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On the Al/Cu Dissimilar Joints Produced Through Simple Cold Compression
, Article Transactions of the Indian Institute of Metals ; Volume 68, Issue 5 , October , 2015 , Pages 991-998 ; 09722815 (ISSN) ; Ghasemi, A ; Pouraliakbar, H ; Jandaghi, M. R ; Sharif University of Technology
Springer India
2015
Abstract
Dissimilar Al/Cu joints were produced through simple cold compression technique. The influence of different reductions (40, 53 and 66 %) on the joint strength was studied. Also, the effect of heat treatment on the joints’ mechanical characteristics was investigated using a modified miniature shear test. Microscopical examinations by means of optical and scanning electron microscopes were conducted and results confirmed that acceptable joints produced through 53 and 66 % deformations. According to the shear test results, it was revealed that post-weld heat treatment influenced the joint’s strength and caused strength enhancement in the samples which were not subjected to annealing prior to...
Effects of Static Restoration Phenomena on Microstructure and Mechanical Properties of A286 Superalloy
, M.Sc. Thesis Sharif University of Technology ; Karimi Taheri, Ali (Supervisor) ; Abbasi, Mahdi (Supervisor)
Abstract
In this investigation, effects of static restoration phenomena on microstructure and mechanical properties of A286 superalloy were studied. Therefore, single hit and double hit hot compression and hot rolling with different delay time at temperatures of 1050 and 1100 °C in strain rate of 0.1 and 6 s-1 were applied. In addition, annealing of cold compressed and cold rolled samples with various amounts of strains in temperature range of 1000-1100 °C were performed. Finally the best method for forming of A286 superalloy was proposed.Single hit hot compression test results shows that dynamic recovery and dynamic recrystallization occurred at temperatures of 1050 and 1100 °C respectively....
Flow stress optimization for 304 stainless steel under cold and warm compression by artificial neural network and genetic algorithm
, Article Materials and Design ; Volume 28, Issue 2 , 2007 , Pages 609-615 ; 02613069 (ISSN) ; Madaah Hosseini, H. R ; Bahrami, A ; Sharif University of Technology
Elsevier Ltd
2007
Abstract
Artificial neural network (ANN) and genetic algorithm were used in this study to obtain a relatively high flow stress in compression tests for 304 stainless steel. Cold and warm compression were carried out in a temperature range from 20 to 600 °C, strain-rate from 0.001 to 100 S-1 and a strain range from 0.1 to 0.5. Optimum conditions for each case were obtained experimentally and were evaluated by the ANN model. The ANN model was used as fitness function for genetic algorithm. The results indicated that this combined algorithm offers an effective condition for 304 stainless steel, which avoids flow localization, dynamic strain aging, adiabatic shear deformation and void generation. © 2005...