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15 results for “Finite Element Method”
Finite element method (FEM) models for translational research in non-invasive brain stimulation
<p>Finite element method (FEM) models for non-invasive brain stimulation modeling using SimNIBS or other compatible software.<br> The mouse and monkey models are described in detail in Alekseichuk et al., Comparative modeling of transcranial magnetic and electric stimulation in mouse, monkey, and human, NeuroImage 2019.<br> The Petri dish model follows a typical experimental setup for in-vitro TMS, similar to what is described in Lenz et al. Repetitive magnetic stimulation induces plasticity of inhibitory synapses, Nature Communications 2016.<br> <br> The following files are included:<br> 1. Brain tissue slice in a Petri dish.<br> 2. Normal adult male nude mouse "Digimouse" (brain volume of 0.38 cm3).<br> 3. Normal adult male capuchin monkey "S" (brain volume of 68.31 cm3).<br> <br> The models include the following tissues (coded with numbers):<br> 1. White matter volume<br> 2. Grey matter volume<br> 3. CSF volume<br> 4. Skull volume<br> 5. Soft tissues volume<br> 8. Eyeballs volume<br> 1001. White matter outer surfaces<br> 1002. Grey matter outer surfaces<br> 1003. CSF outer surfaces<br> 1004. Skull outer surfaces<br> 1005. Soft tissues outer surfaces<br> 1008. Eyeballs outer surfaces<br> <br> With any questions, please, contact the corresponding authors of the relevant papers or <a href="mailto:aopitz@umn.edu">aopitz@umn.edu</a> (Alexander Opitz).</p>
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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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>
Supplementary material for "A Partitioned Finite Element Method for power-preserving discretization of open systems of conservation laws"
<p>This archive contains supplementary material for the paper "A Partitioned Finite Element Method for power-preserving discretization of open systems of conservation laws", containing the source codes for the numerial results presented in the paper. An arXiv pre-print version of the paper is available <a href="https://arxiv.org/abs/1906.05965">here</a>.</p> <p>The following codes are provided:</p> <ul> <li> <p><code>codes/simulation1D_small.jl</code>: small amplitudes (linear) 1D simulation</p> </li> <li> <p><code>codes/simulation1D_large.jl</code>: large amplitudes (nonlinear) 1D simulation</p> </li> <li> <p><code>codes/simulation1D_analytical_gradient</code>: large amplitudes 1D simulation, but using an analytical nonlinear Hamiltonian gradient expression</p> </li> <li> <p><code>codes/simulation2D.jl</code>: large amplitudes (nonlinear) 2D simulation</p> </li> <li> <p><code>codes/convergence1D.jl</code>: convergence analysis of the 1D linear case</p> </li> <li> <p><code>codes/convergence2D.m</code>: convergence analysis of the 2D linear case</p> </li> </ul> <p>A GitHub with the codes and a few instructions on usage is available <a href="http://github.com/flavioluiz/PFEM-article-supplementary-material">here</a>.</p> <p><strong>Acknowledgements</strong></p> <p>This work has been performed in the frame of the Collaborative Research DFG and ANR project INFIDHEM, entitled "Interconnected of Infinite-Dimensional systems for Heterogeneous Media", nº ANR-16-CE92-0028. Further information is available <a href="http://websites.isae-supaero.fr/infidhem/the-project">here</a>.</p>
Analysis files for MSC Marc finite element software, Article: The analysis of shrink-fit connection – the methods of heating and the factors influencing the distribution of residual stresses
<p>This archive contains model files for Finite Element Analysis of the shrink-fit connection in crankshaft and the files for charts in GNUPlot.</p>
A high-resolution finite element method (FEM) human head model for non-invasive brain stimulation
<p>High-resolution finite element method (FEM) model of a human head for non-invasive brain stimulation modeling using SimNIBS or other compatible software. The original head model (Ernie) was downloaded from the tutorial dataset of <a href="http://simnibs.org">www.simnibs.org</a> and further refined in grey matter and white matter regions.</p> <p>This supplementary dataset is released as part of the NeMo-TMS toolbox (<a href="https://github.com/OpitzLab/NeMo-TMS">https://github.com/OpitzLab/NeMo-TMS</a>). Please refer to the corresponding article for more information:</p> <p>Shirinpour, S., Hananeia, N., Rosado, J., Galanis, C., Vlachos, A., Jedlicka, P., Queisser, G., & Opitz, A. (2020). Multi-scale Modeling Toolbox for Single Neuron and Subcellular Activity under (repetitive) Transcranial Magnetic Stimulation. <em>BioRxiv</em>, 2020.09.23.310219. <a href="https://doi.org/10.1101/2020.09.23.310219">https://doi.org/10.1101/2020.09.23.310219</a></p>
Input files for binding energy calculations in "Coupling finite and boundary element methods to solve the Poisson--Boltzmann equation for electrostatics in molecular solvation"
<p>Input files (meshes, pqr, cavities) for binding energy calculations in the manuscript "Coupling finite and boundary element methods to solve the Poisson--Boltzmann equation for electrostatics in molecular solvation" (preprint at https://arxiv.org/abs/2305.11886). This data set of molecular structures was originally proposed by Harris, R.C., Boschtisch, A.H., and Fenley, M.O., JCTC 9 (8) (2013) (<a href="https://doi.org/10.1021/ct300765w">https://doi.org/10.1021/ct300765w</a>). Scripts to generate results are available in https://github.com/MichalBosy/FEM_BEM_coupling/.</p>
Automated X-ray computer tomography segmentation method for finite element analysis of non-crimp fabrics reinforced composites
<p>Data behind the publications:</p> <p>Auenhammer, R.M., Mikkelsen, L.P., Asp, L., Blinzler, B. Automated X-ray computer tomography segmentation method for finite element analysis of non-crimp fabric reinforced composites. <em>Composite Structures, </em><strong>256</strong>, 113136, <a href="https://doi.org/10.1016/j.compstruct.2020.113136">https://doi.org/10.1016/j.compstruct.2020.113136</a>, 2021.</p> <p>Auenhammer, Robert M., Lars P. Mikkelsen, Leif E. Asp, Brina J. Blinzler, Dataset of non-crimp fabric reinforced composites for an X-ray computer tomography aided engineering process, <em>Data in Brief, </em><strong>33</strong>, 106518, <a href="https://doi.org/10.1016/j.dib.2020.106518">https://doi.org/10.1016/j.dib.2020.106518</a>, 2020.</p> <p>Auenhammer, R.M., L.P. Mikkelsen, L.E. Asp, B.J. Blinzler, X-ray tomography based numerical analysis of stress concentrations in non-crimp fabric reinforced composites - assessment of segmentation methods. <em>IOP Conf. Ser.: Mater. Sci. Eng.</em> <strong>942</strong>, 012038, <a href="https://doi.org/10.1088/1757-899X/942/1/012038">https://doi.org/10.1088/1757-899X/942/1/012038</a>, 2020</p> <p>The data-set contain data from three samples: A, E and G. </p> <p>For each sample the data are saved in the follow format</p> <ul> <li>X-ray scan: nii-files</li> <li>SEM scan: tif-files</li> <li>Abaqus files: inp-files </li> <li>X-ray setting: pdf-files</li> <li>SEM settings: hdr-ascii files</li> </ul> <p> </p>
Data from: Model sensitivity and use of the comparative finite element method in mammalian jaw mechanics: mandible performance in the Gray Wolf
Finite Element Analysis (FEA) is a powerful tool gaining use in studies of biological form and function. This method is particularly conducive to studies of extinct and fossilized organisms, as models can be assigned properties that approximate living tissues. In disciplines where model validation is difficult or impossible, the choice of model parameters and their effects on the results become increasingly important, especially in comparing outputs to infer function. To evaluate the extent to which performance measures are affected by initial model input, we tested the sensitivity of bite force, strain energy, and stress to changes in seven parameters that are required in testing craniodental function with FEA. Simulations were performed on FE models of a Gray Wolf (Canis lupus) mandible. Results showed that unilateral bite force outputs are least affected by the relative ratios of the balancing and working muscles, but only ratios above 0.5 provided balancing-working side joint reaction force relationships that are consistent with experimental data. The constraints modeled at the bite point had the greatest effect on bite force output, but the most appropriate constraint may depend on the study question. Strain energy is least affected by variation in bite point constraint, but larger variations in strain energy values are observed in models with different number of tetrahedral elements, masticatory muscle ratios and muscle subgroups present, and number of material properties. These findings indicate that performance measures are differentially affected by variation in initial model parameters. In the absence of validated input values, FE models can nevertheless provide robust comparisons if these parameters are standardized within a given study to minimize variation that arise during the model-building process. Sensitivity tests incorporated into the study design not only aid in the interpretation of simulation results, but can also provide additional insights on form and function.
Design and Analysis of Chiral and Achiral Metasurfaces with the Finite Element Method
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Data from: Model sensitivity and use of the comparative finite element method in mammalian jaw mechanics: mandible performance in the Gray Wolf
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Data from: Finite element modelling vs. classic beam theory: comparing methods for stress estimation in a morphologically diverse sample of vertebrate long bones
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Data from: Comparative finite-element analysis: a single computational modeling method can reliably estimate the mechanical properties of porcine and human vertebrae
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Models and data in support of "EMFEM: a parallel 3D modeling code for frequency-domain electromagnetic method using goal-oriented adaptive finite element method"
<p>These directories contain the model and data files for "EMFEM: a parallel 3D modeling code for frequency-domain electromagnetic method using goal-oriented adaptive finite element method".<br> </p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.