چكيده به لاتين
Abstract: In this research, the kinetics of post severe plastic deformation (SPD) annealing of Sn-5Sb solder alloy was modeled using an integrated finite element – Monte Carlo (MC) simulation. The induction of large staining was performed by equal channel angular pressing technique known as ECAP. During Process, samples were extruded within two intercepted channel with identical cross-sectional area and due to pure shear, a considerable plastic strain stored in the fine-grained pressed metal sample. Deformed samples were then annealed in different temperatures and just after that, quenched for retaining achieved microstructure and further microstructural examinations. By means of proposed method of the current research, it is possible to estimate the fraction of annealed sample, its related kinetics and mechanism and finally energy transfer mode during post SPD heating. Primarily, the hot deformation behavior and processing map of studied alloy by performing hot compression test and deriving constitutive equations. Then flow behavior of alloy was modeled by adaptive neuro-fuzzy inference system (ANFIS) for linking the deformation factors to flow stress of the solder. The materials constant for Johnson-Cook (J-C) plasticity material model was identified by implementing a hybrid inverse modeling technique and imperialist competitive algorithm and consequently the performance of all three constitutive, J-C and ANFIS approaches were compared with each other. Next, the finite element analysis was used to obtain the stress and strain contour of as-ECAPed samples and again an intelligent approach was utilized for establishment of different affecting parameters and desired state variables of ECAP. Consequently, by taking the initial microstructure into account, MC modeling was implemented to depict the recrystallization trend of alloy during post SPD annealing and final microstructure get simulated in any temperature. The effect of various involved parameters such as heterogeneous distribution of deformation stored energy, initial grain size and second phase presence was taken into consideration in the research work. The Sn-5Sb material was annealed in different temperatures posterior to severe deformation and after that, studied with microstructural and metallographic approach to be used as a validation and comparison with graphical output of Mc model. In the study, the approach based on statistical mechanics and minimum energy tendency rules were used to investigate the nucleation and growth mechanism and also final achieved microstructure of the alloy after heating. In this regard, the significant purpose of the work was to link a proper connection with stress- strain distribution as output of finite element method with state variable that can be further utilized as inputs of MC for microstructural evolution simulation.
Keywords: Sn-Sb alloy, Hot deformation, Equal channel anglar pressing, Monte Carlo, Artificial intelligence
