinezhad, Javad (1) Torshizi, Mohammad Vahedi (1) Ziaratban, Armin (1) Mais... Palavra-chave Cutting energy (2) Artificial Neural Network (ANN) (1) Canola (1) Mechanical cutting (1) Moisture content (1) Multiple regression (1) Power consumption (1) Shear strength (1) Stem (1) Sugarcane stalk (1) Ultimate stress (1) Mais... Tipo do documento Info:eu-repo/semantics/article (2) Ano 2016 (1) 2014 (1) País China (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última Application of Artificial Neural Network (ANN) in predicting mechanical properties of canola stem under shear loading CIGR Journal Azadbakht, Mohsen; Torshizi, Mohammad Vahedi; Ziaratban, Armin; Ghajarjazi, Ehsan. In this study, at first the shear parameters including the maximum shear force, shear strength, shear energy and power consumption of canola stem were calculated through force-deformation curve; and then these mechanical properties were determined and predicted using artificial neural network.   For the tests, testing machine Instron (Model Santam STM-5) with 50 N load cell was used.  Stems were cut at 3 diameter levels (1 to 3, 3 to 5 and more than 5 mm), 3 cutting speed levels (75, 115 and 150 mm/min ), 3 cutting angles (0°, 30° and 60°) and three replicates.   Cutting parameters including maximum cutting force, shear strength; cutting energy; consumed power and cutting work were examined.  Tests lasted for each stem until the full cut.  Data... Tipo: Info:eu-repo/semantics/article Palavras-chave: Canola; Cutting energy; Stem; Shear strength; Power consumption; Artificial Neural Network (ANN). Ano: 2016 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/3785 Models of mechanical cutting parameters in terms of moisture content and cross section area of sugarcane stalks CIGR Journal Taghinezhad, Javad; Alimardani, Reza; Jafary, Ali. The objective of this study was to find optimizing moisture content and cutting area of sugarcane stalk cutting parameters using multiple regressions and to verify the optimum levels of the variables.  The effect of moisture content and cutting section area on mechanical cutting properties of sugarcane stalks was studied using a linear blade cutting and UTM (Universal Testing Machine) size reduction device.  Data obtained in the laboratory were divided into four different groups in order to determine the peak force, cutting energy, ultimate stress and specific energy.  Additional criterions were also proposed and used as an indicator of the cutting performance.  These were the marginal cutting parameter (MCP) and return to scale (RTS).  The data obtained... Tipo: Info:eu-repo/semantics/article Palavras-chave: Mechanical cutting; Moisture content; Sugarcane stalk; Ultimate stress; Cutting energy; Multiple regression. Ano: 2014 URL: http://www.cigrjournal.org/index.php/Ejounral/article/view/2579 Registros recuperados: 2 Primeira ... 1 ... Última

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