Metallurgical Engineering

Metallurgical Engineering

Simulation of heat transfer in gas tungsten arc welding of stainless steel type 304

Document Type : Research Paper

Authors
Mostafa Jafarzadegan 1
Reza Taghiabadi 2
Mohammad Ammar Mofid 3
1 Assistant professor of materials science, Faculty of engineering, Imam Khomeini International University (IKIU), Qazvin, Iran.
2 Associate professor of materials science, Faculty of engineering, Imam Khomeini International University (IKIU), Qazvin, Iran.
3 Assistant professor of materials science, Department of Petroleum, Mining and Material Engineering, Faculty of engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
10.22076/me.2020.122979.1284
Abstract
In this paper, the distribution of temperature and thermal cycle in gas tungsten arc welding of stainless steel 304 is studied. The welding operation was performed under different heat inputs of 540 and 782 kJ/mm on the plates with 2 mm thickness. The Abaqus software was employed for simulation. The volumetric heat distribution, according to the double ellipsoidal (Goldak) model, was considered as the heat source of the welding and DFLUX subroutine was coded by FORTRAN. The simulation results were compared with the Rosenthal and Adams models and experimental results. The simulation results with both heat inputs are well compatible with the cross section dimensions of the welds, while the Rosenthal model predicts a smaller welds’ pool size. The temperature-time curves obtained from the simulation and Rosenthal model have considerable differences but their predicted cooling time and rate in the temperature range of 800 to 500 °c, especially in heat input of 782 kJ/mm, are close to each other (the difference is less than 7.2%). The results also showed that the maximum temperature of the regions farther from the fusion boundary in Adams model is predicted higher than that of simulation and Rosenthal model, while the results of simulation and Rosenthal model are closer to each other.
Keywords
Temperature simulation
Abaqus
Rosenthal model
Adams model
GTAW
1.         Pittner A, Weiss D, Schwenk C, Rethmeier M. Fast Temperature Field Generation For Welding Simulation and Reduction Of Experimental Effort. Welding in the World. 2011;55(9):83-90.
2.         Venkateswarlu K, P Nanda K, RaviKumar PS. Finite Element Simulation of Temperature Distribution, Distortion and Residual Stresses of Dissimilar Welded Joints. Materials Today: Proceedings. 2018;5:11933-40.
3.         Perret W, Schwenk C, Rethmeier M. Comparison of analytical and numerical welding temperature field calculation. Computational Materials Science. 2010;47:1005–15.
4.         Nithiarasu P, Lewis RW, Seetharamu KN. Fundamentals of the finite element method for heat and mass transfer. United Kingdom: John Wiley & Sons; 2016.
5.         Ismail MIS, Afieq WMA. Thermal Analysis on a Weld Joint of Aluminium Alloy in Gas Metal Arc Welding. Advances in Production Engineering & Management. 2016;11:29-37.
6.         Bergheau JM, Fortunier R. Finite Element Simulation of Heat Transfer. New Jersey: Wiley; 2008.
7.         Goldak J, Chakravarti A, Bibby M. A New Finite Element Model for Welding Heat Sources. Metallurgical Transactions B. 1984;15B:299-305.
8.         Goldak JA, Akhlaghi M. Computational Welding Mechanics. Boston, MA: Springer; 2005.
9.         Tafarroj MM, Kolahan F. A comparative study on the performance of artificial neural networks and regression models in modeling the heat source model parameters in GTA welding. Fusion Engineering and Design. 2018;131:11-118.
10.       Zubairuddin M, Albert SK, Vasudevan M, Mahadevan S, Chaudhari V, Suri VK. Numerical simulation of multi-pass GTA welding of grade 91 steel. Journal of Manufacturing Processes. 2017;27:87-97.
11.       Velaga SK, Ravisankar A. Finite element based parametric study on the characterization of weld process moving heat source parameters in austenitic stainless steel. International Journal of Pressure Vessels and Piping. 2017;157:63-73.
12.       Zhang M, Zhou Y, Huang C, Chu Q, Zhang W, Li J. Simulation of Temperature Distribution and Microstructure Evolution in the Molten Pool of GTAW Ti-6Al-4V Alloy. Materials. 2018, 1-16.
13.       Yadaiah N, Bag S. Development of egg-configuration heat source model in numerical simulation of autogenous fusion welding process. International Journal of Thermal Sciences. 2014;86:125-38.
14.       Kou S. Welding Metallurgy. Second Edition ed. New Jersey: Wiley; 2003.
15.       Zhu XK, Chao YJ. Effects of temperature-dependent material properties on welding simulation. Computers & Structures. 2002;80:967-76.
16.       Valencia JJ, Quested PN. Thermophysical Properties. In: Stefanescu DM, editor. ASM Handbook. 15. United States of America: ASM International; 2008. p. 468-81.
17.       Mills KC, Li YSZ, Brooks RF. Equations for the Calculation of the Thermo-physical Properties of Stainless Steel. ISIJ International. 2004;44(10):1661-8.
18.       Abaqus 6.14 User Subroutines, Reference Guide: DFLUX User subroutine to define nonuniform distributed flux in a heat transfer or mass diffusion analysis.
19.       Yeh RH, Liaw SP, Yu HB. Thermal analysis of welding on aluminum plates. Journal of Marine Science and Technology. 2003;11(4):, 20-13.
20.       Welding science and technology. In: Jenney CL, O’Brien A, editors. AWS welding handbook. 1. United States of America: American Welding Society; 2001. p. 87-112.
21.       Poorhaydari K, Patchett BM, Ivey DG. Estimation of Cooling Rate in the Welding of Plates with Intermediate Thickness. Welding Journal. 2005;October:149-s-55-s.
22.       Zhang Y, Ma TJ, Xie HX, Tan YM, Li PY. Estimating the Cooling Rates of a Spot Welding Nugget in Stainless Steel. Welding Journal. 2012;91:247s-51s.
23.       Arora A, Roy GG, DebRoy T. Cooling rate in 800 to 500 oC range from dimensional analysis. Science and Technology of Welding and Joining. 2010;15(5):423-7.
24.       Lippold JC, Kotecki DJ. Welding Metallurgy and Weldability of Stainless Steels: Wiley-VCH; 2005.
25.       Suresh G, Parida PK, Bandi S, Ningshen S. Effect of carbon content on the low temperature sensitization of 304L SS and its corrosion resistance in simulated ground water. Materials Chemistry and Physics. 2019;226:184–94.

  • Receive Date 12 March 2020
  • Revise Date 04 August 2020
  • Accept Date 31 October 2020