scholarly journals Effect of Polarity and Oxide Fluxes on Weld-bead Geometry in Activated Tungsten Inert Gas (A-TIG) Welding

2020 ◽  
Vol 38 (4) ◽  
pp. 380-388
Author(s):  
Suman Saha ◽  
Santanu Das
Keyword(s):  
Weld Bead ◽  
Tig Welding ◽  
Inert Gas ◽  
Bead Geometry ◽  
Weld Bead Geometry ◽  
A Tig Welding ◽  
Effect Of Polarity

Performance of weld bead profile during A-TIG welding on nitrogen alloyed stainless steel

2021 ◽  
Author(s):  
Akash Deep ◽  
Vivek Singh ◽  
Som Ashutosh ◽  
M. Chandrasekaran ◽  
Dixit Patel
Keyword(s):  
Stainless Steel ◽  
Welding Process ◽  
Weld Bead ◽  
Tig Welding ◽  
Inert Gas ◽  
Bead Geometry ◽  
Depth Of Penetration ◽  
Weld Bead Geometry ◽  
A Tig Welding ◽  
Arc Welding Process

Abstract Austenitic stainless steel (ASS) is widely fabricated by tungsten inert gas (TIG) welding for aesthetic look and superior mechanical properties while compared to other arc welding process. Hitherto, the limitation of this process is low depth of penetration and less productivity. To overcome this problem activated tungsten inert gas (A-TIG) welding process is employed as an alternative. In this investigation the welding performance of conventional TIG welding is compared with A-TIG process using TiO2 and SiO2 flux with respect to weld bead geometry. The experimental investigation on A-TIG welding of ASS-201 grade shows TiO2 flux helps in achieve higher penetration as compared to SiO2 flux. While welding with SiO2 the hardness in HAZ and weld region higher than that of TIG welding process.

scholarly journals Optimization of Activated Tungsten Inert Gas Welding Process Parameters Using Heat Transfer Search Algorithm: With Experimental Validation Using Case Studies

Metals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 981
Author(s):  
Jay Vora ◽  
Vivek K. Patel ◽  
Seshasai Srinivasan ◽  
Rakesh Chaudhari ◽  
Danil Yurievich Pimenov ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Case Studies ◽  
Process Parameters ◽  
Optimization Technique ◽  
Carbon Steels ◽  
Weld Bead ◽  
Tig Welding ◽  
Inert Gas ◽  
Tungsten Inert Gas Welding ◽  
A Tig Welding

The Activated Tungsten Inert Gas welding (A-TIG) technique is characterized by its capability to impart enhanced penetration in single pass welding. Weld bead shape achieved by A-TIG welding has a major part in deciding the final quality of the weld. Various machining variables influence the weld bead shape and hence an optimum combination of machining variables is of utmost importance. The current study has reported the optimization of machining variables of A-TIG welding technique by integrating Response Surface Methodology (RSM) with an innovative Heat Transfer Search (HTS) optimization algorithm, particularly for attaining full penetration in 6 mm thick carbon steels. Welding current, length of the arc and torch travel speed were selected as input process parameters, whereas penetration depth, depth-to-width ratio, heat input and width of the heat-affected zone were considered as output variables for the investigations. Using the experimental data, statistical models were generated for the response characteristics. Four different case studies, simulating the real-time fabrication problem, were considered and the optimization was carried out using HTS. Validation tests were also carried out for these case studies and 3D surface plots were generated to confirm the effectiveness of the HTS algorithm. It was found that the HTS algorithm effectively optimized the process parameters and negligible errors were observed when predicted and experimental values compared. HTS algorithm is a parameter-less optimization technique and hence it is easy to implement with higher effectiveness.

Finite Element Simulation of A-TIG Welding of Duplex Stainless Steel 2205 Using SYSWELD

2014 ◽  
Vol 592-594 ◽  
pp. 374-379 ◽  
Author(s):  
Korra Nanda Naik ◽  
K.R. Balasubramanian ◽  
M. Vasudevan
Keyword(s):  
Finite Element ◽  
Stainless Steel ◽  
Temperature Distribution ◽  
Duplex Stainless Steel ◽  
Weld Bead ◽  
Tig Welding ◽  
Transient Temperature ◽  
Bead Geometry ◽  
A Tig Welding ◽  
Bead Profile

Bead on plate activated tungsten inert gas (A-TIG) welding of duplex stainless steel (DSS) 2205 was performed to determine the thermal history, temperature distribution and the weld bead geometry. Finite element (FE) simulations were carried out using the software, SYSWELD considering the temperature dependent thermal and mechanical properties of the base material. A 3D double ellipsoidal heat source was employed for the non-linear thermal analysis. The transient temperature distribution, weld bead profile, weld bead dimensions, depth of penetration and bead width were calculated by FE simulation. The simulated weld bead profile was compared with the experimentally measured profile and found to be in agreement.

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.

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