今天是2024年12月15日 星期日 ynufe 退出

Neural network application in simulations of composites Al-Al2O3 tribological properties

http://www.firstlight.cn2009/12/2

[作者] L.A. Dobrzañ ski M. Kremzer J. Trzaska A. W³ odarczyk-Fligier

[单位] Division of Materials Processing Technology, Management and Computer Techniques in Materials Science, Institute of Engineering Materials and Biomaterials, Silesian University of Technology

[摘要] Purpose: The purpose of this paper is application of neural networks in tribological properties simulation of composite materials based on porous ceramic preforms infiltrated by liquid aluminium alloy. Design…

[关键词] Computational materials science Composites Infiltration

Purpose: The purpose of this paper is application of neural networks in tribological properties simulation of

composite materials based on porous ceramic preforms infiltrated by liquid aluminium alloy.

Design/methodology/approach: The material for investigations was manufactured by pressure infiltration

method of ceramic porous preforms. The eutectic aluminium alloy EN AC – AlSi12 was use as a matrix while as

reinforcement were used ceramic preforms manufactured by sintering of Al2O3 Alcoa CL 2500 powder with addition

of pore forming agents as carbon fibres Sigrafil C10 M250 UNS manufactured by SGL Carbon Group Company.

The wear resistance was measured by the use of device designed in the Institute of Engineering Materials and

Biomaterials. The device realize dry friction wear mechanism of reciprocating movement condition. The simulation

of load and number of cycles influence on tribological properties was made by the use of neural networks.

Findings: The received results show the possibility of obtaining the new composite materials with required

tribological properties moreover those properties can by simulated by the use of neural networks.

Practical implications: The composite materials made by the developed method can find application among

the others in automotive industry as the alternative material for elements fabricated from light metal matrix

composite material reinforced with ceramic fibers.

Originality/value: Worked out model of neural network can be used as helpful tool to prediction the wear of

aluminium matrix composite materials In condition of dry friction.

存档附件原文地址

原文发布时间:2009/12/2

引用本文:

L.A. Dobrzañski;M. Kremzer;J. Trzaska;A. W³odarczyk-Fligier.Neural network application in simulations of composites Al-Al2O3 tribological propertieshttp://ynufe.firstlight.cn/View.aspx?infoid=860734&cb=zhangyingyingxg
发布时间:2009/12/2.检索时间:2024/12/15

中国研究生教育排行榜-

正在加载...

中国学术期刊排行榜-

正在加载...

世界大学科研机构排行榜-

正在加载...

中国大学排行榜-

正在加载...

人 物-

正在加载...

课 件-

正在加载...

视听资料-

正在加载...

研招资料 -

正在加载...

知识要闻-

正在加载...

国际动态-

正在加载...

会议中心-

正在加载...

学术指南-

正在加载...

学术站点-

正在加载...