Journal of Welding Science

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This paper reports the applicability of fuzzy logig (FL) to predict the hardness of melt zone (HMZ) during the gas metal arc welding (GMAW) process, which is affected by the combined effect of ZrO₂ nano-particles and welding input parameters. The arc voltage, welding current, welding speed, stick-out, and ZrO₂ nano-particles were used as the input parameters and HMZ as the response to develop FL model. The predicted results from FL were compared with the experimental data. The most important input parameter affecting the HMZs was the addition of ZrO₂ nanoparticle coatings with a thickness of 1 mm, which increased the hardness from 78 to 84 HRB. The correlation factor value obtained was 99.98% between the measured and predicted values of HMZ. The results showed that FL is an accurate and reliable technique for predicting HMZ because of its low error rate. Also, the presence of ZrO₂ nano-particles in the weld pool has increased the penetration up to 2 times.
 

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Single phase brass strips with 2 mm thickness were severely deformed through 1 and 3 cycles of accumulative roll bonding process (ARB). ARB process effectively increased the hardness, yield strength, and the ultimate strength of the processed materials. The hardness of processed material increased from 95 HV in annealed material to 225 HV in 3 cycle ARBed material, and the yielding and ultimate strengths increased more than 5 and 2 times of the annealed sample, respectively. Friction stir welding (FSW) process was successfully conducted on the annealed and ARBed samples to investigate and compare the microstructure and the mechanical properties of the joints obtained in bead on plate configuration. Microstructural observations showed that very fine dynamically recrystallized grains developed in the stir zones (SZs) of all welded samples. Mechanical properties were evaluated by hardness and tensile testing. Hardness test for the ARBed and FS welded samples showed that the hardness value decreased by 110 Hv in the resultant SZs. Results of tensile testing revealed that yield and ultimate strength of the FS welded ARBed samples 1.3 and 1.8 times are greater than that of the annealed FS welded sample .

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The structural and hardness developed in advanced high-strength steel DP590 have been investigated with the help of optical microscopy and scanning electron microscopy on resistance spot welded specimens. The hardness diagram of the weld sections was prepared by microhardness test and the temperature peak and heat distribution were simulated by menas of the Abaqus software. The results show that according to the temperature generated in each region of the weld nugget, the HAZ and base metals have different microstructures, and these difference affects the hardness of the regions. The presence of tempered martensite islands with a fraction of 44% in ferrite matrix in base metal, mainly martensitic structure in the nugget, and martensitic structure along with scattered areas of ferrite in the HAZ was observed. The results of the microhardness tests showed difference in hardness values of the regions, and also it was observed that the hardness values increased in the HAZ and weld zone. The hardness values measured in the nugget, base metal, and HAZ were around 400, 200, and 450 HV which were in accordance with the observed structures

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The surface of continuous casting moulds with high number of castings may be worn or destructed. As result, an approach for increasing these moulds life is necessary. In this project, the goal is the restoration of the DHP copper sample. In this project, the destruction of the copper sample is done by creation of groove using a CNC machine. The restoration of the sample is done using OAW and filler to fill groove area. In this project, the effect of preheating temperature, filler type and heat treatment of welding area on hardness, microstructure, chemical analyses of welding area and thermal conductivity of the weld are investigated. The preheating temperature range of 300 to 450^oC was selected. The Cu-P and Cu-Ag-P fillers were chosen to fill the groove of the weld area. The scanning electron microscope (SEM), energy dispersive x-ray spectroscopy (EDS), micro hardness tester, optical microscope and thermal conductivity meter were employed for evaluation of the results in this project. The results showed that the increase of preheating temperature creates oxide layers and the decrease of preheating temperature causes the incomplete filling of the welding area. Finally, the preheating temperature of 400 ^oC was a proper choice considering the above mentioned factors. The stress relieving operation to decrease stress and preserve the mechanical properties in the temperature of 250 to 400 ^oC and duration two hours was carried out. The result demonstrated that the selected temperature causes no unwanted decrease on the hardness. It was also found that increasing the annealing duration, decreases the hardness of weld for Cu-P filler for Cu-Ag-P filler increasing the annealing duration, first decreases the weld hardness and then increases the weld hardness. The Cu-P filler was compared with Cu-Ag-P filler. The results showed that the Cu-Ag-P filler has less hardness (around 10 percent) than the filler without silver. On the other hand, the thermal conductivity of the Cu-Ag-P filler was around 10 percent more than the thermal conductivity of the Cu-P. It is obvious that the selection of the filler type depends on the type of base metal and its geometry. The results showed that the segregation in the Cu-P filler with 7.2 percent phosphorous, because of the proximity of the weld structure to the eutectic point, has slightly happened; while, the selection of the Cu-Ag-P filler with 6 percent silver caused severe segregation of silver to 90 percent silver at the center of weld at the non-dendrite area

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One of the novel ultrasonic phased array based scanning methods for ultrasonic imaging in non-destructive test is total focusing method (TFM). This method employs maximum available information of the phased array elements and leads to an improved defect detection accuracy compared to conventional scanning methods. Despite its high detection accuracy, TFM behaves weak in distinguishing the real defects from noise which is because of its high background noise level. In this paper, a low complexity technique is presented for performance improvement of TFM which employs a beamforming method on the phased array received signals and leads to a reduction of the background noise and increase in the accuracy of the defect detection. To this end, a thresholding technique along with three-level clipping of the array received data is applied for low-complexity approximation of the correlation matrix inverse employed in the beamforming. Experimental results for detection of drilled holes on a steel pipe show a background noise reduction of 4.45 dB and improvement in the hole distinction of about 3 dB in comparison to those of TFM. In addition, as shown in the simulation results, the minimum distinguishable distance between two neighbor reflector points for the proposed method is 0.21 mm which is 0.23 mm lower than that for TFM.

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Nowadays, aluminum and its alloys have extensive applications in marine and aerospace industrious owing to their excellent properties. Among these alloys, 5xxx series of aluminum alloys have also excellent corrosion resistance, high toughness and strength and also good weldability. Decrease in yield strength and also tensile strength due to the grain growth in the heat affected zone is of the main problems in the welding of these series of Al alloys. In this research work, gas tungsten arc weld joints in two modes i. e. direct current and pulsed current were compared in order to study the effect of this parameter on the microstructure, mechanical properties and corrosion resistance of weld joints. Also, the effect pulsed current parameters such as peak current and basic current were investigated. Microstructural evolutions and fracture surfaces of weld joints were examined by optical microscope and scanning electron microscope, respectively. It was found that the fracture behavior of all joints is in a ductile manner. Also, tensile test and electrochemical polarization were conducted in order to study the mechanical properties and corrosion behavior of weld joints.

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The non-continuous laser beam in pulsed lasers allows the mechanical peening between two consecutive beams on a still hot weld bead. At a very short time (20, 150 and 300 ms) after laser pulse application, mechanical peening was performed on the welding bead. To achieve these short times, the light sensor detects the nth laser pulse and the mechanical arm starts moving. Upon reaching the tip of the pin near the workpiece, the n + 1th pulse was irradiated to the workpiece surface, and so the pin impact to the weld bead after traveling a short distance. Desirable mechanical properties were obtained at the highest time (300 ms) and highest pressure (6 bars). In this time and pressure the weld beads were not broken due to bending forces of peening.

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Nowadays, the use of advanced high strength steels (AHSSs) in body-in-white is one of the hot applied strategies which is followed by the most of the automakers. The study of weldability and weld challenges facing these steels in resistance spot welding process as the most widely used process in the assembly lines of the automotive industry is essential to use the outstanding mechanical responses of AHSSs. This study can result in improvement of mechanical performance of the resistance spot welds of AHSSs. Our results indicate that AHSSs experiences different welding challenges which this work aims to study them by discussing their causes, mechanisms involved and potential ways to address them.

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The aim of this study is to investigate the effect of rotary frictional welding process variables on microstructure, mechanical and physical properties of copper-aluminum dual-tube pipes. For this purpose, using a thermosetting friction welding machine, a copper pipe (99.44% purity) with a similar diameter aluminum tube (1050), was welded in three different conditions with different friction pressures and forging, and then by metallographic, hardening and microstructural testing it placed. The results of this study showed that with increasing friction pressure from 10 and 15 Bar respectively, in the interconnected phase, fuzzy interclass metal samples were created and caused a great loss in the deformation percentage and tensile strength of the interconnected sample. Also, with the reduction of frictional pressure and the removal of forging pressures down to 5 Bar, there is no proper bond between the two samples and formed in the interface between porosity and cracking. The most suitable result for the microstructure, mechanical and physical properties of the samples is in tubes with an outside diameter of 15 mm and an inner diameter of 10 mm, for samples having a friction pressure of about 10 Bar and a forge pressure of 15 Bar. The presence of intermetallic Al-Cu phases such as CuAl₂, due to higher electrical resistance and ceramic nature, increases the electrical resistance of the joint and, on the other hand, the presence of cracks and pores has reduced the flow rate and eventually increased electrical resistance of the samples

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In this investigation, the AISI 2205 duplex stainless steel was welded in the form of bead on plate by A-TIG process with different amount of the ZrO2 and TiO2 activated fluxes. The results of the visual inspection showed that the specimen with 50% ZrO2 and 50% TiO2 activated flux, had the lowest face width and the specimen with contains 90% ZrO2 activated flux, had the highest penetration depth. Also, the results showed that the angular distortion of the specimens with mix of the ZrO2 and TiO2 activated flux were 225% less than the specimen without activated flux. The results of macroscopic examination of different samples showed that the maximum length and width of the macroscopic grains were related to the sample with 90% ZrO2 activated flux and the smallest length and width of the macroscopic grains were related to the sample with 90% TiO2 activated flux. The hardness test results showed that the highest hardness of the samples was gained to 90% TiO2 activated flux specimen with 950 HV and the lowest hardness value for the sample with 90% ZrO2 activated flux with 410 HV. The results of all tests showed that surface activated fluxes (ZrO2 and TiO2) affected to the depth of penetration, face width, angular distortion, length and width of macroscopic grains and the hardness of weld metal by changing the longitudinal and transverse melt flow in the weld pool.

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In this paper, the experimental investigation of formability of friction stir welded ultra-thin sheets of IF steel is investigated experimentally. First, the sheets are joined by friction stir welding process based on the tests determined according to the Taguchi design of experiments. The investigated parameters in the welding process are as tool rotational and traverse speeds. Then, the tailor welded blanks are formed based on dome height test up to the defect stage and the dome height is measured for each test. Therefore, the effects of friction stir welding process parameters on formability of friction stir welded ultra-thin sheets of IF steel are evaluated. The results show that by increasing the rotational speed, the dome height in forming process decreases, while with increasing the traverse speed, the formability of tailor welded blanks by friction stir welding process improves.  Also, the results of optimization based on signal to noise ratio method show that the tool rotational speed has the greatest effect on the dome height of tailor welded blank. 
 

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In this study, the temperature in friction stir welding of duplex stainless steel has been investigated. At first, temperature estimation was modeled and estimated at different distances from the center of the stir zone by the multivariate Lagrangian function. Then, the linear extrapolation method and multiple linear regression method were used to estimate the temperature outside the range and center of the stir zone. Temperature estimation is based on three parameters rotational speed, welding speed and distance from the center of stir zone. In the first method, by generalizing the multivariate Lagrangian method, the multivariate Lagrangian temperature function was generalized according to the above parameters. In the second method, in order to investigate the effect of the variables in the regression model, a comparison of two complete models and a reduced model based on the sum of squares errors was used. Then, by analyzing the multiple regression equations governing the output variable, a multiple linear regression function was introduced. Since the temperature of the stir zone is not measurable by the thermocouple, so in general the best fit curve for estimating the function is when the modeling is based on parameters that minimize the error function.To implement the multiple linear regression method, the error function was introduced to minimize the sum of the error squares and the error derivative was calculated in relation to the parameters of tool rotation speed, welding speed and distance from the center of the stir zone. Therefore, multiple linear regression method was considered as the basic method and as a criterion with other methods. According to the results obtained from the prediction in the center of the stir zone, the temperature difference in all three methods is desirable and negligible. The maximum temperature difference of multiple linear regression method with multivariate Lagrangian method in all nodes was 18.8 ^oC and multiple linear regression method with linear extrapolation method was 26.36 ^oC. Therefore, the multivariate Lagrangian interpolation method is less different than the linear extrapolation method in the center of the stir zone and is more accurate.

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In this paper, ultrasonic welding of glass fiber reinforced thermoses, co-cured whit a thermoplastic has been studied. Co-curing process forms a connection between the thermoset and the thermoplastic while curing the composite. Considering that the calculated stress should not be related to the dimensions of the sample, a horn with a tip dimension smaller than the standard overlap was used. The results show that the actual weld dimensions are bigger than the intended weld dimensions. This has happened due to the movement of the melted thermoplastic to the sideways during the welding. The design of experiment has been done using response surface central composite, and a quadratic equation based on the lap shear strength of the welds containing three principle parameters time, force and amplitude was suggested, as well as predicting the optimum values. The equation shows that the force is an insignificant factor. In the samples with a higher time value the thermosetting resin started to degrade. The dominant failure mode of the specimens is segregation between the thermoset and fibers. The results show that the optimum parameters can result in a lap shear strength of 28.2 MPa, which is a very decent value compared to other methods of joining.
 

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Resistance Spot Welding (RSW) is one of the effective manufacturing processes used widely for joining sheet metals. Prediction of weld strength of welded samples has great importance in manufacturing and different methods are used by researchers to find the fracture force. In this article, the Adaptive Neuro-Fuzzy Inference System (ANFIS) is utilized for prediction of joint strength in welded samples by RSW. A design of experiments (DOE) is prepared according to effective process parameters includes welding current, welding cycle, cooling cycle and electrode force. The sheet metal samples prepared from AISI 1075 carbon steel. Tensile test specimens are prepared and the tensile-shear strength of welded samples are measured. A model is developed according to ANFIS and trained according to teaching-learning based optimization algorithm. 70 % of test data used for network train and the remained 30 % used for access the accuracy of trained network. The accuracy of the trained network was assessed and the results show that the trained network can predict the joint strength with high accuracy. The determination factor (R²) and mean absolute percentage error (MAPE) are 0.99 and 0.48 % for trained data and 0.95 and 6.2% for test data.