M19
Image Based Modelling

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16:05
conference time (CEST, Berlin)
Using Real World Computed Tomography Data for Fatigue Analyses
28/10/2021 16:05 conference time (CEST, Berlin)
Room: M
P. Sugg, P. Pinter (Volume Graphics GmbH, DEU)
P. Sugg, P. Pinter (Volume Graphics GmbH, DEU)
When considering fatigue strength, local effects play a major role. Cast or additively manufactured components exhibit geometric deviations and porosity, which can significantly influence the fatigue strength in both directions. Corner radii can be larger or smaller than intended by the designer effecting an increase or decrease of the fatigue strength, while pores will reduce the lifetime depending on their size and location. Computed tomography (CT) enables to capture these deviations and evaluate their relevance for state-of-the-art fatigue approaches. Pores within structural components might act as a source of stress concentration and thus it is desired to include them in a structural simulation. As there is generally a high number of microstructural pores, including them all in a classical finite element (FE) simulation will require high effort in FE mesh generation and result in large simulation models with a high number of elements to resolve stress concentrations in the vicinity of each defect. Immersed boundary finite element methods are well suited for overcoming these meshing problems. As they do not require a geometry-conforming mesh, they can efficiently be applied to simulate local stress distributions directly on CT scans, which accurately represent complex material structures and internal discontinuities. It is shown that the immersed boundary FE method is suitable to calculate local stress concentrations for the use in fatigue predictions. For more sophisticated simulations, e.g. with non-linear material behavior, a workflow is presented on how to generate volumetric meshes directly from CT data including only critical pores where the linear elastic immersed boundary approach exceeds a certain stress. This method reduces the number of FE-elements and thereby the computation time for subsequent complex FE-simulations significantly. Comparison of the stress concentrations of the immersed boundary FE and a linear elastic classical FE are in good correspondence even with the reduced set of meshed pores.
computed tomography, defects, fatigue, immersed boundary
16:25
conference time (CEST, Berlin)
Large Deformations of Metal Foams: Dynamic CT Results, Simulations and Modeling
28/10/2021 16:25 conference time (CEST, Berlin)
Room: M
E. Glatt (Math2Market GmbH, DEU); M. Hümbert, A. Grießer, S. Rief, L. Hunter (Tescan, USA); W. De Boever (Tescan, BEL); M. Kabel (Fraunhofer ITWM, DEU); H. Grimm-Strele (Fraunhofer ITWM, GRC)
E. Glatt (Math2Market GmbH, DEU); M. Hümbert, A. Grießer, S. Rief, L. Hunter (Tescan, USA); W. De Boever (Tescan, BEL); M. Kabel (Fraunhofer ITWM, DEU); H. Grimm-Strele (Fraunhofer ITWM, GRC)
Metal foams are used in a wide range of applications, for example in energy dissipation and as lightweight materials. When metal foams are an integral part of a structure, the mechanical characteristics and their response to external load need to be well understood. To facilitate a greater understanding, we have utilized lab-based dynamic computed tomography (CT) provided by Tescan to visualize uninterrupted compression of aluminum metal foams. These results where coupled to mechanical simulations of the same samples done with GeoDict. The dynamic CT reveals the different modes of deformation like buckling or bending of struts and collapsing of cells. Moreover, the displacement and deformation of pores can be analyzed and quantified once the scan is imported into the software. The simulation of the compression of 35% is possible thanks to the voxel based FFT solver FeelMath in GeoDict developed by the Fraunhofer ITWM. By comparing simulation and scan, the simulation can be verified in two ways: first, the load curves show whether the stresses in the foam are similar in simulation and experiment. Second, the different deformation modes observed in the simulation can be compared to the deformation modes in the scan as well as the evolution of pore shapes with increasing compression. Two samples from the same foam are tested, analyzed, and simulated. In a next step the verified simulation setup could be used not only on a digital twin obtained by importing a CT scan but also on a statistical digital twin of a foam which can be digitally generated based on the geometrical analysis of the scan. The statistical digital twin can be created with the FoamGeo module in GeoDict. This opens the possibility to create digital foam structures with new properties and to predict their deformation. GeoDict can be used to perform digital parameter studies without the need of manufacturing the foam.
Foam, CT, Image Based Modelling, Microstructural Modelling, Mesh-Free Methods
16:45
conference time (CEST, Berlin)
Utilizing Test Data from DIC for Polymer Material Modeling
28/10/2021 16:45 conference time (CEST, Berlin)
Room: M
S. Teller (Veryst Engineering LLC, USA)
S. Teller (Veryst Engineering LLC, USA)
Digital Image Correlation (DIC) is a powerful non-contact strain measurement tool for large strain, full-field strain measurement that is easily coupled with material testing. Full-field strain measurements give simulation engineers a plethora of data that can be accurately used to characterize a material. This wealth of data can be used to select and calibrate an advanced material model, particularly for materials that exhibit strain localization during uniaxial testing. Effectively using the data can enable an engineer to calibrate a more accurate material model. In this work we perform a digital image correlation and material modeling study on an impact-modified Polycarbonate (PC) material to investigate how to best use full field strain data. The PC material exhibits significant post-yield strain localization (necking) during tensile testing, making the DIC method extremely useful in characterizing mechanical behavior post necking. Additionally, the PC material has significant softening after yield, making accurate material models more difficult to calibrate. DIC is most useful when the engineer can extract all necessary information for an advanced material model. This paper aims to demonstrate which information can be easily used and how to best use it. We analyze the DIC data to extract strain data from different regions of tensile samples, including a virtual extensometer, average strain in the necked region, and average strain in the un-necked region of the samples. We use the strain data to select and calibrate a material model with a single element method, exploring how to use the data from different sample regions to calibrate a more accurate model. Different strain measurements from the same test are utilized to improve the material model. We also use an inverse calibration method to capture the strain and ensure that the material model is as accurate as possible for the simulation, and then simulate an inhomogeneous test specimen and loading to validate the experiment.
Material modeling; Constitutive model; Polymers; Testing; Model Calibration
17:05
conference time (CEST, Berlin)
Application of Image-based Modelling to Qualification and Simulated Testing of Next Generation Heat Exchangers
28/10/2021 17:05 conference time (CEST, Berlin)
Room: M
K. Genc, T. Spirka (Synopsys Inc., USA); B. Muehlhauser (North Star Imaging, USA); S. Acharya (Ansys Inc., USA)
K. Genc, T. Spirka (Synopsys Inc., USA); B. Muehlhauser (North Star Imaging, USA); S. Acharya (Ansys Inc., USA)
Additive Manufacturing (AM) of metal parts is becoming increasingly common as a flexible and scalable option for production. However, AM does have its challenges, notably in terms of the quality of the finished product, including the presence of defects that can increase the risk of failure. One key challenge involves comparing as-designed and as-built AM parts, and how these differences between the virtual and physical affect real-world performance. One set of solutions are being developed through a partnership between Synopsys, nTopology, ANSYS, North Star Imaging (NSI), and EOS. By combining industrial Computed Tomography (CT) with simulation, it is possible to virtually test and compare original CAD designs and scans of the actual printed parts. From this data, manufacturers can identify issues with the component (such as cracking or porosity) that could affect performance and lead to costly delays in production. In this presentation, we will discuss a recent case study for a workflow involving rapid re-design of a traditional heat exchanger, and how the combination of methods helps optimize design. We start with design of the part in nTopology software, analysis and simulation using ANSYS software, printing in EOS AM Machine, CT scanning of the part with NSI, image based inspection and image based meshing in Synopsys and finally simulation of the as-built part in ANSYS. The main focus of this presentation, however, will be on the Quality Analysis (QA) process post CT scanning. From the CT image data, inspection and meshing in Synopsys Simpleware software enables comparison of the performance of the original CAD design and the image-based model through simulation in ANSYS. Using this case study, we will demonstrate that the efficient workflow results in a design that is 80% lighter, 40% smaller in form-factor, and 10k more efficient in heat transfer than conventional technology. In addition, we will discuss how these techniques can be applied to similar design and manufacturing workflows and when applied in production, become fully automated by leveraging Machine Learning based AI technologies.
Segmentation, Computed Tomography, Meshing, Finite Element, Non Destructive Testing, Reverse Engineering
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