Effect of Plasma Arc Welding on Residual Stress and Distortion of Thin Titanium Sheet

In this research work, a finite element model is developed to predict the temperature field and residual stress during plasma arc welding of thin Ti-6Al-4V sheets. Dhinakaran’s heat source model which is based on Parabolic Gaussian distribution is used to predict the temperature field and Anand’s model is used to predict the residual stress. Numerical simulation is performed using ANSYS®. Heat transfer analysis is carried out primarily and the temperature field is given as the input for structural analysis. The concept of APDL programming is used to implement the governing equations. Experimental work has also been conducted to validate the predicted data. Hole Drilling Method (HDM), a semi destructive method and XRD analysis is used to measure the residual stress on the welded specimen. A good agreement is found between the predicted values and measured values.

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Bibliographic Details
Main Authors: Arunkumar,Muthusamy, Dhinakaran,Veeman, Sivashanmugam,Nallathambhi, Petley,Vijay
Format: Digital revista
Language:English
Published: ABM, ABC, ABPol 2019
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1516-14392019000600217
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Summary:In this research work, a finite element model is developed to predict the temperature field and residual stress during plasma arc welding of thin Ti-6Al-4V sheets. Dhinakaran’s heat source model which is based on Parabolic Gaussian distribution is used to predict the temperature field and Anand’s model is used to predict the residual stress. Numerical simulation is performed using ANSYS®. Heat transfer analysis is carried out primarily and the temperature field is given as the input for structural analysis. The concept of APDL programming is used to implement the governing equations. Experimental work has also been conducted to validate the predicted data. Hole Drilling Method (HDM), a semi destructive method and XRD analysis is used to measure the residual stress on the welded specimen. A good agreement is found between the predicted values and measured values.