9786139994922 - Effect of Specimen Geometry on Torsion Test Results de Patil, Rajkumar; Gore, Purushottam (7 resultados)

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Taschenbuch. Condición: Sehr gut. Gebraucht - Sehr gut SG - leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - The objective of present research is to study the effect of different specimen dimensions on the modulus of rigidity, yield shear stress and ultimate shear stress for AISI 1020 steel and Al T6 6061. The experiments are conducted with key specimen dimensions such as total length, outer diameter, inner diameter, useful length and fillet radius at different levels for solid and hollow specimens. The Taguchi parameter design and optimization approach is used for Design of Experiment and subsequently to predict sets of optimal parameters. The Grey Relational Analysis (GRA) method has been used for multi-objective optimization.

Taschenbuch. Condición: Neu. Effect of Specimen Geometry on Torsion Test Results | Rajkumar Patil (u. a.) | Taschenbuch | 116 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786139994922 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | The objective of present research is to study the effect of different specimen dimensions on the modulus of rigidity, yield shear stress and ultimate shear stress for AISI 1020 steel and Al T6 6061. The experiments are conducted with key specimen dimensions such as total length, outer diameter, inner diameter, useful length and fillet radius at different levels for solid and hollow specimens. The Taguchi parameter design and optimization approach is used for Design of Experiment and subsequently to predict sets of optimal parameters. The Grey Relational Analysis (GRA) method has been used for multi-objective optimization.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The objective of present research is to study the effect of different specimen dimensions on the modulus of rigidity, yield shear stress and ultimate shear stress for AISI 1020 steel and Al T6 6061. The experiments are conducted with key specimen dimensions such as total length, outer diameter, inner diameter, useful length and fillet radius at different levels for solid and hollow specimens. The Taguchi parameter design and optimization approach is used for Design of Experiment and subsequently to predict sets of optimal parameters. The Grey Relational Analysis (GRA) method has been used for multi-objective optimization. 116 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The objective of present research is to study the effect of different specimen dimensions on the modulus of rigidity, yield shear stress and ultimate shear stress for AISI 1020 steel and Al T6 6061. The experiments are conducted with key specimen dimensions such as total length, outer diameter, inner diameter, useful length and fillet radius at different levels for solid and hollow specimens. The Taguchi parameter design and optimization approach is used for Design of Experiment and subsequently to predict sets of optimal parameters. The Grey Relational Analysis (GRA) method has been used for multi-objective optimization.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The objective of present research is to study the effect of different specimen dimensions on the modulus of rigidity, yield shear stress and ultimate shear stress for AISI 1020 steel and Al T6 6061. The experiments are conducted with key specimen dimensions such as total length, outer diameter, inner diameter, useful length and fillet radius at different levels for solid and hollow specimens. The Taguchi parameter design and optimization approach is used for Design of Experiment and subsequently to predict sets of optimal parameters. The Grey Relational Analysis (GRA) method has been used for multi-objective optimization.