Melt flow and microstructural characteristics in beam oscillation superimposed laser welding of 304 stainless steel

Li, Junzhao; Liu, Yibo; Zhen, Zuyang; Sun, Qing; Feng, Jicai

doi:10.1016/j.jmapro.2019.12.053

Cited by 57 publications

(28 citation statements)

References 16 publications

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“…Laser welding is considered a preferable method to achieve the joining of medium plates, given its advantages of high power density, low heat input, deep penetration, narrow heat affected zone, and excellent mechanical properties [3,4]. However, some weld defects such as underfill, crack, and porosity easily occur in laser welding [5,6].…”

Section: Introductionmentioning

confidence: 99%

Penetration Depth Prediction of Infinity Shaped Laser Scanning Welding Based on Latin Hypercube Sampling and the Neuroevolution of Augmenting Topologies

2021

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This paper builds an infinity shaped (“∞”-shaped) laser scanning welding test platform based on a self-developed motion controller and galvanometer scanner control gateway, takes the autogenous bead-on-plate welding of 304SS with 3 mm thick specimens as the experimental objects, designs the experimental parameters by the Latin hypercube sampling method for obtaining different penetration depth welded joints, and presents a methodology based on the neuroevolution of augmenting topologies for predicting the penetration depth of “∞”-shaped laser scanning welding. Laser power, welding speed, scanning frequency, and scanning amplitude are set as the input parameters of the model, and welding depth (WD) as the output parameter of the model. The model can accurately reflect the nonlinear relationship between the main welding parameters and WD by validation. Moreover, the normalized root mean square error (NRMSE) of the welding depth is about 6.2%. On the whole, the proposed methodology and model can be employed for guiding the actual work in the main process parameters’ preliminary selection and lay the foundation for the study of penetration morphology control of “∞”-shaped laser scanning welding.

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Section: Introductionmentioning

confidence: 99%

Penetration Depth Prediction of Infinity Shaped Laser Scanning Welding Based on Latin Hypercube Sampling and the Neuroevolution of Augmenting Topologies

2021

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“…The alloy 304 austenitic stainless steel has good corrosion resistance, as well as robust mechanical properties at high temperatures and aggressive environments [ 1 , 2 , 3 ]. Due to its superior properties, 304 stainless steel has been used in a variety of fields, including marine service, power plant, the nuclear sector, oil industries, etc.…”

Section: Introductionmentioning

confidence: 99%

“…Due to its superior properties, 304 stainless steel has been used in a variety of fields, including marine service, power plant, the nuclear sector, oil industries, etc. [ 1 , 2 , 3 , 4 ]. Correspondingly, the deformation characteristics and mechanical properties of 304 stainless and other austenitic stainless steel under various environments have represented one of the major research topics in the field.…”

Section: Introductionmentioning

confidence: 99%

Random Forest Approach in Modeling the Flow Stress of 304 Stainless Steel during Deformation at 700 °C–900 °C

Song

2021

Materials

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The alloy 304 stainless steel is used in a wide variety of industrial applications. It is frequently applied in tough environments, such as those involving high temperatures, low temperatures, and corrosive environments. Hence, research on the flow stress behavior of the alloy during deformation under tough environments is critically important to achieving the maximum effectiveness in the application of the alloy. This research presents a study on the flow stress of 304 stainless steel during hot deformation at the temperatures of 700 ℃–900 ℃ under the strain rates ranging from 0.0002/s–0.02/s. For this study, hot tensile experiments are conducted, and the flow stress variations of the alloy are studied with respect to the variations in the strain rate and temperature. Next, the stress behavior was modeled by the traditional Arrhenius-type constitutive equation and random forest algorithm. Then, the flow stresses predicted by different methods were studied by comparing errors. The results showed that the flow stress was modeled more accurately by the random forest algorithm.

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“…inlet-/outlet tubes of catalysts and filters [25]. Novel trends showed that high-frequency welding could be used as a joining process for these applications [26,27]. However, the TIG process is most often used.…”

Section: Introductionmentioning

confidence: 99%

Influence of Tack Welds Distribution and Welding Sequence on the Angular Distortion of Tig Welded Joint

Tomków

Sobota²,

Krajewski

2020

FU Mech Eng

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In this paper the influence of tack welds distribution and welding sequence on angular distortion of the Tungsten Inert Gas (TIG) welded joint was tested. Additionally, the effect of welding current on angular distortion was assessed. For research X2CrTiNb18 (AISI 441) stainless steel (2.5 mm thick) was chosen. During research specimens were prepared with different distributions of tack welds. Then they were welded by different welding sequences with the use of different welding current values. After welding the angular distortion of each specimen was measured by using the coordinate measuring machine. In the next step specimens were cut. Cross-sections were polished and the metallographic macroscopic testing was conducted to check the geometry of performed welds. Performed experiments allowed determining the optimal tack weld sequence and welding parameters for welding thin stainless steel sheets.

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Melt flow and microstructural characteristics in beam oscillation superimposed laser welding of 304 stainless steel

Cited by 57 publications

References 16 publications

Penetration Depth Prediction of Infinity Shaped Laser Scanning Welding Based on Latin Hypercube Sampling and the Neuroevolution of Augmenting Topologies

Penetration Depth Prediction of Infinity Shaped Laser Scanning Welding Based on Latin Hypercube Sampling and the Neuroevolution of Augmenting Topologies

Random Forest Approach in Modeling the Flow Stress of 304 Stainless Steel during Deformation at 700 °C–900 °C

Influence of Tack Welds Distribution and Welding Sequence on the Angular Distortion of Tig Welded Joint

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