{"title":"Leveraging Full Field Deformation Measurements in Computational Modeling of Damage","authors":"Sara Schlenker, E. Tekerek, A. Kontsos","doi":"10.1115/1.4062291","DOIUrl":null,"url":null,"abstract":"\n Advances in sensing and nondestructive evaluation methods have increased the interest in developing data-driven modeling and associated computational workflows for model-updating, in relation also to a variety of emerging digital twin applications. In this context, of particular interest in this investigation are transient effects that lead to or are caused by deformation instabilities, typically found in the cases of complex material behavior or in interactions between material and geometry. In both cases, deformation localizations are observed which are typically also related to damage effects. This manuscript describes a novel framework to incorporate deformation data into a finite element model (FEM) that has been formulated using non-local mechanics and is capable of receiving such data and using it to describe the development of localizations. Specifically, experimentally measured full field displacement data is used as an input in FEM as an ad-hoc boundary condition at any or every node in the body. To achieve this goal, a plasticity model which includes a spatially averaged non-local hardening parameter in the yield criterion is used to account for associated numerical instabilities and mesh dependence. Furthermore, the introduction of a length scale parameter into the constitutive law allows the connection between material behavior, geometry and localizations. Additional steps remove the experimental data and evolve the computational predictions forward in time. Both one and three-dimensional boundary value problems are used to present results obtained by the proposed framework, while comments are made in terms of its potential uses.","PeriodicalId":52294,"journal":{"name":"Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems","volume":"32 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4062291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Advances in sensing and nondestructive evaluation methods have increased the interest in developing data-driven modeling and associated computational workflows for model-updating, in relation also to a variety of emerging digital twin applications. In this context, of particular interest in this investigation are transient effects that lead to or are caused by deformation instabilities, typically found in the cases of complex material behavior or in interactions between material and geometry. In both cases, deformation localizations are observed which are typically also related to damage effects. This manuscript describes a novel framework to incorporate deformation data into a finite element model (FEM) that has been formulated using non-local mechanics and is capable of receiving such data and using it to describe the development of localizations. Specifically, experimentally measured full field displacement data is used as an input in FEM as an ad-hoc boundary condition at any or every node in the body. To achieve this goal, a plasticity model which includes a spatially averaged non-local hardening parameter in the yield criterion is used to account for associated numerical instabilities and mesh dependence. Furthermore, the introduction of a length scale parameter into the constitutive law allows the connection between material behavior, geometry and localizations. Additional steps remove the experimental data and evolve the computational predictions forward in time. Both one and three-dimensional boundary value problems are used to present results obtained by the proposed framework, while comments are made in terms of its potential uses.