SOM -自组织地图

Carolina Senabre Blanes Sergio Valero Verd, E. Velasco
{"title":"SOM -自组织地图","authors":"Carolina Senabre Blanes Sergio Valero Verd, E. Velasco","doi":"10.4172/2167-7670.C1.003","DOIUrl":null,"url":null,"abstract":"A industry today is challenged by a large number of complexes and often conflicting constraints and requirements such as reduce the cost and weight of vehicles, compress vehicle development cycle time, and improve product performances, e.g., Safety, NVH, Durability, etc. More recently, multidisciplinary design optimization (MDO) is a systematic tool to integrate all the attributes in vehicle design and find a compromise solution to satisfy those stringent performances and requirements. In addition, as most computer aided engineering (CAE) simulations are computation intensive, special optimization methods and processes are often required. This presentation will focus on historical developments and applications of optimization and robustness methods for vehicle designs. It will address significant technologies, such as advanced model bias updating method, data mining based design space identification involving large-scale engineering problems, and score function based reliability design method considering data uncertainty. Lastly, a vehicle example of minimizing the weight and satisfying safety and NVH requirements is presented to demonstrate the proposed methodology.","PeriodicalId":7286,"journal":{"name":"Advances in Automobile Engineering","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"SOM - Self organizing maps\",\"authors\":\"Carolina Senabre Blanes Sergio Valero Verd, E. Velasco\",\"doi\":\"10.4172/2167-7670.C1.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A industry today is challenged by a large number of complexes and often conflicting constraints and requirements such as reduce the cost and weight of vehicles, compress vehicle development cycle time, and improve product performances, e.g., Safety, NVH, Durability, etc. More recently, multidisciplinary design optimization (MDO) is a systematic tool to integrate all the attributes in vehicle design and find a compromise solution to satisfy those stringent performances and requirements. In addition, as most computer aided engineering (CAE) simulations are computation intensive, special optimization methods and processes are often required. This presentation will focus on historical developments and applications of optimization and robustness methods for vehicle designs. It will address significant technologies, such as advanced model bias updating method, data mining based design space identification involving large-scale engineering problems, and score function based reliability design method considering data uncertainty. Lastly, a vehicle example of minimizing the weight and satisfying safety and NVH requirements is presented to demonstrate the proposed methodology.\",\"PeriodicalId\":7286,\"journal\":{\"name\":\"Advances in Automobile Engineering\",\"volume\":\"50 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Automobile Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4172/2167-7670.C1.003\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Automobile Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/2167-7670.C1.003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

当今的汽车行业面临着大量复杂因素的挑战,并且常常存在相互冲突的限制和要求,例如降低车辆的成本和重量,压缩车辆开发周期,提高产品性能,例如安全性、NVH、耐久性等。近年来,多学科设计优化(MDO)作为一种系统的工具,将车辆设计中的所有属性整合在一起,并找到一个折衷的解决方案,以满足这些严格的性能和要求。此外,由于大多数计算机辅助工程(CAE)模拟都是计算密集型的,因此通常需要特殊的优化方法和过程。本报告将重点介绍优化和鲁棒性方法在车辆设计中的历史发展和应用。它将解决重要的技术,如先进的模型偏差更新方法,基于数据挖掘的设计空间识别涉及大规模工程问题,以及考虑数据不确定性的基于评分函数的可靠性设计方法。最后,给出了一个最小化车辆重量并满足安全性和NVH要求的实例来演示所提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SOM - Self organizing maps
A industry today is challenged by a large number of complexes and often conflicting constraints and requirements such as reduce the cost and weight of vehicles, compress vehicle development cycle time, and improve product performances, e.g., Safety, NVH, Durability, etc. More recently, multidisciplinary design optimization (MDO) is a systematic tool to integrate all the attributes in vehicle design and find a compromise solution to satisfy those stringent performances and requirements. In addition, as most computer aided engineering (CAE) simulations are computation intensive, special optimization methods and processes are often required. This presentation will focus on historical developments and applications of optimization and robustness methods for vehicle designs. It will address significant technologies, such as advanced model bias updating method, data mining based design space identification involving large-scale engineering problems, and score function based reliability design method considering data uncertainty. Lastly, a vehicle example of minimizing the weight and satisfying safety and NVH requirements is presented to demonstrate the proposed methodology.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信