Mechanical and Sliding Wear Performance of Vacuum-Cast AA7075-Co Alloy Composites: Parametric Optimization and Ranking Analysis

IF 2.6 3区 材料科学 Q2 METALLURGY & METALLURGICAL ENGINEERING International Journal of Metalcasting Pub Date : 2024-05-31 DOI:10.1007/s40962-024-01368-8
Ashiwani Kumar, Mukesh Kumar
{"title":"Mechanical and Sliding Wear Performance of Vacuum-Cast AA7075-Co Alloy Composites: Parametric Optimization and Ranking Analysis","authors":"Ashiwani Kumar, Mukesh Kumar","doi":"10.1007/s40962-024-01368-8","DOIUrl":null,"url":null,"abstract":"<p>This research work reports on the mechanical and sliding wear performance analysis of vacuum-cast AA7075-Co (0–2 wt% @step of 0.5) alloy composites for gear application. The specimens were sized for their physical, mechanical, and sliding wear test standards. Wear tests were performed in lubricated conditions on a muti-specimen tribo-tester. The results show that reinforcement of cobalt particulates into the alloy matrix improves the mechanical properties and reduces the void content. The resultant composites have density ranges from 2.81 to 2.91 g/cc, voids content from (~ 3.55 to 2.46%), hardness from 151.2 to 196 Hv, flexural strength from 341 to 498.2 MPa, compressive strength from 290 to 490 MPa, tensile strength from 235 to 394 MPa, and impact strength from 20 to 65.5 J. The specific wear rate shows a 25% improvement in performance with cobalt reinforcement relative to neat one. The Taguchi analysis with ANOVA reveals the following parametric order of normal load, sliding velocity, sliding distance, and filler content that actively controls the wear process of such composites. Further, Preference selection index ranking methods reveal that the composition having 2 wt% cobalt reinforcement tends to optimize overall performance metrics relative to others and has validated with subjective analysis.</p>","PeriodicalId":14231,"journal":{"name":"International Journal of Metalcasting","volume":"80 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Metalcasting","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1007/s40962-024-01368-8","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METALLURGY & METALLURGICAL ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

This research work reports on the mechanical and sliding wear performance analysis of vacuum-cast AA7075-Co (0–2 wt% @step of 0.5) alloy composites for gear application. The specimens were sized for their physical, mechanical, and sliding wear test standards. Wear tests were performed in lubricated conditions on a muti-specimen tribo-tester. The results show that reinforcement of cobalt particulates into the alloy matrix improves the mechanical properties and reduces the void content. The resultant composites have density ranges from 2.81 to 2.91 g/cc, voids content from (~ 3.55 to 2.46%), hardness from 151.2 to 196 Hv, flexural strength from 341 to 498.2 MPa, compressive strength from 290 to 490 MPa, tensile strength from 235 to 394 MPa, and impact strength from 20 to 65.5 J. The specific wear rate shows a 25% improvement in performance with cobalt reinforcement relative to neat one. The Taguchi analysis with ANOVA reveals the following parametric order of normal load, sliding velocity, sliding distance, and filler content that actively controls the wear process of such composites. Further, Preference selection index ranking methods reveal that the composition having 2 wt% cobalt reinforcement tends to optimize overall performance metrics relative to others and has validated with subjective analysis.

Abstract Image

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
真空铸造 AA7075-Co 合金复合材料的机械和滑动磨损性能:参数优化和排序分析
本研究报告分析了用于齿轮应用的真空浇铸 AA7075-Co(0-2 wt% @ 步距为 0.5)合金复合材料的机械和滑动磨损性能。试样尺寸符合物理、机械和滑动磨损测试标准。在润滑条件下,在多试样三重试验机上进行了磨损试验。结果表明,在合金基体中添加钴微粒可提高机械性能并减少空隙含量。复合材料的密度范围从 2.81 到 2.91 g/cc,空隙含量从(~ 3.55 到 2.46%),硬度从 151.2 到 196 Hv,抗弯强度从 341 到 498.2 MPa,抗压强度从 290 到 490 MPa,抗拉强度从 235 到 394 MPa,冲击强度从 20 到 65.5 J。利用方差分析进行的田口分析表明,法向载荷、滑动速度、滑动距离和填料含量的参数顺序能有效控制此类复合材料的磨损过程。此外,偏好选择指数排序法显示,与其他方法相比,含有 2 wt%钴增强剂的复合材料倾向于优化整体性能指标,这一点已通过主观分析得到验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International Journal of Metalcasting
International Journal of Metalcasting 工程技术-冶金工程
CiteScore
4.20
自引率
42.30%
发文量
174
审稿时长
>12 weeks
期刊介绍: The International Journal of Metalcasting is dedicated to leading the transfer of research and technology for the global metalcasting industry. The quarterly publication keeps the latest developments in metalcasting research and technology in front of the scientific leaders in our global industry throughout the year. All papers published in the the journal are approved after a rigorous peer review process. The editorial peer review board represents three international metalcasting groups: academia (metalcasting professors), science and research (personnel from national labs, research and scientific institutions), and industry (leading technical personnel from metalcasting facilities).
期刊最新文献
Effect of Austenitization Time on Corrosion and Wear Resistance in Austempered Ductile Iron From the Editor Numerical Simulation and Experimental Investigation of Microstructure Evolution and Flow Behavior in the Rheological Squeeze Casting Process of A356 Alloy The Effect of N Content on the Microstructure and Wear Resistance of Improved High-Carbon Chromium Bearing Steel Enhanced Classification of Refractory Coatings in Foundries: A VPCA-Based Machine Learning Approach
×
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