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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.read more
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Ultrasonic spot welding of a clad 7075 aluminum alloy: Strength and fatigue life
TL;DR: In this paper, the authors examined weldability of an AA7072-cladded high-strength AA7075-T6 via ultrasonic spot welding, focusing on the influence of welding energy on mechanical properties and failure mechanisms.
Journal Article
The effect of activating fluxes on 316l stainless steel weld joint characteristic in tig welding using the taguchi method
E. Ahmadi,A. R. Ebrahimi +1 more
TL;DR: In this paper, the effect of activating flux on the TIG welding process was investigated and the optimal parameters were determined using the Taguchi method with L9 (3) orthogonal array.
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Prediction of element transfer due to flux and optimization of chemical composition and mechanical properties in high-strength low-alloy steel weld
TL;DR: The transfer of elements C, Si, Mn, P and S from slag into the weld metal or from weld metal into the slag and microhardness has been studied using formulated fluxes.
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In situ strain investigation during laser welding using digital image correlation and finite-element-based numerical simulation
TL;DR: In situ strain evolution during laser welding has been measured by means of digital image correlation to assess the susceptibility of an advanced high strength automotive steel to solidification cracking as mentioned in this paper, and a novel method realised using auxiliary illumination and optical narrow bandpass filter allowed strain measurements as close as 1.5 mm from the fusion boundary with good spatial and temporal resolution.
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Effect of filler metal and post-weld friction stir processing on stress corrosion cracking susceptibility of Al–Zn–Mg arc welds
TL;DR: In this paper, the authors investigated the detrimental effect of T phase precipitates on cracking initiation of gas metal arc welds and showed that T phase precipitation at the weld toe was correlated to stress corrosion cracking in the lap joints of aluminium alloy (AA) 7003 (Al-Zn-Mg) welded with AA 5356 (Almg) type filler wire.
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
Leifeng Liu,Qingqing Ding,Yuan Zhong,Ji Zou,Jing Wu,Yu-Lung Chiu,Jixue Li,Ze Zhang,Qian Yu,Zhijian Shen +9 more
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.