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120 results for “Finite Element”
Raw images and processed datasets related to the journal article Robust Assessment of Post-Localisation Hardening Behaviour in Eurofer97 using Inverse Finite Element Methods
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Finite element mesh of fusion energy heat exchange component: hybrid CAD/IBSim model including a graphite foam interlayer
<p>Image-Based Simulation (IBSim) mesh:<br> A finite element mesh of a conceptual design for a fusion energy heat exchange component (monoblock). The mesh is a hybrid from a computer aided design (CAD) drawing for the pipe and armour and IBSim for the interlayer. The IBSim interlayer is generated directly from a 3D volumetric image of a graphite foam block (KFoam). The 3D image was generated with an X-ray tomography scan performed by Dr Llion Evans with Manchester X-ray Imaging Facility equipment, which was funded in part by the EPSRC (grants EP/F007906/1, EP/F001452/1 and EP/I02249X/1). Conversion of the data to FE mesh was achieved using ScanIP, part of the Simpleware suite of programmes, version 7 (Synopsys Inc., Mountain View, CA, USA).</p> <p>The FE mesh data uses the EnSight Gold file format and may be visualised using Paraview (<a href="https://www.paraview.org">https://www.<strong>paraview</strong>.org</a>).</p> <p>The CT data used for the mesh is available as a separate dataset:</p> <p>This data was used originally for the following publications (please cite if re-using the data):<br> Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Image based in silico characterisation of the effective thermal properties of a graphite foam”, Carbon, Vol. 143, pp. 542-558, 2018. <a href="https://doi.org/10.1016/j.carbon.2018.10.031">https://doi.org/10.1016/j.carbon.2018.10.031</a></p> <p>Ll.M. Evans, L. Margetts, P.D. Lee, C.A.M. Butler, E. Surrey, “Improving modelling of complex geometries in novel materials using 3D imaging”, Proceedings of NEA International Workshop on Structural Materials for Innovative Nuclear Systems, Manchester, UK, July 2016. <a href="https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf">https://www.oecd-nea.org/science/smins4/documents/P1-18_LlME_SMINS4_paper_reviewed.pdf</a></p>
FIGURE 1 in Coupling finite element analysis and multibody system dynamics for biological research
FIGURE 1. Simplification of the center of head movement as a joint in extinct Temnospondyli amphibian when biting. Elaborated from the original image (en.wikipedia.org/wiki/File:Jammerbergia_formops.jpg). Under license: CC BY-SA 3.0 (creativecommons.org/licenses/by-sa/3.0/).
FIGURE 4 in Coupling finite element analysis and multibody system dynamics for biological research
FIGURE 4. Von Mises stress distribution in the skull for the Static Analysis in FEA in cases 1A, 2A, 3A, 1B, 2B and 3B.
FIGURE 2 in Coupling finite element analysis and multibody system dynamics for biological research
FIGURE 2. Studied test cases of different feeding movements when applying a force F=800 N in the direction of the red arrow (when the force is perpendicular at the view the red arrow is a red dot). Case 1A, 2A and 3A with a fixed boundary condition in the condyle without the web of beams. Case 1B, 2B and 3B with the web of beams in the condyle and a fixed boundary condition.
FIGURE 6 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE 6. Box-plots of Von Mises stress distributions when Quasi-Ideal Meshes (QUIM) are assumed for the 20 Cingulata mandibles analysed. The 80% of the values of the Von Mises stress distribution are represented between the upper and lower whiskers
FIGURE 3 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE 3. Evolution of the values of Arithmetic Mean (AM), Mesh-Weighted Arithmetic Mean (MWAM), Median (M), Mesh-Weighted Median (MWM), Percentage Error of the Arithmetic Mean (PEofAM) and Percentage Error of the Median (PEofM) in front of the size of the elements (1) and the uniformity of the mesh (2). Meshes from a Chlamyphorus truncates. S07 refers to Mesh S7 (mesh size), SE refers to Mesh SE (mesh homogeneity).
FIGURE S2 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE S2. Map of Von Mises stress distribution in the six meshes of Chlamyphorus truncates obtained when evaluating the influence of the homogeneity of the mesh.
FIGURE 2 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE 2. Six meshes of Chlamyphorus truncates obtained when evaluating the influence of the homogeneity of the mesh.
FIGURE 1 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE 1. Twelve meshes of Chlamyphorus truncates obtained when evaluating the influence of size of the elements in the mesh.
FIGURE 5 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE 5. Evolution of the box-plots of the Von Mises stress distribution. X-axes refers to meshes S01 to S12: the size of the elements (1); and meshes SA to SF: the uniformity of the mesh (2). Meshes from a Chlamyphorus truncates.
FIGURE 4 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE 4. Evolution of the convergence error of each iteration of Arithmetic Mean (AM), Mesh-Weighted Arithmetic Mean (MWAM), Median (M), Mesh-Weighted Median (MWM) in front of the number of nodes (1) and the percentage of Refined Area (percent value of area with homogeneous mesh) (2). Meshes from a Chlamyphorus truncates. S07 refers to Mesh S7 (mesh size), SE refers to Mesh SE (mesh homogeneity).
FIGURE S1 in Accounting for differences in element size and homogeneity when comparing Finite Element Models: Armadillos as a case study
FIGURE S1. Map of Von Mises stress distribution in the 12 meshes of Chlamyphorus truncates obtained when evaluating the influence of size of the elements in the mesh.
Surfactant Transport on Evolving Surfaces - Solutions of Space-Time Trace Finite Element Methods visualized.
<p>Videos of numerical experiments in the article "An accurate and robust Eulerian finite element method for partial differential equations on evolving surfaces" by H. Sass and A. Reusken. Surfactant transport on evolving surfaces with high curvatures and topological singularities is illustrated.</p>
Deformation simulation results of Capriccio method coupled systems for conducting comparative one- and multidimensional studies on the coupling of the finite element method with particle-based techniques
<p>readme_3Dresults.txt</p> <p><br> <strong>Description</strong>:</p> <p>This readme explains the content and path structure of the results obtained from a<br> deformation test conducted on slightly different MD-FE coupled systems performing the<br> Capriccio method in a three-dimensional space within the associated project thesis [1],<br> published on the following dataset: <a href="https://doi.org/10.5281/zenodo.7924367">https://doi.org/10.5281/zenodo.7924367</a></p> <p>Furthermore, input files and parameters as well as potential tables required to reproduce<br> the obtained data are provided as well.</p> <p>The molecular dynamics (MD) part is executed in LAMMPS and the finite element (FE) method<br> part by a MATLAB script as described in Section 4.1 of [1]. The whole setup of the 3D<br> models is elaborated in Section 4.2 of [1]. A discussion of some results is given in<br> Chapter 6 of [1] in the context of assessing their comparability with the corresponding 1D<br> model.</p> <p><br> <strong>Context</strong>:</p> <p>[1] L. Laubert, "Establishing a framework for conducting comparative one- and<br> multidimensional studies on the coupling of the finite element method with<br> particle-based techniques", Project Thesis, Friedrich-Alexander-Universität<br> Erlangen-Nürnberg (FAU), 2023.</p> <p><br> <strong>Contact</strong>:</p> <p>Lukas Laubert<br> Institute of Applied Mechanics<br> Friedrich-Alexander-Universiät Erlangen-Nürnberg<br> Egerlandstraße 5<br> 91058 Erlangen</p> <p><br> <strong>License</strong>:</p> <p>Creative Commons Attribution Non Commercial 4.0 International</p> <p><br> <strong>Path structure and files</strong>:</p> <p>- The ZIP compressed files each contain a folder containing all simulation files as well as<br> postprocessing variables:<br> * /FE_data/ contains all output files after each FE simulation in each iteration step<br> * /MD_data/ contains all output files after each MD simulation in each iteration step<br> * /input_files/ contains the input FE model "cgps_dpd_c_1_2000.inp", the MD particle<br> configurations "cgps_dpd_c_1_2000.data", the AP particle coordinates <br> "cgps_dpd_c_1_2000.ac" as well as further Abaqus CAE FE files that<br> can be used to adapt the present FE model<br> * /input_parameters/ contains the parameter dataset; "Capriccio.prm" is the main parameter<br> dataset, whose adaptations lead to similar adjustments in the other parameter files<br> * "Capriccio_FEMD_main_meggie_WZ.sh" is a shell script for executing simulations<br> * "job.out" is an output protocol that documents the progress of the simulations<br> * "Job.err" is an error protocol that documents detected errors during the simulations<br> * "log.lammps" logs MD parameter sets<br> * "meta.info" provides version information of used softwares among few other information<br> * "next_job.info" documents the next load step and iteration step that is to be executed<br> when simulation jobs are restarted on the used computation cluser<br> * **_workspace_vars.mat comprises a set of postprocessing variables obtained by executing a<br> postprocessing script provided by Capriccio group</p> <p>- "md_dpd_main-CBpot-writeobs-sandw.in" is an input script that further defines and loads<br> MD simulation parameter</p> <p>- ***_table are potential tables applied during the MD simulations<br> * "Angle_table" lists the angle bending potential<br> * "Bond_table" lists the bond potentials<br> * "Nonbond_table" lists the non-bonded interaction potential</p>
Hierarchical universal matrices for H(curl) tetrahedral finite elements
<p>The contents of this repository are associated with the paper:</p> <p>[1] L. L. Toth, A. Amor-Martin, and R. Dyczij-Edlinger, "Hierarchical Universal Matrices for Curvilinear Tetrahedral H(curl) Finite Elements," submitted to IEEE Transactions on Antennas and Propagation.</p> <p>The subdirectory UniversalMatrices contains mathematical formulas for hierarchical L2 and H(curl) basis functions, the corresponding universal matrices (UM), and a MATLAB script for generating these UMs. The bases and UMs are given in two different formats:</p> <p>*.mat MATLAB data file with a MATLAB structure,</p> <p>*.xml file with a structure.</p> <p>The subdirectory MATLAB_TestCode contains MATLAB scripts and input data for reproducing the numerical results given in [1].</p> <p>For details, see the README.txt files in the bottom-level directories.</p>
Finite Element Analysis perturbation files for Rubin Observatory Simonyi Survey Telescope and LSST Camera
<p>## Notes on FEA files</p> <p><br> </p> <p># M1M3 Bending modes</p> <p> </p> <p>M1M3_1um_156_grid.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_1um_156_grid.txt</p> <p>- shape = (5256, 159)</p> <p>- Each row is one of 5256 FEA nodes.</p> <p>- 0th column is M1M3 disambiguator</p> <p>- 1st and 2nd columns are FEA node x and y in M1M3 CS</p> <p>- Last 156 columns are bending modes; the z-displacement of each node for each mode.</p> <p> </p> <p>M1M3_1um_156_force.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_1um_156_force.txt</p> <p>- shape = (156, 159)</p> <p>- Each row is one of 156 bending modes.</p> <p>- 0th column is actuator ID</p> <p>- 1st and 2nd columns are actuator x and y in M1M3 CS</p> <p>- Last 156 columns are forces in Newtons for each mode.</p> <p><br> </p> <p># M1M3 print through</p> <p> </p> <p>M1M3_dxdydz_zenith.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_dxdydz_zenith.npy</p> <p>- shape = (5256, 3)</p> <p>- Each row is one of 5256 FEA nodes.</p> <p>- Columns are dx, dy, dz in M1M3 CS.</p> <p>- This is the gravitational "print through" when mirror is zenith pointing</p> <p> </p> <p>M1M3_dxdydz_horizon.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_dxdydz_horizon.npy</p> <p>- shape = (5256, 3)</p> <p>- Each row is one of 5256 FEA nodes.</p> <p>- Columns are dx, dy, dz in M1M3 CS.</p> <p>- This is the gravitational "print through" when mirror is horizon pointing</p> <p> </p> <p>M1M3_force_zenith.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_force_zenith.npy</p> <p>- shape = (256,)</p> <p>- Each row is one of 256 actuators. (So we consider the x and y actuators here too.)</p> <p>- Columns are forces in Newtons.</p> <p>- These are the mirror support forces when the mirror is zenith pointing. (Is this after optimization? Include LUT or not?)</p> <p> </p> <p>M1M3_force_horizon.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_force_horizon.npy</p> <p>- shape = (256,)</p> <p>- Each row is one of 256 actuators. (So we consider the x and y actuators here too.)</p> <p>- Columns are forces in Newtons.</p> <p>- These are the mirror support forces when the mirror is horizon pointing. (Is this after optimization? Include LUT or not?)</p> <p><br> </p> <p># M1M3 Thermal</p> <p> </p> <p>M1M3_thermal_FEA.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_thermal_FEA.npy</p> <p>- shape = (5244, 7)</p> <p>- Each row is one of 5244 FEA nodes. (Why aren't these the same as above? I don't know.)</p> <p>- Columns are:</p> <p>- 0: Unit-Normalized FEA x</p> <p>- 1: Unit-Normalized FEA y</p> <p>- 2: Bulk temperature dz coefficient</p> <p>- 3: x temperature gradient dz coefficient</p> <p>- 3: y temperature gradient dz coefficient</p> <p>- 3: z temperature gradient dz coefficient</p> <p>- 3: r temperature gradient dz coefficient</p> <p><br> </p> <p># M1M3 Miscellany</p> <p> </p> <p>M1M3_influence_256.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_influence_256.npy</p> <p>- shape = (5256, 256)</p> <p>- Each row is one of 5256 FEA nodes.</p> <p>- Each column is one of 256 actuators.</p> <p>- Values are dz/dF for each actuator/node.</p> <p> </p> <p>M1M3_LUT.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_LUT.txt</p> <p>- shape = (257, 91)</p> <p>- First column is index in degrees (0-90 inclusive). Last 256 columns are forces in Newtons.</p> <p>- Each column is LUT for one value of the elevation index.</p> <p> </p> <p>M1M3_1000N_UL_shape_156.fits.gz</p> <p>- source = IM/data/M1M3/M1M3_1000N_UL_shape_156.npy</p> <p>- shape = (5256, 156)</p> <p>- Rows must be FEA nodes, columns must be bending modes.</p> <p>- Not sure what the purpose is of this one.</p> <p><br> </p> <p># M2 Bending modes</p> <p> </p> <p>M2_1um_grid.fits.gz</p> <p>- source = IM/data/M2/M2_1um_grid.DAT</p> <p>- shape = (15984, 75)</p> <p>- Each row is one of 15984 FEA nodes.</p> <p>- 0th column is node index ?</p> <p>- 1st and 2nd columns are FEA node x and y in M2 CS</p> <p>- Last 72 columns are bending modes; the z-displacement of each node for each mode.</p> <p> </p> <p>M2_1um_force.fits.gz</p> <p>- source = IM/data/M2/M2_1um_force.DAT</p> <p>- shape = (72, 75)</p> <p>- Each row is one of 72 bending modes.</p> <p>- 0th column is actuator ID</p> <p>- 1st and 2nd columns are actuator x and y in M2 CS</p> <p>- Last 72 columns are forces in Newtons for each mode.</p> <p> </p> <p># M2 print through / thermal</p> <p> </p> <p>M2_GT_FEA.fits.gz</p> <p>- source = IM/data/M2/M2_GT_FEA.txt</p> <p>- shape = (9084, 6)</p> <p>- Each row is one of 9084 FEA nodes. (Why aren't these the same as above? I don't know.)</p> <p>- Columns are:</p> <p>- 0: Unit-Normalized FEA x</p> <p>- 1: Unit-Normalized FEA y</p> <p>- 2: Zenith print through dz coefficient</p> <p>- 3: Horizon print through dz coefficient</p> <p>- 4: z temperature gradient dz coefficient</p> <p>- 5: r temperature gradient dz coefficient</p> <p><br> </p>
Simulation data of Schmidt et al., A three-dimensional finite element formulation coupling electrochemistry and solid mechanics on resolved microstructures of all-solid-state lithium-ion batteries, DOI: https://doi.org/10.1016/j.cma.2023.116468
<p>This data set includes the simulation results of the relevant simulations published in the paper: "Schmidt et al., A three-dimensional finite element formulation coupling electrochemistry and solid mechanics on resolved microstructures of all-solid-state lithium-ion batteries, DOI: https://doi.org/10.1016/j.cma.2023.116468".</p> <p>Please refer to the paper for the details of the model as well as the parameterization of the model for the respective simulations.</p> <p>The provided lzip archive is structured into separate folders, one per simulation. Each folder contains the output data and a short README.txt with further hints. For information on the compression algorithm and how to uncompress it lzip please refer to https://en.wikipedia.org/wiki/Lzip.</p>
Finite Element model data for Academic Rotor bladed-disc system
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Finite Element model of the upper lumbar and lower thoracic spine
<p>Finite element method (FEM) model of the lumbar spine, stored in <a href="https://code-aster.org/">code_aster</a> med-file format.</p> <p>The dataset is used to develop the SODALITE virtual clinical trial use-case. It contains a FEM-model of a part of the lumbar spine. Modelled are a part of the vertebra L2, the vertebra L1 and the intervertebral disc between them. The model is generated based on the coresponding computer tomographic imaging <a href="https://doi.org/10.5281/zenodo.3959070">volume dataset</a> and <a href="https://doi.org/10.5281/zenodo.3961270">iso-surface</a>.</p> <p>The datasets' content is illustrated by the attached png image which shows a shaded surface rendering of the dataset.</p> <p> </p>
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