**4.4. Discussions and recommendation for further research**

602 Numerical Simulation – From Theory to Industry

Fig. 19 illustrates the distortions of the welding structure due to the welding sequences. The initial undeformed configurations were also shown. From Fig. 19, it can be seen the angular distortions occurred in both flanges. It can be further revealed that there was the difference of distortion between the flanges showing that the distortion was unsymmetrical. The maximum value of angular distortion took place on the right flange for all the welding sequences, unless that of WS-2 which took place on the left one. The simulation results obtained also clearly indicate the influence of the welding sequences examined in the present study to the angular distortions of the T-joint fillet weld considering the same boundary conditions appliedin the corresponding FEM models of the T-joint fillet weld.

Furthermore, Table 3 summarizes the vertical displacements and the angular distortions of both flanges due to the welding sequences. The angular distortion differences were also

**Figure 19.** Distortions of the welding structure due to the welding sequences: (a) WS-1, (b) WS-2, (c)

**4.3. Distortions** 

shown in Table 3.

WS-3, and (d) WS-4.

From the results, it seems that, for the problem considered in this numerical study, two welding sequences, namely WS-2 and WS-4, have taken the attention. The WS-2, which is called as simple alternating welding, has produced the lowest peak temperature and the smallest longitudinal and transverse residual stresses as well. Meanwhile the WS-4, which is called as multiple crossing welding, has produced the smallest angular distortion and angular distortion difference, although it produced the highest peak temperature.

The information appears to be consistent with respect to the welding sequences performed. The corresponding value of the von Mises stress and the distortion difference produced as shown respectively in Table 2 and 3 indicated this as well. In particular, the results were also in contrast to those of WS-1 and WS-3. Not only did the welding sequences produce high angular distortions, but also they resulted in relatively high values of the von Mises stresses. Furthermore, the distortion results obtained appears to be match with the ones usually found in the welding practice incorporating alternating welding.

Also, considering limited literatures concerning welding simulation of T-joint fillet welds in 3D (Chang & Lee, 2009 and Deng et al., 2007), the results obtained would be very valuable

and useful to welding designers and practitioners, because the results have been describing the predicted or anticipated residual stresses and distortions with respect to the welding sequences, varied from simple to multiple crossing welding. In addition, the assessment of welding performance which can be taken in an efficient and fast manner allows the designers to integrate it in their subsequent design plans.

3D Finite Element Simulation of T-Joint Fillet Weld:

Effect of Various Welding Sequences on the Residual Stresses and Distortions 605

**Author details** 

*Surabaya, Indonesia* 

Mas Irfan Purbawanto Hidayat

*(ITS), Surabaya, Indonesia* 

**Acknowledgement** 

acknowledged.

**6. References** 

41, 250-258.

New York.

Cambridge.

Eng. , Vol. 195, 6710-6736.

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Concequences, Pergamon Press Ltd, London.

Stresses, Computers and Structures, Vol. 81, 273-286.

*Department of Ocean Engineering, Institut Teknologi Sepuluh Nopember (ITS),* 

High-Performance Alloys, ASM International USA.

*Department of Materials and Metallurgical Engineering, Institut Teknologi Sepuluh Nopember* 

Funding provided by Institut Teknologi Sepuluh Nopember (ITS) Surabaya is gratefully

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Nur Syahroni

Furthermore, the 3D simulation results of T-joint fillet weld may be further used as validation model for 3D welding simulations as well as for other numerical technique implementations such as mesh-less techniques, where no predefined mesh is required to build interpolation of the potential field variables investigated thus reducing cumbersome mesh preparation and increasing the related simulation time.

Moreover, the relationship between the input and output variables of the welding process may be further investigated and optimized using techniques from artificial intelligence (AI) family, such as neural networks and genetic algorithm. For examples, in the single pass GTAW welding method presented in this study, the variables of welding current, voltage, welding speed and welding sequences have been examined, in which more output variables may be also examined, such as the nature and dimensions of weld bead. Thus, much more information and insights can be revealed in such a welding process, which is in turn very useful to optimize the welding process.

It is noted here that the aspects of shrinkage were not discussed in the present paper. The aspects could be also related to the variation of welding speed. Also, it may be interesting if some welding paths in one WS are performed and simulated simultaneously thus allowing the exploitation of symmetry and anti-symmetry boundary conditions in the finite element model. The aforementioned aspects would be the subjects of further investigations.
