Numerical Simulation and Artificial Neural Network Modeling for Predicting Welding-Induced Distortion in Butt-Welded 304L Stainless Steel Plates

Narayanareddy, V. V.; Chandrasekhar, N.; Vasudevan, M.; Muthukumaran, S.; Vasantharaja, P.

doi:10.1007/s11663-015-0468-x

Cited by 11 publications

(3 citation statements)

References 25 publications

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“…The employed data to construct the neural network were captured from the FEM simulation while the accuracy of numerical results was veri ed by the experiments. The same work has also been performed by Narayanareddy et al [15].…”

Section: Introductionmentioning

confidence: 63%

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Using an optimized RBF neural network to predict the out-of-plane welding distortions based on the 3-2-1 locating scheme

Tafarroj

Kolahan

2018

Scientia Iranica

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This study deals with the e ect of locator positioning in the 3-2-1 locating scheme to control the out-of-plane distortion in gas tungsten arc welding of sheet metals. To apply this locating scheme to the sheet metals, a suitable xture was designed. The distortion of the welded plates was predicted using the Radial Basis Function (RBF) neural network. To gather the experimental data employed in the RBF modeling process, a set of welding tests was performed on the sheet specimens by varying the positions of the three locators. The parameters of the network were optimally selected using the Simulated Annealing (SA) optimization algorithm. The average and maximum errors computed for the test dataset were respectively 2.43% and 5.30% while in some cases, the error fell below 1%. The results of the RBF network showed very good agreement with the experiments and it can be concluded that this modeling technique can be utilized successfully in predicting the welding distortions when the 3-2-1 locating scheme is used.

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Section: Introductionmentioning

confidence: 63%

“…The range of Sp was selected to be between [0.1,10] with the step of 10 2 . Likewise, N was set to vary between [1,15] with the step of 1. The convergence plot of the SA algorithm is illustrated in Figure 9.…”

Section: Resultsmentioning

confidence: 99%

Using an optimized RBF neural network to predict the out-of-plane welding distortions based on the 3-2-1 locating scheme

Tafarroj

Kolahan

2018

Scientia Iranica

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“…While the maximum deformation distribution changes at 4.938 * 10-4 mm. this value of deformation which occur on the top of mould (red area figure 6-b) is still in the elastic domain of the material [13][14][15][16].…”

Section: Thermal Behavior Of Blowingmentioning

confidence: 99%

Simulation and Numerical Modeling of Mechanical Properties of Stainless Steel Mold X39CrMo17-1

Issam¹,

Younes²,

Idir³

et al. 2019

RCMA

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This paper designs two molds based on stainless steel X39CrMo17-1, and studies their thermo-mechanical behavior through finite-element simulation on SolidWorks. Based on the simulation results, detailed analysis was carried out on the following aspects: the fluid distribution on the edge of each mode in a hot blowing cycle, the temperature distribution during the injection of thermoplastics, as well as the mechanical properties like deformation and stress resistances. The results show that, the two molds had no significant difference in air flow behavior at 30 bars; the variation of the airflow velocity field was less pronounced on the inner wall; the thermal stress was homogenous in both molds; the drawing rate on the inner wall was much higher than that on the outer wall; the two molds had no significant elastic deformation under 150kN. Overall, the designed molds can keep the crystallization temperatures of the polyethylene terephthalate (PET).

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Residual Stress Prediction for Butt-Welded Plate Joint with Unequal Plate Thickness Using Artificial Neural Networks

Baruah,

Sarkar,

Singh

2024

Lecture Notes in Mechanical Engineering

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Numerical Simulation and Artificial Neural Network Modeling for Predicting Welding-Induced Distortion in Butt-Welded 304L Stainless Steel Plates

Cited by 11 publications

References 25 publications

Using an optimized RBF neural network to predict the out-of-plane welding distortions based on the 3-2-1 locating scheme

Using an optimized RBF neural network to predict the out-of-plane welding distortions based on the 3-2-1 locating scheme

Simulation and Numerical Modeling of Mechanical Properties of Stainless Steel Mold X39CrMo17-1

Residual Stress Prediction for Butt-Welded Plate Joint with Unequal Plate Thickness Using Artificial Neural Networks

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