scholarly journals Influence of mill scale on weld bead geometry and thermal cycle during GTA welding of high-strength steels

2020 ◽  
Vol 64 (7) ◽  
pp. 1175-1183
Author(s):  
Rahul Sharma ◽  
Uwe Reisgen
Keyword(s):  
Thermal Cycle ◽  
High Strength Steels ◽  
High Strength ◽  
Gta Welding ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Mill Scale

Finite Element Simulation of Weld Bead Geometry and Temperature Distribution during GTA Welding of Modified 9Cr-1Mo Steel and Experimental Validation

2014 ◽  
Vol 14 (4) ◽  
pp. 195-207 ◽  
Author(s):  
M. Zubairuddin ◽  
S.K. Albert ◽  
M. Vasudevan ◽  
V. Chaudhari ◽  
V.K. Suri
Keyword(s):  
Finite Element ◽  
Cooling Rate ◽  
Gta Welding ◽  
Butt Joint ◽  
Weld Bead ◽  
Peak Temperature ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Element Simulation ◽  
Effect Of Copper

AbstractThe thermal analysis of Modified 9Cr-1Mo steel plate during GTA welding is carried out using finite element method employing SYSWELD software. First, the simulation of bead on plate welds for 16 varying process parameter conditions by employing a double ellipsoidal heat source was carried out. Simulated bead on plate weld bead dimensions for the 16 welds were compared with the actual bead dimensions obtained experimentally. Then the simulation of GTA welding of square butt joint on 3 mm thick plates of dimensions 300 × 125 × 3 mm was carried out. The simulated thermal profiles were validated using thermocouple measurements. There was good agreement between the predicted and measured weld bead profiles and thermal cycles for square butt joint. The investigation on the effect of copper back up plate on the peak temperature and the cooling rate has revealed that the peak temperature decreased by 147 °C and the cooling rate increased by 35%.

Lumped Multitorch Control of Welding During Production

1994 ◽  
Vol 116 (3) ◽  
pp. 348-354 ◽  
Author(s):  
C. C. Doumanidis
Keyword(s):  
Controller Design ◽  
Welding Process ◽  
Gta Welding ◽  
Adaptive Controller ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Thermomechanical Characteristics ◽  
Process Disturbances ◽  
Geometric Arrangements

In this article, multiple lumped thermomechanical characteristics of the welding process are regulated by modulation of the welding conditions in real time through feedback control. The controller design is based on three dynamic welding models: a lumped analytical formulation of the weld bead geometry, a numerical simulation of the distributed thermal and phase field, and an experimental linearized model with nonstationary parameters. To account for nonlinearity and thermal drift effects, the weld parameters are identified in-process by the multivariable adaptive controller through surface temperature measurements with an infared pyrometer. Multiple heat inputs, implemented by a single reciprocating, timeshared torch, are employed for simultaneous decoupled control of thermal attributes, such as weld bead size, heat affected zone and cooling rate. The performance of closed-loop controlled welding is tested in setpoint changes and unexpected process disturbances for various welding techniques, materials and geometric arrangements, including new experiments of stainless pipe seam GTA welding.

Effect of Process Parameters and Heat Input on Weld Bead Geometry of Laser Welded Titanium Ti-6Al-4V Alloy

2019 ◽  
Vol 969 ◽  
pp. 613-618 ◽  
Author(s):  
Muralimohan Cheepu ◽  
D. Venkateswarlu ◽  
P. Nageswara Rao ◽  
S. Senthil Kumaran ◽  
Narayanan Srinivasan
Keyword(s):  
Laser Welding ◽  
Weld Zone ◽  
Laser Beam Welding ◽  
High Strength ◽  
Industrial Applications ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Weld Geometry ◽  
Welding Technique

Laser beam welding is one of the most favorable welding technique and its importance in industry is demanding due to higher welding speeds and lower dimensions and distortions in the welds. Moreover, its high strength to weld geometries and minimal heat affected zones makes favorable for various industrial applications. In the present study, laser welding of titanium alloy was investigated to observe the effects of parameters on the bead geometry and metallurgical properties. The laser power and welding speeds were varied to identify their impact on the formation of weld geometry. The width and depth of the fusion zone is varied with welding conditions. The finer grains identified in weld zone and the width of heat affected zone was significantly changes with laser welding power. The mechanical properties of the weld joint are controlled by obtaining optimum weld bead geometry and width of the head affected zone in the welds.

A modified version of MATLAB application window for predicting the weld bead profile and stress–strain plot of AA5052 CMT weldment using ER4043

SIMULATION ◽  
2021 ◽  
pp. 003754972110315
Author(s):  
B Girinath ◽  
N Siva Shanmugam
Keyword(s):  
Strain Curve ◽  
Weld Bead ◽  
Welding Parameters ◽  
Bead Geometry ◽  
Hybrid Technique ◽  
Stress Strain Curve ◽  
Stress Strain ◽  
Weld Bead Geometry ◽  
Inference System ◽  
Engineering Stress

The present study deals with the extended version of our previous research work. In this article, for predicting the entire weld bead geometry and engineering stress–strain curve of the cold metal transfer (CMT) weldment, a MATLAB based application window (second version) is developed with certain modifications. In the first version, for predicting the entire weld bead geometry, apart from weld bead characteristics, x and y coordinates (24 from each) of the extracted points are considered. Finally, in the first version, 53 output values (five for weld bead characteristics and 48 for x and y coordinates) are predicted using both multiple regression analysis (MRA) and adaptive neuro fuzzy inference system (ANFIS) technique to get an idea related to the complete weld bead geometry without performing the actual welding process. The obtained weld bead shapes using both the techniques are compared with the experimentally obtained bead shapes. Based on the results obtained from the first version and the knowledge acquired from literature, the complete shape of weld bead obtained using ANFIS is in good agreement with the experimentally obtained weld bead shape. This motivated us to adopt a hybrid technique known as ANFIS (combined artificial neural network and fuzzy features) alone in this paper for predicting the weld bead shape and engineering stress–strain curve of the welded joint. In the present study, an attempt is made to evaluate the accuracy of the prediction when the number of trials is reduced to half and increasing the number of data points from the macrograph to twice. Complete weld bead geometry and the engineering stress–strain curves were predicted against the input welding parameters (welding current and welding speed), fed by the user in the MATLAB application window. Finally, the entire weld bead geometries were predicted by both the first and the second version are compared and validated with the experimentally obtained weld bead shapes. The similar procedure was followed for predicting the engineering stress–strain curve to compare with experimental outcomes.

Electric arc shape and weld bead geometry analysis under the electromagnetic constriction and expansion effect

2021 ◽  
Author(s):  
Miguel Guilherme Antonello ◽  
Alexandre Queiroz Bracarense ◽  
Régis Henrique Gonçalves e Silva ◽  
Ivan Olszanski Pigozzo ◽  
Marcelo Pompermaier Okuyama
Keyword(s):  
Electric Arc ◽  
Weld Bead ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Arc Shape ◽  
Geometry Analysis ◽  
Expansion Effect

A Model for In-Process Control of Thermal Properties During Welding

1989 ◽  
Vol 111 (1) ◽  
pp. 40-50 ◽  
Author(s):  
C. C. Doumanidis ◽  
D. E. Hardt
Keyword(s):  
Process Control ◽  
Thermal Response ◽  
Weld Bead ◽  
Distributed Parameter ◽  
Bead Geometry ◽  
Actual Process ◽  
Weld Bead Geometry ◽  
Thermally Activated ◽  
Real Time Tracking ◽  
Welding Processes

The control of welding processes has received much attention in the past decade, with most attention placed on real-time tracking of weld seams. The actual process control has been investigated primarily in the context of weld bead geometry regulation, ignoring for the most part the metallurgical properties of the weld. This paper addresses the latter problem through development of a model for in-process control of thermally activated material properties of weld. In particular, a causal model relating accessible inputs to the outputs of weld bead area, heat affected zone width, and centerline cooling rate at a critical temperature is developed. Since the thermal system is a distributed parameter, nonlinear one, it is modelled numerically to provide a baseline of simulation information. Experiments are performed that measure the thermal response of actual weldments and are used to calibrate the simulation and then to verify the basic dynamics predicted. Simulation results are then used to derive a locally linear transfer function matrix relating inputs and outputs. These are shown to be nonstationary, depending strongly upon the operating point and the boundary conditions.

Predicting Bead Geometry of 2F-Fillet Joint Welded by Small Wire SAW

2012 ◽  
Vol 576 ◽  
pp. 185-188 ◽  
Author(s):  
Shahfuan Hanif Ahmad Hamidi ◽  
Abdul Ghalib Tham ◽  
Yupiter H.P. Manurung ◽  
Sunhaji Kiyai Abas
Keyword(s):  
Welding Current ◽  
Weld Bead ◽  
Welding Parameter ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
Absolute Deviation ◽  
Fillet Weld ◽  
Welding Condition ◽  
Code Of Practice ◽  
The Cost

The cost of development of WPS will be very expensive if the welding parameter is selected based on trial and error. Optimal welding condition cannot be easily guessed unless the operator has records of good welding. If a calculator that can predict the welding parameter for the desired bead geometry accurately, such tool will be extremely useful for any fabrication industry. This paper intends to investigate the correlation between the welding parameter and weld bead geometry of 2F position T-fillet carbon steel, when welded by 1.2 mm diameter wire submerged arc welding. Keeping only one parameter as variable, 2F fillet weld coupons are welded by SAW with a range of welding current, welding voltage and welding speed. Only weld bead geometry that complied with the quality requirement of code of practice AWS D1.1 is considered. The trendline graph is created to fit the correlation between the heat input and the fillet weld geometry. By incorporating the trendline formulas into the calculator, the weld bead geometry can be predicted accurately for any welding parameter. The mean absolute deviation (MAD) between the predicted geometry and the experimental results is less than 0.50mm.

Sign in / Sign up

Export Citation Format

Share Document