Amit Rana, Sandeep Deshwal, Rajesh and Naveen Hooda
The weld joint mechanical properties of friction stir welding (FSW) are majorly reliant on different input parameters of the FSW machine. The study and optmization of these…
Abstract
Purpose
The weld joint mechanical properties of friction stir welding (FSW) are majorly reliant on different input parameters of the FSW machine. The study and optmization of these parameters is uttermost requirement and aim of this study to increase the suitability of FSW in different manufacturing industries. Hence, the input parameters are optimized through different soft computing methods to increase the considered objective in this study.
Design/methodology/approach
In this research, ultimate tensile strength (UTS), yield strength (YS) and elongation (EL) of FSW prepared butt joints of AA6061 and AA5083 Aluminium alloys materials are investigated as per American Society for Testing and Materials (ASTM E8-M04) standard. The FSW joints were prepared by changing the three input process parameters. To develop experimental run order design matrix, rotatable central composite design strategy was used. Furthermore, genetic algorithm (GA) in combination (Hybrid) with response surface methodology (RSM), artificial neural network (ANN), i.e. RSM-GA, ANN-GA, is exercised to optimize the considered process parameters.
Findings
The maximum value of UTS, YS and EL of test specimens on universal testing machine was measured as 264 MPa, 204 MPa and 14.41%, respectively. The most optimized results (UTS = 269.544 MPa, YS = 211.121 MPa and EL = 17.127%) are obtained with ANN-GA for the considered objectives.
Originality/value
The optimization of input parameters to increase the output objective values using hybrid soft computing techniques is unique in this research paper. The outcomes of this study will help the FSW using manufacturing industries to choose the best optimized parameters set for FSW prepared butt joint with improved mechanical properties.
Details
Keywords
Santosh Chaudhary and Jyoti Deshwal
This study is to examine the impact of viscous dissipation, thermal radiation and Ohmic heating on the magnetohydrodynamic (MHD) flow with thermal and mass transport over a…
Abstract
Purpose
This study is to examine the impact of viscous dissipation, thermal radiation and Ohmic heating on the magnetohydrodynamic (MHD) flow with thermal and mass transport over a horizontally stretching surface. Cattaneo–Christov heat flux model on a non-Newtonian viscous fluid along with two viscosity models and convective boundary condition has been employed. Tri-hybrid nanofluid has been used to increase thermal performance.
Design/methodology/approach
Governing mathematical model has been transposed into a dimensionless system of ordinary differential equations (ODEs) by applying suitable similarity transformation. Numerical solution has been found by applying the bvp4c shooting method in MATLAB software.
Findings
Velocity and thermal profiles of Model-I dominate the profiles of Model-II whereas opposite behavior is noticed for concentration profiles. It is concluded that there is an increase in temperature due to thermal radiation, viscous dissipation and convective boundary condition.
Originality/value
The novelty of presented work is to examine the impact of Ohmic heating, viscous dissipation, thermal radiation, chemical reaction and two models of viscosity on Cattaneo–Christov heat flux model of tri-hybrid non-Newtonian nanofluid with convective boundary constraint. The accuracy and effectiveness of presented model have been compared with already published research.