添加剂搅拌摩擦沉积修复高强铝合金疲劳行为的多物理场预测

IF 2.4 3区 材料科学 Q3 ENGINEERING, MANUFACTURING Integrating Materials and Manufacturing Innovation Pub Date : 2023-11-01 DOI:10.1007/s40192-023-00309-3
N. I. Palya, K. A. Fraser, Y. Hong, N. Zhu, M. B. Williams, K. Doherty, P. G. Allison, J. B. Jordon
{"title":"添加剂搅拌摩擦沉积修复高强铝合金疲劳行为的多物理场预测","authors":"N. I. Palya, K. A. Fraser, Y. Hong, N. Zhu, M. B. Williams, K. Doherty, P. G. Allison, J. B. Jordon","doi":"10.1007/s40192-023-00309-3","DOIUrl":null,"url":null,"abstract":"Abstract A smooth particle hydrodynamic (SPH) simulation of an additive friction stir deposition (AFSD) repair was used to inform a multi-physics approach to predict the fatigue life of a high strength aluminum alloy. The AFSD process is a solid-state layer-by-layer additive manufacturing approach in which a hollow tool containing feedstock is used to deposit material. While an understanding of the evolving microstructures is necessary to predict material performance, the elevated temperatures and strain rates associated with severe plastic deformation processes (SPDP) make accurate collection of experimental data within AFSD difficult. Without the ability to experimentally determine material history within the AFSD process, an SPH model was employed to predict the thermomechanical history. The SPH simulation of an AFSD repair was used to inform several microstructural models to predict material history during and after processing with AFSD and a post-processing heat treatment. These microstructure models are then used to inform a mechanistic microstructure and performance model to predict the fatigue life of an AFSD repair in AA7075.","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":"18 7-8","pages":"0"},"PeriodicalIF":2.4000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-physics Approach to Predict Fatigue Behavior of High Strength Aluminum Alloy Repaired via Additive Friction Stir Deposition\",\"authors\":\"N. I. Palya, K. A. Fraser, Y. Hong, N. Zhu, M. B. Williams, K. Doherty, P. G. Allison, J. B. Jordon\",\"doi\":\"10.1007/s40192-023-00309-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract A smooth particle hydrodynamic (SPH) simulation of an additive friction stir deposition (AFSD) repair was used to inform a multi-physics approach to predict the fatigue life of a high strength aluminum alloy. The AFSD process is a solid-state layer-by-layer additive manufacturing approach in which a hollow tool containing feedstock is used to deposit material. While an understanding of the evolving microstructures is necessary to predict material performance, the elevated temperatures and strain rates associated with severe plastic deformation processes (SPDP) make accurate collection of experimental data within AFSD difficult. Without the ability to experimentally determine material history within the AFSD process, an SPH model was employed to predict the thermomechanical history. The SPH simulation of an AFSD repair was used to inform several microstructural models to predict material history during and after processing with AFSD and a post-processing heat treatment. These microstructure models are then used to inform a mechanistic microstructure and performance model to predict the fatigue life of an AFSD repair in AA7075.\",\"PeriodicalId\":13604,\"journal\":{\"name\":\"Integrating Materials and Manufacturing Innovation\",\"volume\":\"18 7-8\",\"pages\":\"0\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Integrating Materials and Manufacturing Innovation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s40192-023-00309-3\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrating Materials and Manufacturing Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40192-023-00309-3","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0

摘要

摘要采用搅拌摩擦沉积(AFSD)修复过程的光滑颗粒流体动力学(SPH)模拟,为预测高强度铝合金的疲劳寿命提供了多物理场方法。AFSD工艺是一种固态逐层增材制造方法,其中包含原料的中空工具用于沉积材料。虽然了解不断变化的微观结构对于预测材料性能是必要的,但与严重塑性变形过程(SPDP)相关的高温和应变速率使得在AFSD内准确收集实验数据变得困难。由于无法通过实验确定AFSD过程中的材料历史,因此采用SPH模型来预测热力学历史。AFSD修复的SPH模拟被用来为几个微观结构模型提供信息,以预测AFSD加工期间和之后的材料历史以及后处理热处理。然后将这些微观结构模型用于建立机械微观结构和性能模型,以预测AA7075中AFSD修复的疲劳寿命。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Multi-physics Approach to Predict Fatigue Behavior of High Strength Aluminum Alloy Repaired via Additive Friction Stir Deposition
Abstract A smooth particle hydrodynamic (SPH) simulation of an additive friction stir deposition (AFSD) repair was used to inform a multi-physics approach to predict the fatigue life of a high strength aluminum alloy. The AFSD process is a solid-state layer-by-layer additive manufacturing approach in which a hollow tool containing feedstock is used to deposit material. While an understanding of the evolving microstructures is necessary to predict material performance, the elevated temperatures and strain rates associated with severe plastic deformation processes (SPDP) make accurate collection of experimental data within AFSD difficult. Without the ability to experimentally determine material history within the AFSD process, an SPH model was employed to predict the thermomechanical history. The SPH simulation of an AFSD repair was used to inform several microstructural models to predict material history during and after processing with AFSD and a post-processing heat treatment. These microstructure models are then used to inform a mechanistic microstructure and performance model to predict the fatigue life of an AFSD repair in AA7075.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Integrating Materials and Manufacturing Innovation
Integrating Materials and Manufacturing Innovation Engineering-Industrial and Manufacturing Engineering
CiteScore
5.30
自引率
9.10%
发文量
42
审稿时长
39 days
期刊介绍: The journal will publish: Research that supports building a model-based definition of materials and processes that is compatible with model-based engineering design processes and multidisciplinary design optimization; Descriptions of novel experimental or computational tools or data analysis techniques, and their application, that are to be used for ICME; Best practices in verification and validation of computational tools, sensitivity analysis, uncertainty quantification, and data management, as well as standards and protocols for software integration and exchange of data; In-depth descriptions of data, databases, and database tools; Detailed case studies on efforts, and their impact, that integrate experiment and computation to solve an enduring engineering problem in materials and manufacturing.
期刊最新文献
New Paradigms in Model Based Materials Definitions for Titanium Alloys in Aerospace Applications An Explainable Deep Learning Model Based on Multi-scale Microstructure Information for Establishing Composition–Microstructure–Property Relationship of Aluminum Alloys Comparison of Full-Field Crystal Plasticity Simulations to Synchrotron Experiments: Detailed Investigation of Mispredictions 3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry L-PBF High-Throughput Data Pipeline Approach for Multi-modal Integration
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1