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Numerical Simulation Of The Continuous Drive Friction Welding Deformation Process Of30CrNi4MoA

Posted on:2013-01-31Degree:MasterType:Thesis
Country:ChinaCandidate:S S ZhangFull Text:PDF
GTID:2231330374972912Subject:Mechanical Manufacturing and Automation
Abstract/Summary:PDF Full Text Request
Continue drive friction welding is a solid-state joining process, heat in the friction welding is generated by conversion of mechanical energy into thermal energy at interface of the work pieces during rotation under pressure. The friction surface temperature near and reach the thermoplastic state, under the combined action of pressure and heat welding jiont was formed. Now-days friction welding is widespread used in various industries.The temperature field and stress-strain fields during welding process are important factors that significantly affect on the mechanical properties and microstructure in weld joint. The welding process is a non-liner process because of the interaction between temperature field and material properties as well as friction force and thrust force.A thermo-mechanical coupled finite element model of30CrNi4MoA ring was established to simulate the temperature field and stress-strain fields of this process. By using FEM analysis software ABAQUS the temperature field and stress-strain field as well as the upset shorting were calculated. The factors that affect on the upset shorting are also discussedTo verify the FE models, the calculate data and joint shape of axial shorting were compared to the measured ones.they were shown in good agreement respectively. So we can conclude that the FE models were valid and the calculated results were reliable.Established prediction system of Axial shortening using matlab neural network toolbox, the prediction model has good generalization ability. Discussed the process parameters impact on the axial shortening obtained by the prediction system and the results consistent with the conclusion from. finite element simulation.
Keywords/Search Tags:finite element, continue drive friction welding, neural network, axial shortening
PDF Full Text Request
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