Published at : 29 Jul 2019
Volume : IJtech
Vol 10, No 4 (2019)
DOI : https://doi.org/10.14716/ijtech.v10i4.1849
Karim Agrebi | Laboratory of Applied Mechanics and Engineering, University of Tunis EL Manar, National Engineering School of Tunis, BP 37, Le Belvédère, 1002, Tunisia |
Asma Belhadj | Laboratory of Applied Mechanics and Engineering, University of Tunis EL Manar, National Engineering School of Tunis, BP 37, Le Belvédère, 1002, Tunisia |
Mahmoud Bouhafs | Laboratory of Applied Mechanics and Engineering, University of Tunis EL Manar, National Engineering School of Tunis, BP 37, Le Belvédère, 1002, Tunisia |
Welding processes are widely used in many
industries. The determination of welding parameters and the study of their
influence on the mechanical and metallurgical behavior of materials require
multiple experiments, and the relevant studies are costly in terms of time and
resources. Thus, numerical simulations can serve as a solution when it comes to
choosing the appropriate welding process and optimizing its parameters while
minimizing costs. The present work contributes to the development of a finite
element code, using MATLAB software, for the prediction of thermo-mechanical and
metallurgical behavior during the Tungsten inert gas (TIG) welding process.
Numerical computation is based on the mathematical formulation of physical
phenomena and thermal exchanges. In this paper, results dealing with the
prediction of the temperature field evolution during the C50 steel TIG-welding
process are presented. In this case, the thermal problem is solved numerically
using the finite element method. The memory and computation time problems are
solved using optimal stocking and resolution algorithms. To validate the
developed computation code, numerical results are first compared with other
published numerical results, then with our experimental data. A satisfactory
concordance between simulated temperature evolutions and those measured with thermocouples
implanted in the welded sheets was found.
Finite elements; Mathematical formulation; Thermal simulation; TIG welding
During welding, highly complicated phenomena
occur due to the coupled interactions between heat transfer, metallurgical
transformation, and mechanical behavior. To be able to predict the evolution of
these phenomena, numerical methods—especially the finite element method
(FEM)—are widely used. This method, which is performed using calculation codes
like TRANSWELD (Hamide & Bellet, 2007; Hamide et al., 2008), ASTER CODE
(Delmas, 2013) and SYSWELD, is based on mathematical formulation of the coupled
physical phenomena.
Several works have been published on numerical simulation of the welding process. Simulating thermal behavior during welding processes is based on numerically solving three-dimensional transient heat equations with temperature-dependent material properties (Belhadj et al., 2010; Anca et al., 2011; Seleš et al., 2018). Numerical calculations require a longer time calculation, high storage capacity, and significant computer resources to predict the thermal, followed by metallurgical and mechanical, history. For this reason, using an adaptive mesh can be a solution for solving calculation problems (Hamide & Bellet, 2007; Hamide et al., 2008). For the validation of thermal simulation results during welding processes, researchers have compared temperature evolutions with experimental data, analytical solutions, or simulation results with other FEM code calculation. Anca et al.(2011) compared simulated temperature evolutions during welding processes with a semi-analytical solution developed by Weiner and Boley (1963). Moreover, Belhadj et al.(2010) simulated thermal behavior during CO2 laser welding and compared the temperature evolution according to time with the thermocouple-measured temperature in many positions on a welded sheet.
The TIG welding process is one of the
most common methods used in the aerospace, automotive, and pipe industries (Lundbäck,
2003; Baskoro et al., 2011).TIG process welding, especially of stainless steel,
has been studied numerically and experimentally by many authors (Del Coz Diaz
et al., 2010;Ganesh et al., 2014; Aissani et al., 2015; Chuaiphan &
Srijaroenpramong, 2018). These numerical simulations have been developed with
software like ABAQUS, ASTER CODE, and ANSYS. These software programs offer a
significant computing potential, especially for thermo-mechanical modeling.
However, they are limited for modeling other phenomena occurring during the
welding of some materials, such as metallurgical transformations or convection
flow in the melt. Nevertheless, these limitations can be overcome via the
user’s ability to develop and integrate functions, employing subroutines to
extend the possibilities of this software and providing the flexibility
required for any research work. In this study, we have opted for the
development of a specific numerical calculation tool, integrating all the
welding phenomena, using the MATLAB software to simulate material behavior
during the TIG welding of phase transformation steel. This computer code gives
the possibility to predict the thermo-mechanical and metallurgical
transformations in the welded sheets from the beginning of the welding until
the end of the cooling.
In this paper, thermal history prediction and its validation are presented. A thermal model with a moving heat source is developed to calculate the temperature on each element of an adaptive mesh during the welding and cooling stages. The developed thermal model considers the nonlinearity introduced by thermo-physical properties, which depends on the temperature. The numerical results are presented in the form of isotherms at different times of welding and temperature evolutions according to time in each point of the mesh. In addition to numerical model development, an experimental protocol is performed to optimize the TIG welding parameters of the C50 steel, realize automatic welding lines, and specifically, measure temperature data during welding using K-thermocouples implanted in several points on the welded sheet. These experimental results aim to validate the numerical results from the developed model. Therefore, finite element simulated temperature evolutions according to time are compared with those measured experimentally.
In
the work, we have developed a computer finite element code using MATLAB
software. This code aims to predict thermal behavior during C50-steel
TIG-welding. The suggested model gives the possibility to determinate the
space-time temperature evolutions in each point of the welded sheet from the
beginning of welding until the return to thermal balance. In addition to
numerical study, experimental investigations are made in order to measure
temperature evolutions according to time during the welding of a 7mm sheet.
Comparison of numerical and experimental results shows a good consistency.The validated temperature fields at various time steps,
resulting from the developed model, are used as an input data on the mechanical
and metallurgical behavior simulation models during the TIG welding of C50
steel. Results of these models will be published subsequently.
Aissani, M., Guessasma, S., Zitouni, A., Hamzaoui, R.,
Bassir, D.,Benkedda, Y., 2015. Three-Dimensional Simulation of 304L Steel TIG
Welding Process: Contribution of The Thermal Flux. Applied Thermal Engineering,Volume 89, pp.822–832
Anca, A., Cardona, A., Risso, J.,Fachinotti, V.D., 2011.
Finite Element Modeling of Welding Processes. Applied Mathematical Modelling, Volume 35(2), pp.688–707
Baskoro, A.S., Masuda, R., Suga, Y., 2011. Comparison of
Particle Swarm Optimization and Genetic Algorithm for Molten Pool Detection in
Fixed Aluminum Pipe Welding. International Journal of Technology, Volume
2(1), pp. 74–83
Belhadj, A., Bessrour, J., Masse, J.E., Bouhafs,
M.,Barrallier, L., 2010. Finite Element Simulation of Magnesium Alloys Laser
Beam Welding. Journal of Materials
Processing Technology, Volume 210(9), pp.1131–1137
Chuaiphan, W., Srijaroenpramong, L., 2018. Optimization of Gas Tungsten Arc Welding Parameters for the Dissimilar
Welding between AISI 304 and AISI 201 Stainless Steels. Defence Technology, Volume 15(2), pp. 170–178
Del Coz Diaz, J.J., Rodríguez, P.M., Nieto, P.G.,
Castro-Fresno, D., 2010. Comparative Analysis of TIG Welding Distortions between
Austenitic and Duplex Stainless Steels by FEM. Applied Thermal Engineering, Volume 30(16),pp.2448–2459
Delmas, J., 2013. Functions of Form and Points of Integration
Finite Elements. EDF Research and Development, GNU FDL
Depradeux, L., Jullien, J.F., 2004. 2D and 3D Numerical
Simulations of TIG Welding of a 316L Steel Sheet. Revue Européenne des Eléments, Volume13(3-4),pp.
269–288
Ganesh,
K.C., Vasudevan, M., Balasubramanian, K.R., Chandrasekhar, N., Mahadevan, S.,
Vasantharaja, P.,Jayakumar, T., 2014. Modeling,
Prediction and Validation of Thermal Cycles, Residual Stresses and Distortion
in Type 316 LN Stainless Steel Weld Joint Made by TIG Welding Process. Procedia Engineering, Volume 86, pp.767–774
Hamide, M.,Bellet, M., 2007. Adaptive Anisotropic Mesh
Technique for Coupled Problems: Application to Welding Simulation. In J.M.
Cesar de Sa, & A.D. Santos (Eds.), AIP
Conference Proceedings, Volume 908(1), pp.1561–1566
Hamide,
M., Massoni, E.,Bellet, M., 2008. Adaptive
Mesh Technique for Thermal–Metallurgical Numerical Simulation of Arc Welding
Processes. International Journal for Numerical
Methods in Engineering, Volume 73(5), pp.624–641
Lundbäck, A., 2003. Finite
Element Modeling and Simulation of Welding of Aerospace Components. Doctoral
Dissertation, Luleåtekniskauniversitet, Swedia
Seleš, K., Peri?, M., Tonkovi?, Z.,2018. Numerical Simulation of a Welding Process using a Prescribed Temperature Approach. Journal of Constructional Steel Research, Volume 145, pp.49–57
Weiner, J.H., Boley, B.A., 1963. Elasto-Plastic Thermal Stresses in a Solidifying Body. Journal of the Mechanics and Physics of Solids, Volume11(3), pp.145–154