{"title":"Identification for elastoplastic constitutive parameters of 316L stainless steel lattice structures using finite element model updating and integrated digital image correlation","authors":"Zhaozhen Huang, Caroline Antion, Franck Toussaint","doi":"10.1016/j.mechmat.2024.105232","DOIUrl":null,"url":null,"abstract":"<div><div>Lattice structures are widely considered for industrial applications owing to their excellent energy absorption and mechanical properties. In this work, octet-truss lattice structures are manufactured from 316L stainless steel powder by selective laser melting (SLM). The geometrical information of lattice structures is captured by SEM and X-ray tomography. It reveals that realistic dimensions of struts differ slightly from CAD-designed ones. The mechanical behaviors are investigated both experimentally and numerically. Quasi-static uni-axial compression experiments with 2D digital image correlation (DIC) technology are conducted to measure displacement/strain fields. Finite element analysis based on an elastic and anisotropic plastic constitutive model is used to simulate mechanical behaviors. To improve the predictive accuracy, a finite element model updating approach is implemented to identify constitutive parameters. The results show that numerical simulation with optimized parameters match well with experiments in aspect of force-displacement curve at elastic–plastic stage and displacement fields.</div></div>","PeriodicalId":18296,"journal":{"name":"Mechanics of Materials","volume":"202 ","pages":"Article 105232"},"PeriodicalIF":3.4000,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechanics of Materials","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167663624003247","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
晶格结构因其出色的能量吸收和机械性能而被广泛应用于工业领域。在这项工作中,利用选择性激光熔化(SLM)技术,用 316L 不锈钢粉末制造出了八叉桁架晶格结构。通过扫描电子显微镜和 X 射线断层扫描捕捉了晶格结构的几何信息。结果表明,支柱的实际尺寸与 CAD 设计的尺寸略有不同。实验和数值研究了机械行为。利用二维数字图像相关(DIC)技术进行了准静态单轴压缩实验,以测量位移/应变场。基于弹性和各向异性塑性组成模型的有限元分析用于模拟机械行为。为了提高预测精度,采用了一种有限元模型更新方法来确定构成参数。结果表明,在弹塑性阶段的力-位移曲线和位移场方面,采用优化参数的数值模拟与实验结果非常吻合。
Identification for elastoplastic constitutive parameters of 316L stainless steel lattice structures using finite element model updating and integrated digital image correlation
Lattice structures are widely considered for industrial applications owing to their excellent energy absorption and mechanical properties. In this work, octet-truss lattice structures are manufactured from 316L stainless steel powder by selective laser melting (SLM). The geometrical information of lattice structures is captured by SEM and X-ray tomography. It reveals that realistic dimensions of struts differ slightly from CAD-designed ones. The mechanical behaviors are investigated both experimentally and numerically. Quasi-static uni-axial compression experiments with 2D digital image correlation (DIC) technology are conducted to measure displacement/strain fields. Finite element analysis based on an elastic and anisotropic plastic constitutive model is used to simulate mechanical behaviors. To improve the predictive accuracy, a finite element model updating approach is implemented to identify constitutive parameters. The results show that numerical simulation with optimized parameters match well with experiments in aspect of force-displacement curve at elastic–plastic stage and displacement fields.
期刊介绍:
Mechanics of Materials is a forum for original scientific research on the flow, fracture, and general constitutive behavior of geophysical, geotechnical and technological materials, with balanced coverage of advanced technological and natural materials, with balanced coverage of theoretical, experimental, and field investigations. Of special concern are macroscopic predictions based on microscopic models, identification of microscopic structures from limited overall macroscopic data, experimental and field results that lead to fundamental understanding of the behavior of materials, and coordinated experimental and analytical investigations that culminate in theories with predictive quality.