V. Venkatesh, D. Furrer, S. Burlatsky, M. Kaplan, A. Ross, S. Barker, M. McClure
{"title":"航空航天应用中基于模型的钛合金材料定义新范例","authors":"V. Venkatesh, D. Furrer, S. Burlatsky, M. Kaplan, A. Ross, S. Barker, M. McClure","doi":"10.1007/s40192-024-00373-3","DOIUrl":null,"url":null,"abstract":"<p>To meet the increasing demands of next generation high performance aircraft and propulsion system requirements, multidisciplinary model based materials engineering (MBME) approaches that utilize physics-based, quantitative process–structure–property–performance (PSPP) relationships are being developed and implemented. Traditional empirically based material property development resulted in underutilized component capabilities, and hinder MBME based methods that would allow the optimization of inter-related technologies of materials, manufacturing processes, and component design. A model-based materials engineering framework provides a means to enhanced materials and process definitions, and the rapid development of optimal designs with respect to cost, weight, performance, and qualification. Several key elements have been identified for the successful establishment of a model-based material definition (MBMD) infrastructure. These include individual or sets of specific computational model and data tools that work together in a cross-disciplinary engineering workflow. These infrastructural elements include robust, validated, scalable, fit for purpose models with the appropriate level of accuracy; toolsets for the automated linking of materials, manufacturing, and design models; enhanced data capture and management system to enable model calibration, validation and capture of materials and process variability; and multi-scale materials characterization tools and methods. This paper will review examples of industrial MBMD frameworks for titanium and titanium component design that utilizes validated manufacturing process, microstructure evolution, mechanical property and component/system performance modeling tools that have been developed to support robust PSPP relationships that enable high performance location specific component designs.</p>","PeriodicalId":13604,"journal":{"name":"Integrating Materials and Manufacturing Innovation","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New Paradigms in Model Based Materials Definitions for Titanium Alloys in Aerospace Applications\",\"authors\":\"V. Venkatesh, D. Furrer, S. Burlatsky, M. Kaplan, A. Ross, S. Barker, M. McClure\",\"doi\":\"10.1007/s40192-024-00373-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>To meet the increasing demands of next generation high performance aircraft and propulsion system requirements, multidisciplinary model based materials engineering (MBME) approaches that utilize physics-based, quantitative process–structure–property–performance (PSPP) relationships are being developed and implemented. Traditional empirically based material property development resulted in underutilized component capabilities, and hinder MBME based methods that would allow the optimization of inter-related technologies of materials, manufacturing processes, and component design. A model-based materials engineering framework provides a means to enhanced materials and process definitions, and the rapid development of optimal designs with respect to cost, weight, performance, and qualification. Several key elements have been identified for the successful establishment of a model-based material definition (MBMD) infrastructure. These include individual or sets of specific computational model and data tools that work together in a cross-disciplinary engineering workflow. These infrastructural elements include robust, validated, scalable, fit for purpose models with the appropriate level of accuracy; toolsets for the automated linking of materials, manufacturing, and design models; enhanced data capture and management system to enable model calibration, validation and capture of materials and process variability; and multi-scale materials characterization tools and methods. This paper will review examples of industrial MBMD frameworks for titanium and titanium component design that utilizes validated manufacturing process, microstructure evolution, mechanical property and component/system performance modeling tools that have been developed to support robust PSPP relationships that enable high performance location specific component designs.</p>\",\"PeriodicalId\":13604,\"journal\":{\"name\":\"Integrating Materials and Manufacturing Innovation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Integrating Materials and Manufacturing Innovation\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1007/s40192-024-00373-3\",\"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":"88","ListUrlMain":"https://doi.org/10.1007/s40192-024-00373-3","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}
New Paradigms in Model Based Materials Definitions for Titanium Alloys in Aerospace Applications
To meet the increasing demands of next generation high performance aircraft and propulsion system requirements, multidisciplinary model based materials engineering (MBME) approaches that utilize physics-based, quantitative process–structure–property–performance (PSPP) relationships are being developed and implemented. Traditional empirically based material property development resulted in underutilized component capabilities, and hinder MBME based methods that would allow the optimization of inter-related technologies of materials, manufacturing processes, and component design. A model-based materials engineering framework provides a means to enhanced materials and process definitions, and the rapid development of optimal designs with respect to cost, weight, performance, and qualification. Several key elements have been identified for the successful establishment of a model-based material definition (MBMD) infrastructure. These include individual or sets of specific computational model and data tools that work together in a cross-disciplinary engineering workflow. These infrastructural elements include robust, validated, scalable, fit for purpose models with the appropriate level of accuracy; toolsets for the automated linking of materials, manufacturing, and design models; enhanced data capture and management system to enable model calibration, validation and capture of materials and process variability; and multi-scale materials characterization tools and methods. This paper will review examples of industrial MBMD frameworks for titanium and titanium component design that utilizes validated manufacturing process, microstructure evolution, mechanical property and component/system performance modeling tools that have been developed to support robust PSPP relationships that enable high performance location specific component designs.
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.