{"title":"用于金属增材制造的细胞自动机和晶体塑性建模","authors":"Majid Kavousi","doi":"10.21741/9781644903131-267","DOIUrl":null,"url":null,"abstract":"Abstract. This paper presents a methodology to establish a process-structure-property (PSP) relationship for the additive manufacturing (AM) of small AISI 316L parts, as might be used in coronary stent applications. The methodology includes a physically based process-structure model based on cellular automata (CA) for microstructure characterization and generation, coupled with crystal plasticity finite element (CPFE) structure-property modelling to predict the mechanical response of the AM part under tensile loading. The effect of AM process variables, such as laser power and scanning speed, are reflected in the PSP modelling through the thermal modelling of AM feeding into the CA model. The CA method is shown to be able to capture microstructure texture, which is key to anisotropic behavior of AM parts. The present study aims to (i) establish a practical link between CA and CPFE models and (ii) identify optimal process variables with respect to ductility.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"42 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cellular automata and crystal plasticity modelling for metal additive manufacturing\",\"authors\":\"Majid Kavousi\",\"doi\":\"10.21741/9781644903131-267\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. This paper presents a methodology to establish a process-structure-property (PSP) relationship for the additive manufacturing (AM) of small AISI 316L parts, as might be used in coronary stent applications. The methodology includes a physically based process-structure model based on cellular automata (CA) for microstructure characterization and generation, coupled with crystal plasticity finite element (CPFE) structure-property modelling to predict the mechanical response of the AM part under tensile loading. The effect of AM process variables, such as laser power and scanning speed, are reflected in the PSP modelling through the thermal modelling of AM feeding into the CA model. The CA method is shown to be able to capture microstructure texture, which is key to anisotropic behavior of AM parts. The present study aims to (i) establish a practical link between CA and CPFE models and (ii) identify optimal process variables with respect to ductility.\",\"PeriodicalId\":515987,\"journal\":{\"name\":\"Materials Research Proceedings\",\"volume\":\"42 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Research Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21741/9781644903131-267\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Research Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21741/9781644903131-267","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
摘要本文介绍了一种为冠状动脉支架应用中的小型 AISI 316L 零件的增材制造(AM)建立工艺-结构-性能(PSP)关系的方法。该方法包括一个基于细胞自动机(CA)的物理工艺-结构模型,用于微观结构的表征和生成,并结合晶体塑性有限元(CPFE)结构-属性建模,以预测 AM 零件在拉伸载荷下的机械响应。通过将 AM 热建模输入 CA 模型,PSP 建模反映了 AM 过程变量(如激光功率和扫描速度)的影响。CA 方法能够捕捉微观结构纹理,而微观结构纹理是 AM 零件各向异性行为的关键。本研究旨在(i)建立 CA 模型与 CPFE 模型之间的实用联系,(ii)确定延展性方面的最佳工艺变量。
Cellular automata and crystal plasticity modelling for metal additive manufacturing
Abstract. This paper presents a methodology to establish a process-structure-property (PSP) relationship for the additive manufacturing (AM) of small AISI 316L parts, as might be used in coronary stent applications. The methodology includes a physically based process-structure model based on cellular automata (CA) for microstructure characterization and generation, coupled with crystal plasticity finite element (CPFE) structure-property modelling to predict the mechanical response of the AM part under tensile loading. The effect of AM process variables, such as laser power and scanning speed, are reflected in the PSP modelling through the thermal modelling of AM feeding into the CA model. The CA method is shown to be able to capture microstructure texture, which is key to anisotropic behavior of AM parts. The present study aims to (i) establish a practical link between CA and CPFE models and (ii) identify optimal process variables with respect to ductility.