A356 as matrix and nano SiC as reinforcement material nanocomposites are fabricated in this work. Since nanoparticles tend to agglomerate into large clusters during composite processing, effect of ultrasonic cavitation to avoid agglomeration and clustering of nanoparticles in melts is studied. Cavitation pressure required to be developed by the ultrasonic transducer to disperse reinforcements is evaluated. Uniform distribution of nanoparticles is ascertained by SEM test. EDS analysis reveals that there is no contamination of the fabricated composite. Fabricated nanocomposites are then machined into tensile, wear test specimens of dimensions according to ASTM standards. Mechanical properties like tensile strength, hardness, ductility, sliding wear resistance are evaluated and compared with pure aluminum alloy. Machinability and electrical conductivity also evaluated. In the present work, an attempt has been made to confirm the applicability of ANN techniques for prediction of wear of MMNCs by comparing the results of ANN with the experimental results. In addition to the above prediction model, yield strength results are validated using an analytical model.
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Prof.D.Suneel, a distinguished academician and a seasoned Mechanical Professor is the Head of the Mechanical Department and Dean Academics in Narasaraopeta Engineering College, Narasaraopet. He received his Doctorate Degree from Andhra University, Visakhapatnam, INDIA in the year 2010.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A356 as matrix and nano SiC as reinforcement material nanocomposites are fabricated in this work. Since nanoparticles tend to agglomerate into large clusters during composite processing, effect of ultrasonic cavitation to avoid agglomeration and clustering of nanoparticles in melts is studied. Cavitation pressure required to be developed by the ultrasonic transducer to disperse reinforcements is evaluated. Uniform distribution of nanoparticles is ascertained by SEM test. EDS analysis reveals that there is no contamination of the fabricated composite. Fabricated nanocomposites are then machined into tensile, wear test specimens of dimensions according to ASTM standards. Mechanical properties like tensile strength, hardness, ductility, sliding wear resistance are evaluated and compared with pure aluminum alloy. Machinability and electrical conductivity also evaluated. In the present work, an attempt has been made to confirm the applicability of ANN techniques for prediction of wear of MMNCs by comparing the results of ANN with the experimental results. In addition to the above prediction model, yield strength results are validated using an analytical model. 160 pp. Englisch. Bestandsnummer des Verkäufers 9786139963515
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Donthamsetty SuneelProf.D.Suneel, a distinguished academician and a seasoned Mechanical Professor is the Head of the Mechanical Department and Dean Academics in Narasaraopeta Engineering College, Narasaraopet. He received his Doctora. Bestandsnummer des Verkäufers 261127933
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A356 as matrix and nano SiC as reinforcement material nanocomposites are fabricated in this work. Since nanoparticles tend to agglomerate into large clusters during composite processing, effect of ultrasonic cavitation to avoid agglomeration and clustering of nanoparticles in melts is studied. Cavitation pressure required to be developed by the ultrasonic transducer to disperse reinforcements is evaluated. Uniform distribution of nanoparticles is ascertained by SEM test. EDS analysis reveals that there is no contamination of the fabricated composite. Fabricated nanocomposites are then machined into tensile, wear test specimens of dimensions according to ASTM standards. Mechanical properties like tensile strength, hardness, ductility, sliding wear resistance are evaluated and compared with pure aluminum alloy. Machinability and electrical conductivity also evaluated. In the present work, an attempt has been made to confirm the applicability of ANN techniques for prediction of wear of MMNCs by comparing the results of ANN with the experimental results. In addition to the above prediction model, yield strength results are validated using an analytical model. Bestandsnummer des Verkäufers 9786139963515
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Taschenbuch. Zustand: Neu. Synthesis & Characterization of Metal Matrix Nanocompsites | With Ultrasonic Cavitation Assisted Dispersion of SiC Nanoparticles in A356 alloy | Suneel Donthamsetty | Taschenbuch | 160 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139963515 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 115129962
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A356 as matrix and nano SiC as reinforcement material nanocomposites are fabricated in this work. Since nanoparticles tend to agglomerate into large clusters during composite processing, effect of ultrasonic cavitation to avoid agglomeration and clustering of nanoparticles in melts is studied. Cavitation pressure required to be developed by the ultrasonic transducer to disperse reinforcements is evaluated. Uniform distribution of nanoparticles is ascertained by SEM test. EDS analysis reveals that there is no contamination of the fabricated composite. Fabricated nanocomposites are then machined into tensile, wear test specimens of dimensions according to ASTM standards. Mechanical properties like tensile strength, hardness, ductility, sliding wear resistance are evaluated and compared with pure aluminum alloy. Machinability and electrical conductivity also evaluated. In the present work, an attempt has been made to confirm the applicability of ANN techniques for prediction of wear of MMNCs by comparing the results of ANN with the experimental results. In addition to the above prediction model, yield strength results are validated using an analytical model.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 160 pp. Englisch. Bestandsnummer des Verkäufers 9786139963515
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