R. Shanmugavel, Thirumalai Kumaran Sundaresan, Uthayakumar Marimuthu, Pethuraj Manickaraj
{"title":"赤泥增强铝复合材料工艺优化及磨损性能研究","authors":"R. Shanmugavel, Thirumalai Kumaran Sundaresan, Uthayakumar Marimuthu, Pethuraj Manickaraj","doi":"10.1155/2016/9082593","DOIUrl":null,"url":null,"abstract":"This work presents the application of hybrid approach for optimizing the dry sliding wear behavior of red mud based aluminum metal matrix composites (MMCs). The essential input parameters are identified as applied load, sliding velocity, wt.% of reinforcement, and hardness of the counterpart material, whereas the output responses are specific wear rate and Coefficient of Friction (COF). The Grey Relational Analysis (GRA) is performed to optimize the multiple performance characteristics simultaneously. The Principle Component Analysis (PCA) and entropy methods are applied to evaluate the values of weights corresponding to each output response. The experimental result shows that the wt.% of reinforcements (%) followed by the sliding velocity (%) contributed more to affecting the dry sliding wear behavior. The optimized conditions are verified through the confirmation test, which exhibited an improvement in the grey relational grade of specific wear rate and COF by 0.3 and 0.034, respectively.","PeriodicalId":44668,"journal":{"name":"Advances in Tribology","volume":"2016 1","pages":"1-7"},"PeriodicalIF":1.5000,"publicationDate":"2016-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2016/9082593","citationCount":"11","resultStr":"{\"title\":\"Process Optimization and Wear Behavior of Red Mud Reinforced Aluminum Composites\",\"authors\":\"R. Shanmugavel, Thirumalai Kumaran Sundaresan, Uthayakumar Marimuthu, Pethuraj Manickaraj\",\"doi\":\"10.1155/2016/9082593\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work presents the application of hybrid approach for optimizing the dry sliding wear behavior of red mud based aluminum metal matrix composites (MMCs). The essential input parameters are identified as applied load, sliding velocity, wt.% of reinforcement, and hardness of the counterpart material, whereas the output responses are specific wear rate and Coefficient of Friction (COF). The Grey Relational Analysis (GRA) is performed to optimize the multiple performance characteristics simultaneously. The Principle Component Analysis (PCA) and entropy methods are applied to evaluate the values of weights corresponding to each output response. The experimental result shows that the wt.% of reinforcements (%) followed by the sliding velocity (%) contributed more to affecting the dry sliding wear behavior. The optimized conditions are verified through the confirmation test, which exhibited an improvement in the grey relational grade of specific wear rate and COF by 0.3 and 0.034, respectively.\",\"PeriodicalId\":44668,\"journal\":{\"name\":\"Advances in Tribology\",\"volume\":\"2016 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2016-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2016/9082593\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Tribology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2016/9082593\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Tribology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2016/9082593","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Process Optimization and Wear Behavior of Red Mud Reinforced Aluminum Composites
This work presents the application of hybrid approach for optimizing the dry sliding wear behavior of red mud based aluminum metal matrix composites (MMCs). The essential input parameters are identified as applied load, sliding velocity, wt.% of reinforcement, and hardness of the counterpart material, whereas the output responses are specific wear rate and Coefficient of Friction (COF). The Grey Relational Analysis (GRA) is performed to optimize the multiple performance characteristics simultaneously. The Principle Component Analysis (PCA) and entropy methods are applied to evaluate the values of weights corresponding to each output response. The experimental result shows that the wt.% of reinforcements (%) followed by the sliding velocity (%) contributed more to affecting the dry sliding wear behavior. The optimized conditions are verified through the confirmation test, which exhibited an improvement in the grey relational grade of specific wear rate and COF by 0.3 and 0.034, respectively.