Welding Metallurgy of
01 Jan 1987-
About: 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.
Citations
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29 Aug 2021
TL;DR: In this paper, wire plus arc additive manufacturing (WAAM) technology with higher deposition rate and efficient material utilization was employed to fabricate a stainless steel 321 (SS 321) wall for the first time.
Abstract: Wire plus arc additive manufacturing (WAAM) technology with higher deposition rate and efficient material utilization was employed to fabricate a stainless steel 321 (SS 321) wall for the first tim...
5 citations
TL;DR: In this article, an Artificial Neural Network (ANN) model is developed for the analysis of the correlation between the friction welding parameters and tensile strength of both AISI 316 austenitic-stainless steel and Ck 45 steel.
Abstract: The optimization of the friction welding parameters through experimental studies does not only cause loss of time and materials but also increases the cost. In this study, an Artificial Neural Network (ANN) model is developed for the analysis of the correlation between the friction welding parameters and tensile strength of both AISI 316 austenitic-stainless steel and Ck 45 steel. The input parameters of the model are friction time, friction pressure and upset pressure while tensile strength is the output. Experimental data are used to train and test the neural network. A good correlation was obtained between the experimental values and the ANN model prediction (R = 0.9711). By using this model, the number of experiments to obtain optimal parameters of friction welding and number of tensile tests could be minimized. K e y w o r d s: friction welding, AISI 316 stainless steel, Ck 45 steel, mechanical properties, Artificial Neural Network (ANN)
5 citations
DOI•
01 Jan 2016
TL;DR: In this paper, the authors present a Table of Table of contents of the paper "A.K.A., Table of Contents" and a table of the authors' abstracts.
Abstract: ................................................................................................................................................ ii Preface .................................................................................................................................................. iii Table of
5 citations
Cites background from "Welding Metallurgy of"
...3 (a) The configuration of the circular patch test, and (b) the Houldcroft susceptibility test [7]....
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...1 (a) The distribution of the growth rate and the temperatur different growth modes within a single columnar grain in the weld pool [7]....
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...Several factors are reported to affect the formation of hot cracks during welding [7]....
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...The process of solidification plays a key role in the final microstructure and properties that result from fusion welding [7]....
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...Higher voltage and current values increase the heat input since they directly increase the power applied to the system, whereas higher welding speeds reduce the heat input [7] since this will increase the volume of material over which the power is applied....
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06 Apr 2021
TL;DR: Abdulaziz Albannai, Abdulkareem Aloraier, Ayman Alaskari, Meshal Alawadhi, Suraj Joshi2 1 Department of Manufacturing and Welding Engineering Technology, College of Technological Studies, PAAET, Shuwaikh 70654, Kuwait City, Kuwait as mentioned in this paper.
Abstract: Abdulaziz Albannai1, Abdulkareem Aloraier1, Ayman Alaskari1, Meshal Alawadhi1, Suraj Joshi2 1Department of Manufacturing and Welding Engineering Technology, College of Technological Studies, PAAET, Shuwaikh 70654, Kuwait City, Kuwait. E-mail: ai.albannai@paaet.edu.kw; as.aloraier@paaet.edu.kw; am.alaskari@paaet.edu.kw; my.alawadhi@paaet.edu.kw 2Department of Mechanical and Industrial Engineering, Concordia University, 1515 St. Catherine Street West, Montréal, Québec, Canada. E-mail: suraj.joshi@concordia.ca
5 citations
TL;DR: In this article, the authors describe the complex, augmented accuracies required and high-speed material combining process for CO2 laser beam welding (LBW) which is one of the complex and high speed material combining processes.
Abstract: CO2 laser beam welding (LBW) is one of the complex, augmented accuracies required and high-speed material combining process. To combine different materials such as stainless steels, carbon steels, ...
5 citations
References
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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.
1,172 citations
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.
557 citations
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.
Abstract: Spot welding, particularly resistance spot welding (RSW), is a critical joining process in automotive industry. The development of advanced high strength steels for applications in automotive industry is accompanied with a challenge to better understand the physical and mechanical metallurgy of these materials during RSW. The present paper critically reviews the fundamental understanding of structure–properties relationship in automotive steels resistance spot welds. The focus is on the metallurgical characteristics, hardness–microstructure correlation, interfacial to pullout failure mode transition and mechanical performance of steel resistance spot welds under quasi-static, fatigue and impact loading conditions. A brief review of friction stir spot welding, as an alternative to RSW, is also included.
369 citations
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.
369 citations
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.
314 citations