Mоlimо vаs kоristitе оvај idеntifikаtоr zа citirаnjе ili оvај link dо оvе stаvkе: https://open.uns.ac.rs/handle/123456789/9928
Nаziv: Modeling approach for determination of backward extrusion strain energy on AlCu5PbBi
Аutоri: Barisic B.
Grizelj B.
Plancak M.
Dаtum izdаvаnjа: 27-мар-2008
Čаsоpis: Key Engineering Materials
Sažetak: In the paper, firstly on the basis of different theoretical methods and by means of different strain determining criteria the analytic modeling of backward extrusion process was done. Analyzed analytical models are derived directly from the mathematical description of the backward extrusion physical phenomena and their mathematical description has been presented. Afterwards, numerical modeling of strain energy by means of ABAQUS 6.4.1. software [1] was done. Also, stochastic modeling, founded on the statistic processing of experimental data according to the mathematical theory of experimental design, has been examined. For establishing of process strain energy, the second order stochastic model has been introduced. Analytic, numerical and stochastic research and experiments were performed according to central composite design (type CCC). As industrial case, the material AlCu5Pb Bi was chosen. The power law which describes material compression properties is obtained as kf = 334.33 · φ0.192. The extrusion strain energy is dependent on the change in section size, friction coefficient, and material properties. Because of that, these parameters were varied variables at the all points of CCC design. The diameter of workpiece used in this design was set predetermined as industrial case, but both coefficient of friction and wall thickness of workpiece has been varied according to experimental design. The best results in modeling were derived by means of stochastic modeling, and the best strain energy model in the form W = -1111.82 - 88.7 · μ - 3200 · μ2 + 625 · μ · s + 816.43 · s - 42.25 · s2 has been obtained.
URI: https://open.uns.ac.rs/handle/123456789/9928
ISSN: 10139826
DOI: 10.4028/0-87849-467-7.221
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