Numerical models of gas metal arc welds using experimentally determined weld pool shapes as the representation of the welding heat source

Wahab, Muhammad Abdul; Painter, M. J.

doi:10.1016/s0308-0161(97)00049-5

Cited by 41 publications

(25 citation statements)

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“…3 kg m − . The thermal conductivity and specific heat for individual phases reported in the literature depend of the authors, although follows similar trends [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][24][25][26][27][28][29][30][31][32][33] . The reason for such lack is due to the possibility of different features of the phases formed depending on the thermal history.…”

Section: Thermophysical Propertiesmentioning

confidence: 72%

“…The a,b f , c and b r , are source constant parameters that define the size and shape of the ellipses and, therefore, the heat source distribution. These parameters were estimated from the models for determination of the dimensions of a weld pool proposed by Wahab and Painter 27 and may be found in Table 2 together with the respective investigated welding parameters in this study, while the factors f f and f r were defined as 0.6 and 1.4 respectively. Thickness and preheating effects on the welding region for the investigated steel were also carried out in order to evaluate the response of the present model when applied to more general cases.…”

Section: Initial and Boundary Thermal Conditionsmentioning

confidence: 99%

“…( ) (27) where Vr is the cooling rate at 700 o C in °C.h -1 . At this point, is convenient to summarizes and point out the main features of the FVM computational code considered in this work and their shortcomings.…”

Section: Hardnessmentioning

confidence: 99%

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Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

et al. 2016

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A phenomenological model to predict the multiphase diffusional decomposition of the austenite in low-alloy hypoeutectoid steels was adapted for welding conditions. The kinetics of phase transformations coupled with the heat transfer phenomena was numerically implemented using the Finite Volume Method (FVM) in a computational code. The model was applied to simulate the welding of a commercial type of low-alloy hypoeutectoid steel, making it possible to track the phase formations and to predict the volume fractions of ferrite, pearlite and bainite at the heat-affected zone (HAZ). The volume fraction of martensite was calculated using a novel kinetic model based on the optimization of the well-known Koistinen-Marburger model. Results were confronted with the predictions provided by the continuous cooling transformation (CCT) diagram for the investigated steel, allowing the use of the proposed methodology for the microstructure and hardness predictions at the HAZ of low-alloy hypoeutectoid steels.

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Section: Thermophysical Propertiesmentioning

confidence: 72%

Section: Initial and Boundary Thermal Conditionsmentioning

confidence: 99%

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Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

et al. 2016

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“…The process variables with the maximum influence are the welding current, welding voltage, travel speed and arc efficiency [2]. The important factors for weld bead geometry are bead width, bead height and weld penetration.…”

Section: Introductionmentioning

confidence: 99%

Modelling and Optimization of Gas Metal Arc Welding Using Response Surface Methodology

2016

Arimpie - 2016

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Abstract-GMAW is a complicated process with many interrelated parameters affecting the quality of the welded joint. The process variables with the maximum influence are the welding current, welding voltage, travel speed and arc efficiency. Response surface methodology was used to predict the weld penetration of gas metal arc welded mild steel. The experiments were conducted based on three factors, three-level, and central composite face centered design with full replications technique, and mathematical model was developed. The results obtained through response surface methodology were verified through a confirmation experiment.The welding parameters such as speed, welding current and voltage have been optimized for material AISI 1020 using GMAW process. To fortify the robustness of experimental design, a confirmation test was performed at selected optimal process parameter setting. Observations from this method may be useful for automotive sub-assemblies, shipbuilding and vessel fabricators and operators to obtain optimal welding conditions. Keywords-Gas metal arc welding, penetration, response surface methodology,central composite design.

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“…Vários destes foram elaborados para prever aspectos geométricos do cordão, propriedades mecânicas e tensões residuais da junta e comportamento da poça de fusão [5][6][7][8][9][10][11][12][13]. Outros tantos foram desenvolvidos para, em conjunto com a monitoração de parâmetros do processo, permitir o seu controle, assim como inferir a qualidade do cordão e a formação de descontinuidades [14][15][16][17].…”

Section: Introductionunclassified

Modelagem matemática do processo de soldagem GMAW: transferência por vôo livre

Santana¹,

Modenesi²

2011

Soldag. insp.

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Resumo Palavras-chave: Soldagem MIG/MAG, Simulação numérica, Modelagem matemática, Parâmetros de soldagem. Abstract: This paper describes the conception and validation of a mathematical model applied to GMA welding. This model allows predicting some welding parameters as well as process behavior for operation with free flight transfer mode. This model was based on a set of equations that describes the power source characteristics, the voltage drop along the electric arc, the welding circuit and the

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Numerical models of gas metal arc welds using experimentally determined weld pool shapes as the representation of the welding heat source

Cited by 41 publications

References 1 publication

Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

Numerical Predictions for the Thermal History, Microstructure and Hardness Distributions at the HAZ during Welding of Low Alloy Steels

Modelling and Optimization of Gas Metal Arc Welding Using Response Surface Methodology

Modelagem matemática do processo de soldagem GMAW: transferência por vôo livre

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