H. Cheikh Sleiman, Murilo Henrique Moreira, Alessandro Tengattini, S. Dal Pont
{"title":"From tomographic imaging to numerical simulations: an open-source workflow for true morphology mesoscale FE meshes","authors":"H. Cheikh Sleiman, Murilo Henrique Moreira, Alessandro Tengattini, S. Dal Pont","doi":"10.21809/rilemtechlett.2023.184","DOIUrl":null,"url":null,"abstract":"Full-field techniques such as tomography are becoming progressively more central in the study of complex phenomena, in particular where spatiotemporal evolution is crucial, as in moisture transport or crack initiation in porous media. These techniques provide a unique insight in the local process whose quantification allows the improvement of our understanding and of the models describing them. Nevertheless, the model validation can be pushed further by attempting to explicitly represent the heterogeneities and simulate their role in the processes. Once validated, these models can be used to perform “virtual experiments”, and overcome the limitations of the experiments (e.g., sample size and number, fine control of the boundary and initial conditions). This study proposes a connection between tomography images and mesoscale models through a workflow that mainly employs open-source tools. This workflow is illustrated through the digitization of a Portland cement concrete sample, stemming from neutron tomographies and resulting in a numerical finite element mesh. The proposed workflow is flexible, allowing for the conversion of images from various sources, such as x-ray or neutron tomographies, to different numerical representations of the domain, such as finite element meshes or even a discrete domain required by discrete element methods, while preserving real morphologies with an accuracy proportionate to the specific need of the problem. Beside its generalizability, our method also offers automated labelling of the different domains and boundaries in both the volumetric and surface meshes, which is often necessary for assigning material properties and boundary conditions. Finally, the series of image, geometry and mesh processing steps described in this work are made available on a GitHub repository.","PeriodicalId":36420,"journal":{"name":"RILEM Technical Letters","volume":" 18","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"RILEM Technical Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21809/rilemtechlett.2023.184","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
Full-field techniques such as tomography are becoming progressively more central in the study of complex phenomena, in particular where spatiotemporal evolution is crucial, as in moisture transport or crack initiation in porous media. These techniques provide a unique insight in the local process whose quantification allows the improvement of our understanding and of the models describing them. Nevertheless, the model validation can be pushed further by attempting to explicitly represent the heterogeneities and simulate their role in the processes. Once validated, these models can be used to perform “virtual experiments”, and overcome the limitations of the experiments (e.g., sample size and number, fine control of the boundary and initial conditions). This study proposes a connection between tomography images and mesoscale models through a workflow that mainly employs open-source tools. This workflow is illustrated through the digitization of a Portland cement concrete sample, stemming from neutron tomographies and resulting in a numerical finite element mesh. The proposed workflow is flexible, allowing for the conversion of images from various sources, such as x-ray or neutron tomographies, to different numerical representations of the domain, such as finite element meshes or even a discrete domain required by discrete element methods, while preserving real morphologies with an accuracy proportionate to the specific need of the problem. Beside its generalizability, our method also offers automated labelling of the different domains and boundaries in both the volumetric and surface meshes, which is often necessary for assigning material properties and boundary conditions. Finally, the series of image, geometry and mesh processing steps described in this work are made available on a GitHub repository.