Machine learning-based characterization of friction stir welding in aluminum alloys

IF 2.7 4区 材料科学 Q3 ENGINEERING, CHEMICAL
Chanjuan Chen
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引用次数: 0

Abstract

This research presents a machine learning (ML) approach that integrates Bayesian theorem to predict residual stress, plastic deformation, and peak temperature in friction stir welding (FSW) of diff...
基于机器学习的铝合金搅拌摩擦焊特性分析
本研究提出了一种机器学习(ML)方法,该方法结合了贝叶斯定理,可预测不同材料的搅拌摩擦焊(FSW)中的残余应力、塑性变形和峰值温度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Adhesion Science and Technology
Journal of Adhesion Science and Technology 工程技术-材料科学:综合
CiteScore
5.10
自引率
13.00%
发文量
136
审稿时长
4.1 months
期刊介绍: Journal of Adhesion Science and Technology ( JAST) provides a forum for the basic and applied aspects of adhesion, chemistry of adhesives, coatings and sealants, and structure-properties relationships in adhesive joints and deals with applications of adhesion principles in all areas of technology.
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