An Improved Method of Capturing the Surface Boundary of a Ti-6Al-4V Fusion Weld Bead for Finite Element Modeling

Turner, Richard; Villa, Matteo; Sovani, Yogesh; Panwisawas, Chinnapat; Perumal, Bama; Ward, Robin; Brooks, Jeffery; Basoalto, Hector

doi:10.1007/s11663-015-0489-5

Cited by 4 publications

(6 citation statements)

References 10 publications

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“…[25] The capability of this heat source representation, using Cartesian co-ordinates to specify the fusion boundary, has been demonstrated, and is illustrated in Figure 3. The critical outputs from the thermal simulation include the replication of the size and shape of the weld pool predicted by the CFD model, in the FE software.…”

Section: Resultsmentioning

confidence: 99%

“…[23,24] However, It is also possible to directly enter a set of Cartesian x,z co-ordinates to describe the ½ width of the weld pool (in the x-axis) (assuming a symmetrical weld shape) at any given depth (the z-axis), about the widest region of the molten weld pool in its y axis (length). [25] The widest region of the cross-sectioned weld pool is considered to be the location at which the heat source beam (either laser or EB) is contacting the material. The software will then make a best attempt to maintain the fusion boundary at these specified Cartesian co-ordinates by heating the enclosed material above the liquidus temperature.…”

Section: Methodsmentioning

confidence: 99%

“…Validation of the thermal fields predicted by coupled modeling was considered in previous work. [25] However, a mechanical validation exercise is presented here to assess the accuracy of the coupled model against experimental data.…”

Section: Methodsmentioning

confidence: 99%

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An Integrated Modeling Approach for Predicting Process Maps of Residual Stress and Distortion in a Laser Weld: A Combined CFD–FE Methodology

Turner

Panwisawas

Sovani

et al. 2016

Metall Mater Trans B

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Laser welding has become an important joining methodology within a number of industries for the structural joining of metallic parts. It offers a high power density welding capability which is desirable for deep weld sections, but is equally suited to performing thinner welded joints with sensible amendments to key process variables. However, as with any welding process, the introduction of severe thermal gradients at the weld line will inevitably lead to process-induced residual stress formation and distortions. Finite element (FE) predictions for weld simulation have been made within academia and industrial research for a number of years, although given the fluid nature of the molten weld pool, FE methodologies have limited capabilities. An improvement upon this established method would be to incorporate a computational fluid dynamics (CFD) model formulation prior to the FE model, to predict the weld pool shape and fluid flow, such that details can be fed into FE from CFD as a starting condition. The key outputs of residual stress and distortions predicted by the FE model can then be monitored against the process variables input to the model. Further, a link between the thermal results and the microstructural properties is of interest. Therefore, an empirical relationship between lamellar spacing and the cooling rate was developed and used to make predictions about the lamellar spacing for welds of different process parameters. Processing parameter combinations that lead to regions of high residual stress formation and high distortion have been determined, and the impact of processing parameters upon the predicted lamellar spacing has been presented.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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An Integrated Modeling Approach for Predicting Process Maps of Residual Stress and Distortion in a Laser Weld: A Combined CFD–FE Methodology

Turner

Panwisawas

Sovani

et al. 2016

Metall Mater Trans B

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“…The welding experiments were, thus, executed before the simulations, then the welds were sectioned and the weld pool width was recorded as a function of the depth. This heat source model is presented in the literature [40]. Weld pool dimensions for the models were matched to the experiment.…”

Section: Finite Element Modellingmentioning

confidence: 99%

Metallurgical Modelling of Ti-6Al-4V for Welding Applications

Villa

Brooks

Turner

et al. 2021

Metals

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Manufacturing processes such as welding subject the α/β titanium alloy Ti-6Al-4V to a wide range of temperatures and temperature rates, generating microstructure variations in the phases and in the precipitate dimensions. In this study, the metallurgical and numerical modelling of Ti-6Al-4V when subjected to a high energy density welding process was affected by a series of analytical equations coded in Sysweld commercial specialist FE welding software. Numerical predictions were compared with experimental results from laser welding tests on plates with different thicknesses, initial microstructural morphologies, and operating conditions. The evolution of the microstructure was described by using a diffusion-based approach when the material was operating in the α + β field, whilst empirical equations were used for temperatures above the β-transus temperature. Predictions made by the subroutines within the FE model were shown to match with reasonable trends when validated using experimental characterisation methods for various metallurgical features, including the α particle size, β grain size, martensitic needle thickness, and relative phase volume fractions.

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“…The SYSWELD simulation software for welding has been widely used by several researchers. By using a Cartesian coordinate system in SYSWELD, it helps in achieving the exact weld pool shape produced by the laser [20]. The various heat source models such as three-dimensional conical and coupled heat source models are used for predicting the actual weld bead morphology.…”

Section: Introductionmentioning

confidence: 99%

Finite element modeling and optimization of hybrid laser–TIG welding of type 316L(N) austenitic stainless steel

Chandrasekhar

Ragavendran

Vasudevan

2020

J Braz. Soc. Mech. Sci. Eng.

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An integrated approach was followed for determining the optimized process parameters for hybrid laser-tungsten inert gas (TIG) welding of 316L(N) stainless steel which involve FEM followed by optimization. FEM-based model was developed to predict the thermal distribution for a various combination of welding process parameters. The hybrid heat source combining conical and double-ellipsoidal heat sources was used for generating the temperature distribution during welding. The penetration depth produced by welding was estimated from the thermal model for various set of process parameters by running the model several times. The generated dataset consisting of process parameters and the depth of penetration (DOP) was used for developing adaptive neuro-fuzzy information system (ANFIS) model for correlating the set of input process parameters with the output DOP. This ANFIS model was then used in the objective function of a genetic algorithm (GA) for identifying the optimum process parameters to achieve the maximum DOP during autogenous hybrid laser-TIG welding. The optimized solutions were validated by performing bead-on-plate experiments on 5.6-mm-thick type 316L(N) stainless steel plates. The above-integrated approach was found to accurately determine the optimum hybrid laser-TIG welding process parameters for achieving the maximum DOP with minimum experimentation.

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An Improved Method of Capturing the Surface Boundary of a Ti-6Al-4V Fusion Weld Bead for Finite Element Modeling

Abstract: This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Cited by 4 publications

References 10 publications

An Integrated Modeling Approach for Predicting Process Maps of Residual Stress and Distortion in a Laser Weld: A Combined CFD–FE Methodology

An Integrated Modeling Approach for Predicting Process Maps of Residual Stress and Distortion in a Laser Weld: A Combined CFD–FE Methodology

Metallurgical Modelling of Ti-6Al-4V for Welding Applications

Finite element modeling and optimization of hybrid laser–TIG welding of type 316L(N) austenitic stainless steel

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