Characterization of the tensile properties of friction stir welded aluminum alloy joints based on axial force, traverse speed, and rotational speed

[1]  A. Heidarzadeh,et al.  Correlation between process parameters, grain size and hardness of friction-stir-welded Cu–Zn alloys , 2018, Rare Metals.

[2]  A. Heidarzadeh,et al.  Effect of friction stir welding on microstructure and mechanical properties of dissimilar Al 5083-H321 and 316L stainless steel alloy joints , 2016 .

[3]  Sylvie Castagne,et al.  Sustainable manufacturing models for mass finishing process , 2016 .

[4]  Reza Vatankhah Barenji,et al.  Influence of heat input conditions on microstructure evolution and mechanical properties of friction stir welded pure copper joints , 2016, Transactions of the Indian Institute of Metals.

[5]  Dongya Zhao,et al.  A new stepwise and piecewise optimization approach for CO2 pipeline , 2016 .

[6]  Sylvie Castagne,et al.  Computational model for predicting the effect of process parameters on surface characteristics of mass finished components , 2016 .

[7]  A. Heidarzadeh,et al.  Dissimilar butt friction stir welding of Al 5083-H321 and 316L stainless steel alloys , 2016 .

[8]  Reza Vatankhah Barenji,et al.  Effect of tool traverse speed on microstructure and mechanical performance of friction stir welded 7020 aluminum alloy , 2016 .

[9]  Akhil Garg,et al.  Investigation of the joint length of weldment of environmental-friendly magnetic pulse welding process , 2016 .

[10]  Abazar Asghari,et al.  Ductility reduction factor and collapse mechanism evaluation of a new steel knee braced frame , 2016 .

[11]  Aydin Azizi,et al.  Microstructure and mechanical properties of friction stir welded thick pure copper plates , 2016 .

[12]  Liang Gao,et al.  Energy conservation in manufacturing operations: modelling the milling process by a new complexity-based evolutionary approach , 2015 .

[13]  A. Heidarzadeh,et al.  On the effect of β phase on the microstructure and mechanical properties of friction stir welded commercial brass alloys , 2015, Data in brief.

[14]  V. Sharma,et al.  Surface composites by friction stir processing: A review , 2015 .

[15]  M. V. A. Raju Bahubalendruni,et al.  A general regression neural network approach for the evaluation of compressive strength of FDM prototypes , 2015, Neural Computing and Applications.

[16]  A. Gandomi,et al.  New design equations for elastic modulus of concrete using multi expression programming , 2015 .

[17]  R. V. Barenji,et al.  Elucidating of tool rotational speed in friction stir welding of 7020-T6 aluminum alloy , 2015 .

[18]  Jasmine Siu Lee Lam,et al.  Process characterisation of 3D-printed FDM components using improved evolutionary computational approach , 2015 .

[19]  Masoud Jabbari,et al.  Prediction of grain size and mechanical properties in friction stir welded pure copper joints using a thermal model , 2015 .

[20]  Reza Vatankhah Barenji,et al.  Tensile Properties of Friction Stir Welds of AA 7020 Aluminum Alloy , 2015, Transactions of the Indian Institute of Metals.

[21]  K. Tai,et al.  An integrated computational approach for determining the elastic properties of boron nitride nanotubes , 2014, International Journal of Mechanics and Materials in Design.

[22]  Dongya Zhao,et al.  Terminal sliding mode control for continuous stirred tank reactor , 2015 .

[23]  G. Hussain,et al.  Establishing Mathematical Models to Predict Grain Size and Hardness of the Friction Stir-Welded AA 7020 Aluminum Alloy Joints , 2015, Metallurgical and Materials Transactions B.

[24]  Akhil Garg,et al.  Combined CI-MD approach in formulation of engineering moduli of single layer graphene sheet , 2014, Simul. Model. Pract. Theory.

[25]  Quanmin Zhu,et al.  A framework of neural networks based consensus control for multiple robotic manipulators , 2014, Neurocomputing.

[26]  Akhil Garg,et al.  An embedded simulation approach for modeling the thermal conductivity of 2D nanoscale material , 2014, Simul. Model. Pract. Theory.

[27]  E. Nazari,et al.  Establishing a Mathematical Model to Predict the Tensile Strength of Friction Stir Welded Pure Copper Joints , 2013, Metallurgical and Materials Transactions B.

[28]  A. Garg,et al.  Comparison of regression analysis, Artificial Neural Network and genetic programming in Handling the multicollinearity problem , 2012, 2012 Proceedings of International Conference on Modelling, Identification and Control.

[29]  E. Nazari,et al.  Tensile behavior of friction stir welded AA 6061-T4 aluminum alloy joints , 2012 .

[30]  E. Nazari,et al.  Effect of friction stir welding (FSW) parameters on strain hardening behavior of pure copper joints , 2012 .

[31]  Chee How Wong,et al.  Nanomechanics of imperfectly straight single walled carbon nanotubes under axial compression by using molecular dynamics simulation , 2012 .

[32]  C. Muralidharan,et al.  Establishing Empirical Relationships to Predict Grain Size and Tensile Strength of Friction Stir Welded AA 6061-T6 Aluminium Alloy Joints , 2010 .

[33]  V. Balasubramanian,et al.  Optimizing friction stir welding parameters to maximize tensile strength of AA2219 aluminum alloy joints , 2009 .

[34]  V. Balasubramanian,et al.  Comparison of RSM with ANN in predicting tensile strength of friction stir welded AA7039 aluminium alloy joints , 2009 .

[35]  A. Heidarzadeh,et al.  A comparative study of microstructure and mechanical properties between friction stir welded single and double phase brass alloys , 2016 .

[36]  Bibhuti Bhusan Biswal,et al.  Application of Artificial Intelligence Methods to Spot Welding of Commercial Aluminum Sheets (B.S. 1050) , 2014, SocProS.

[37]  M. Azadbeh,et al.  Densification and volumetric change during supersolidus liquid phase sintering of prealloyed brass Cu28Zn powder: Modeling and optimization , 2014 .

[38]  C. H. Wong,et al.  Torsional Characteristics of Single Walled Carbon Nanotube with Water Interactions by Using Molecular Dynamics Simulation , 2014 .

[39]  Quanmin Zhu,et al.  Synchronized control with neuro-agents for leader-follower based multiple robotic manipulators , 2014, Neurocomputing.

[40]  Bibhuti Bhusan Biswal,et al.  Comparative Evaluation of Optimization Algorithms at Training of Genetic Programming for Tensile Strength Prediction of FDM Processed Part , 2014 .

[41]  Dominic P. Searson,et al.  GPTIPS: An Open Source Genetic Programming Toolbox For Multigene Symbolic Regression , 2010 .

[42]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.