A desktop computer model of the arc, weld pool and workpiece in metal inert gas welding

Murphy, Anthony B.; Nguyen, Vu; Feng, Yuqing; Thomas, David G.; Gunasegaram, Dayalan R.

doi:10.1016/j.apm.2017.01.033

Cited by 22 publications

(11 citation statements)

References 48 publications

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“…Ideally, the predicted temperature field can be used as thermal loads in the weld stress and distortion simulation. Indeed, Anthony et al [148] developed an integrated model to simulate arc plasma, filler wire transfer, and weld pool dynamics in a lap-fillet weld geometry to predict weld residual stress and distortion. However, this approach is impractical for a large and complex welded structure due to the complexity of numerical model and computational cost.…”

Section: Thermalmentioning

confidence: 99%

Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions

Zhang

Yang

Wei

et al. 2020

Journal of Manufacturing Science and Engineering

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Welding is a major manufacturing process that joins two or more pieces of materials together through heating/mixing them followed by cooling/solidification. The goal of welding manufacturing is to join materials together to meet service requirements at lowest costs. Advanced welding manufacturing is to use scientific methods to realize this goal. This paper views advanced welding manufacturing as a three step approach: (1) pre-design that selects process and joint design based on available processes (properties, capabilities, and costs); (2) design that uses models to predict the result from a given set of welding parameters and minimizes a cost function for optimizing the welding parameters; (3) real-time sensing and control that overcome the deviations of welding conditions from their nominal ones used in optimizing the welding parameters by adjusting the welding parameters based on such real-time sensing and feedback control. The paper analyzes how these three steps depend on process properties/capabilities, process innovations, predictive models, numerical models for fluid dynamics, numerical models for structures, real-time sensing, and dynamic control. The paper also identifies the challenges in obtaining ideal solutions and reviews/analyzes the existing efforts toward better solutions. Special attention and analysis have been given to (1) gas tungsten arc welding (GTAW) and gas metal arc welding (GMAW) as benchmark processes for penetration and materials filling; (2) keyhole plasma arc welding (PAW), keyhole-tungsten inert gas (K-TIG), and keyhole laser welding as improved/capable penetrative processes; (3) friction stir welding (FSW) ......

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Section: Thermalmentioning

confidence: 99%

Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions

Zhang

Yang

Wei

et al. 2020

Journal of Manufacturing Science and Engineering

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“…al. [3] to study thermal histories of MIG welded works. The model can determine temperature distribution, density of current, speed and mass fraction over the complete weld area, work piece and the input data may be used to generate the important properties of weld-ments like stress pattern and micro structural changes.…”

Section: Modelling Studiesmentioning

confidence: 99%

Optimization of Metal Inert Gas Welding Process during Joining of Structural Steels- An Overview

Misra

Porwal

2020

E3S Web Conf.

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Metal Inert Gas welding is a fast, reliable and cost effective technique for joining of different ferrous materials and steels used in the construction of large structures like Fe410WA, IS2062, SS304, AISI1040 and AISI316 etc. To obtain better quality and performance of the steel welded joints, parameter optimisation of metal inert gas welding procedure and weld heat treatment process is carried out. In optimization work and studies, variables of GMAW process like welding voltage and current, speed of welding, WFR (rate of wire feed), GFR (rate of gas flow), type of gas used and effect of heat treatments are kept changing to get best combinations of input parameters for best quality of welded parts. The quality of welds is evaluated in terms of mechanical properties of welded joints like ultimate tensile and yield strength, elongation, microstructure, heat affected zone and defect free weld joints etc. Model and experimental studies are done in different combinations to get best combination of input parameters for steels. Studies by authors have identified the significance of input parameters in ascending order and some of them also quantified the optimal values of the input parameters. Pre and post weld heat treatment of structures is beneficial in improvement of mechanical and fatigue properties.

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“…To take into account the production of metal vapour from the liquid metal surfaces, and the transport of the vapour in the arc, an additional conservation equation for the metal vapour mass fraction has to be solved (Murphy, 2013b). If the mixing of the wire and workpiece alloys in the weld pool is modelled, a further conservation equation for the wire alloy mass fraction is required (Murphy et al, 2017). The energy conservation and electromagnetic equations are also solved in the solid regions of the workpiece and the electrode.…”

Section: The Computational Model Of Mig Weldingmentioning

confidence: 99%

“…Steadystate solution of the equations is often acceptable; only if the welding parameters change, or near the start or end of the weld, is time-dependent solution required. The equations used have been presented by Murphy et al (2017). They are solved using an in-house FORTRAN code based on the finite-volume method presented by Patankar (1980).…”

Section: The Computational Model Of Mig Weldingmentioning

confidence: 99%

A computational model of arc welding – from a research tool to a software product

2017

Syme, G., Hatton MacDonald, D., Fulton, B. And Piantadosi, J. (Eds) MODSIM2017, 22nd International Congress on Modelling and Si

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CSIRO has a long history of modelling arc plasma processes, including arc welding, plasma torches and plasma waste conversion. The models use the methods of computational fluid dynamics applied to viscous incompressible flows, extended to include an energy conservation equation, Maxwell's equations, and additional source terms to take into account plasma effects. The models have been used to gain a scientific understanding of arc plasma physics and chemistry and, as they have gained sophistication and accuracy, to improve and optimise industrial processes. The computer codes that have been developed have, until recently, relied on expert users with familiarity with the detailed operation of the code, and access to a FORTRAN compiler. In a typical implementation, input parameters are provided using user-editable text files, progress towards convergence is monitored by viewing a continuously-updated text file, and the results of the calculations are written as text files and as data files readable by graphics programs. Input and output file handling is not automated; the user is required to rename files to avoid overwriting, and to ensure that all relevant files are stored together. The provision of an appropriate start-up file (for example, a solution obtained for a similar set of input parameters) has required the user to select the file; this relies on the user carefully documenting the input parameters for all solution files. One of CSIRO's arc welding codes has now been packaged into a software product, ArcWeld, using CSIRO's Workspace workflow framework. This advance was motivated by a customer, General Motors, requesting that the code be easily usable by its welding engineers and technicians. The model is three-dimensional and treats the full arc welding process, with solid, liquid and plasma regions included in the computational domain. Despite these factors, physically-based simplifications are used to ensure that ArcWeld can be run under 64bit Windows on standard desktop computers. A simple GUI is used for entry of input parameters, starting the computer code, displaying progress towards convergence, and access to graphical output. The most appropriate start-up file is automatically selected based on the input parameters. All input and output data are written to a user-selected directory. This work has had important benefits. For the scientist, using a workflow platform means that common components and functionality are available as prewritten and pretested operations, so scientists can focus more on their core science and not as much on software development. For end users, the code can now be run by non-experts, who require only very basic training and access to a desktop computer. The input parameters are automatically stored with the output data, reducing the reliance on user documentation, and the user can easily visualise the results. These changes mean that the science can be advanced more quickly and the software can be used 'on the factory floor' to help optimise welding processes. More broadly, t...

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A desktop computer model of the arc, weld pool and workpiece in metal inert gas welding

Cited by 22 publications

References 48 publications

Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions

Advanced Welding Manufacturing: A Brief Analysis and Review of Challenges and Solutions

Optimization of Metal Inert Gas Welding Process during Joining of Structural Steels- An Overview

A computational model of arc welding – from a research tool to a software product

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