A Model to Simulate Welding Process (or additive manufacturing)



Details about Additive Manufacturing and Welding:

Here we provide a brief description of additive manufacturing and welding to make it easier to understand.


Many metallic structures in the industry are assembled through some kind of welding process which is composed of heating, melting and solidification using a heat source such as arc, laser, torch or electron beam. The highly localized transient heat and strongly nonlinear temperature fields in both heating and cooling processes cause non-uniform thermal expansion and contraction, resulting in plastic deformation in the weld and surrounding areas. As a result, residual stress, strain and distortion are permanently produced in the welded structures[1]:

High tensile residual stresses are known to promote fracture and fatigue, while compressive residual stresses may induce undesired, and often unpredictable, global or local buckling during or after the welding. It is particularly evident with large and thin panels, as used in the construction of automobile bodies and ships. These adversely affect the fabrication, assembly, and service life of the structures. Therefore, prediction and control of residual stresses and distortion from the welding process are extremely important in the shipbuilding and automotive industry [1]

Additive manufacturing and WAAM:

Additive manufacturing (AM) of large-scale components requires an insight into the complicated microstructural features. Wire + arc additive manufacturing (WAAM) is by far the most efficient AM process with a relatively higher deposition rate (1-4 kg/h). This enables the manufacturing of large parts up to several metres. This manufacturing process incorporates either gas metal arc welding (GMAW), plasma arc welding or gas tungsten arc welding techniques for metal deposition. Compared to its counterpart powder-based AM techniques, such as selective laser melting (SLM), the WAAM process offers a lower
production cost due to its relatively high deposition rate [2].

A wide range of weldable metals and alloys such as steel nickel and titanium alloys can be employed in this technology. WAAM facilitates the efficient manufacturing of Ti alloys such as Ti-6Al-4V alloy, which is extensively important in the aerospace industry. A substantial reduction in the buy-to-fly ratio from around 10-20 for a conventionally machined component to 1 could be achieved using this process. WAAM incorporates a multi-pass arc welding process, resulting in the efficient manufacturing of
large-scale parts with acceptable mechanical properties at a lower production cost [2].

More details about this product:

There are more than 300 parameters, including power, speed, and printing strategy, which can affect the quality of the as-built part. Expensive and time-consuming trial-and-error is common to determine optimal conditions for the process. An efficient finite element analysis (FEA) tool is helpful to accurately predict the actual manufacturing process. This reduces the number of costly experimental iterations. Thus, modelling is an important skill in fields related to additive manufacturing and welding processes.

What we offer here:

In this video, you will learn how to create a simple welding model that is similar to the additive manufacturing process. To simulate the welding process you need a heat transfer model in Abaqus. For adding material we use the element birth technique by using Python code. For heat flux, you define a gaussian heat distribution in the Dflux subroutine. To use subroutine we need to use the FORTRAN code and also Abaqus needs to be linked to Intel FORTRAN. You might also be interested in using Goldak heat input and you can find it here (Click here). The video is short so you can learn this in less than 20 minutes and have the output and Abaqus CAE file.

If you like to develop the model with the Goldak heat input model you can use the following link to download it:

Goldak heat input for Welding and AM process

 In this video, we avoid giving too many details so you can easily use the product. Here, you can find the following files:

Abaqus files: CAE, ODB, INP, FORTRAN, Python, and JNL

Solidwork model

Powerpoint files that contain more details.

Video files: How to create this model, Powerpoint presentation.

For more information please send me an Email:



[1] Zhu, X. K., and Y. J. Chao. “Effects of temperature-dependent material properties on welding simulation.” Computers & Structures 80.11 (2002): 967-976.

[2] Tangestani, Reza, et al. “Effects of Vertical and Pinch Rolling on Residual Stress Distributions in Wire and Arc Additively Manufactured Components.” Journal of Materials Engineering and Performance (2020): 1-12.



Easy learning

1 review for A Model to Simulate Welding Process (or additive manufacturing)

  1. HyperLyceum Team (verified owner)

    This is a good start for beginners.

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