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Welding Metallurgy of

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The article was published on 1987-01-01 and is currently open access. It has received 991 citations till now. The article focuses on the topics: Welding.

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Citations
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Development of Artificial Neural Network Models for Predicting Weld Output Parameters in Advanced Fusion Welding of a Magnesium Alloy

TL;DR: In this paper, artificial neural network (ANN) models and multi-response optimization technique were used to predict and select the best welding parameters during Hybrid Laser Arc Welding (HLAW), Hot Wire Cladding (HWC) and Cold Metal Transfer (CMT) of ZE41-T5 alloy.
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Assessment of Inter-granular Corrosion Susceptibility of 304L Stainless Steel Using Non-destructive Electrochemical Techniques

TL;DR: In this paper, the effect of heat treatment on the corrosion resistance of 304L stainless steel was studied and the extent of sensitization was quantitatively evaluated using double loop electrochemical potentiodynamic reactivation test.
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Fatigue strength analysis of welded joints using an experimental approach based on static characterization tests

TL;DR: In this article, Khatib et al. proposed an approach to estimate the fatigue life of the weld bead, which is based on the local deformations approach (-N) that requires fatigue parameters related to material strength.
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Fatigue Life Behaviour of Transverse Fillet Weld and Transverse Fillet on Weld of the HSLA S460G2+M Followed by HFMI/PIT

TL;DR: In this article, the authors dealt with the fatigue life assessment of the transverse fillet weld and transverse weld on weld fatigue specimen of the offshore steel S460G2+M with a thickness of 10 mm.
References
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A review on selective laser sintering/melting (SLS/SLM) of aluminium alloy powders: Processing, microstructure, and properties

TL;DR: In this article, the state of the art in selective laser sintering/melting (SLS/SLM) processing of aluminium powders is reviewed from different perspectives, including powder metallurgy (P/M), pulsed electric current (PECS), and laser welding of aluminium alloys.
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Dislocation network in additive manufactured steel breaks strength–ductility trade-off

TL;DR: In this article, the authors show that the pre-existing dislocation network, which maintains its configuration during the entire plastic deformation, is an ideal modulator that is able to slow down but not entirely block the dislocation motion.
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Critical review of automotive steels spot welding: process, structure and properties

TL;DR: In this article, the fundamental understanding of structure-properties relationship in automotive steels resistance spot welds is discussed. And a brief review of friction stir spot welding, as an alternative to RSW, is also included.
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Revisiting fundamental welding concepts to improve additive manufacturing: From theory to practice

TL;DR: In this article, a unified equation to compute the energy density is proposed to compare works performed with distinct equipment and experimental conditions, covering the major process parameters: power, travel speed, heat source dimension, hatch distance, deposited layer thickness and material grain size.
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Using deep neural network with small dataset to predict material defects

TL;DR: This study attempted to predict solidification defects by DNN regression with a small dataset that contains 487 data points and found that a pre-trained and fine-tuned DNN shows better generalization performance over shallow neural network, support vector machine, and DNN trained by conventional methods.