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All Topics > Biocomputational Focus > Physics-Based Simulation |
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149 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
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OpenSim
- OpenSim is a freely available, user extensible software system that lets users develop models of musculoskeletal structures and create dynamic simulations of movement.
Find out how to join the community and see the work being performed using OpenSim at <a href="http://opensim.stanford.edu">opensim.stanford.edu</a>.
Access all of our OpenSim resources at the new <br /><a href="http://opensim.stanford.edu/support/index.html"><b style="color:#900; font-size:16px;">Support Site</b></a>.
Watch our <a href="http://www.youtube.com/watch?v=ME0VHfCtIM0">Introductory Video</a> get an overview of the OpenSim project and see how modeling can be used to help plan surgery for children with cerebral palsy.
<iframe width="560" height="315" src="https://www.youtube.com/embed/ME0VHfCtIM0" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> | |
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Registered: 2006-03-23 18:48 |
OpenMM
- OpenMM is a toolkit for molecular simulation. It can be used either as a stand-alone application for running simulations, or as a library you call from your own code. It
provides a combination of extreme flexibility (through custom forces and integrators), openness, and high performance (especially on recent GPUs) that make it truly unique among simulation codes.
<b>NEED HELP?</b> Check out the discussion forums under <a href="https://simtk.org/forums/viewforum.php?f=161">Public Forums</a> and the material from our workshops under <a href="https://simtk.org/project/xml/downloads.xml?group_id=161">Downloads</a>.
<b>GET STARTED QUICKLY:</b> Tutorials and sample scripts to run OpenMM are available in the <a href="http://wiki.simtk.org/openmm/VirtualRepository">OpenMM Code Repository</a>.
<b>SOURCE CODE:</b> The source code for OpenMM is available under <a href="https://simtk.org/project/xml/downloads.xml?group_id=161">Downloads</a> and also from the <a href="http://www.github.com/SimTk/openmm">Github Source Code Repository</a>.
<b>BENCHMARKS:</b> A collection of <a href="http://wiki.simtk.org/openmm/Benchmarks">benchmarks</a> is available to show the performance of OpenMM simulating a variety of molecular systems.
<b>CITING OPENMM:</b> Any work that uses OpenMM should cite the papers listed on the <a href="https://simtk.org/project/xml/publications.xml/?group_id=161">Publications</a> page. | |
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Registered: 2006-11-16 18:27 |
Open Knee(s): Virtual Biomechanical Representations of the Knee Joint
- Open Knee(s) was aimed to provide free access to three-dimensional finite element representations of the knee joint (<A HREF="https://doi.org/10.1007/s10439-022-03074-0">https://doi.org/10.1007/s10439-022-03074-0</A>). The development platform remains open to enable any interested party to use, test, and edit the model; in a nut shell get involved with the project.
This study was primarily funded by the National Institute of General Medical Sciences, National Institutes of Health (R01GM104139) and in part by National Institute of Biomedical Imaging and Bioengineering (R01EB024573 and R01EB025212). Previous activities leading towards this project had been partially funded by the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (R01EB009643).
Open Knee(s) by Open Knee(s) Development Team is licensed under a <A HREF="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</A>.
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Registered: 2010-02-18 20:41 |
SimVascular: Cardiovascular Modeling and Simulation
- SimVascular is an open source software suite for cardiovascular simulation, providing a complete pipeline from medical image data to 3D model construction, meshing, and blood flow simulation. SimVacular represents the state of the art in cardiovascular simulation, including advanced tools for physiologic boundary conditions, fluid structure interaction, and an accurate and efficient finite element Navier-Stokes solver. SimVascular integrates custom code with best-in-class open source packages to support clinical and basic science research.
DOCUMENTATION and CLINICAL EXAMPLES are available on the main project website at:
http://www.simvascular.org
Demo projects and examples for SimVascular can be downloaded at:
https://simtk.org/projects/sv_tests
Interested users should join the mailing list for the SimVascular project on simtk.org to be notified about upcoming releases and workshop announcements.
<b>If you use SimVascular for your work, please cite the following publication:</b>
Updegrove, A., Wilson, N., Merkow, J., Lan, H., Marsden, A. L. and Shadden, S. C., <a href="http://link.springer.com/article/10.1007/s10439-016-1762-8">SimVascular - An open source pipeline for cardiovascular simulation</a>, <em>Annals of Biomedical Engineering</em> (2016). DOI:10.1007/s10439-016-1762-8
The SimVascular project is funded by the NSF SSI program under Program Officers Rajiv Ramnath (ACI) and Sumanta Acharya (CBET). | |
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Registered: 2007-03-13 21:42 |
Reproducibility in simulation-based prediction of natural knee mechanics
- Modeling and simulation offers a cost-effective and prompt path to respond to the pressing medical needs for restoration of knee function. However, the reproducibility of simulation results, to inform scientific and clinical decision making, is questionable. Reproducibility is a pressing issue in scientific conduct. For modeling and simulation, there is added scrutiny particularly with the desire to repurpose and reuse virtual specimens for prospective solutions of diverse scientific and clinical problems. A significant portion of the modeling and simulation workflow includes development, evaluation, and simulation. This workflow, while based on objective scientific principles, commonly requires intuition during implementation; therefore relies on the knowledge and expertise of the modeler. This ‘art of modeling’ can be a fundamental source of diminished reproducibility. The goal of this study is to understand how modelers’ choices to build models, even when using the same data, may influence predictions and therefore the reproducibility of simulation results. Five modeling and simulation teams will independently develop, calibrate and benchmark computational models of knees based on the same data sets and reuse these models to simulate the same scientifically and clinically relevant scenarios. Ideally, predicted joint and tissue mechanics will be the same. In practice, the skills and experiences of model developers will reflect upon their modeling choices; and as a result, discrepancies will exist. The proposed activity will document the magnitude and potential sources of such discrepancies through comparisons of model components and simulation results. This project will examine and critique the current state of model development and simulation reproducibility in joint and tissue mechanics. This will translate into reliable models of the knee joint for simulation-based discoveries and in silico design and evaluation of medical devices and interventions. The required exchange of data, model components, and simulation results among the teams and with the public will also impact developers and users of such resources. Specifications, to facilitate data and model exchange and to develop data and modeling standards, and guidance, to inform modeling and simulation workflows, will likely emerge as by-products of the research activity. Subsequently, this project aims to curate various modeling & simulation and data resources for scientific and clinical investigations of knee biomechanics. An additional goal of the project site is to be a discussion platform among investigators who collect data and build models for the knee joint. | |
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Registered: 2015-12-07 21:06 |
Calibrated EMG-Informed Neuromusculoskeletal Modelling Toolbox (CEINMS)
- The software permits the simulation of all the transformations that take place from the onset of muscle excitation to the generation of force in 34 musculotendon units and the resulting moments about six degrees of freedom (DOFs) in the lower extremity. The selected DOFs include: hip flexion-extension, hip adduction-abduction, hip internal-external rotation, knee flexion-extension, ankle plantar-dorsi flexion, and ankle subtalar angle.
Experimentally recorded electromyography (EMG) signals and three-dimensional joint angles can be used to determine the neural drive and the instantaneous kinematics for the multiple musculotendon units being modelled. Furthermore, the CEINMS software can estimate the excitation patterns for musculotendon units from which EMGs cannot be experimentally measured and adjust the EMG linear envelopes that may be subject to measurement errors and uncertainties, while ensuring dynamical consistency in the predicted joint moments.
Finally, the CEINMS software allows automatically identification of a number of parameters that determine the way musculotendon units activate and contract, which vary non-linearly across individuals. This is done via an optimization-based calibration procedure that adjusts the internal parameters to best reflect the anatomy and physiology of an individual. | |
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Activity Percentile: 96.26 Registered: 2013-02-19 05:59 |
OpenArm: Volumetric & Time Series Models of Muscle Deformation
- We invite anyone in the research community to use the OpenArm and OpenArm Multisensor data sets to validate existing muscle deformation models or to devise new ones.
Full details can be found in the following papers:
Laura A. Hallock, Bhavna Sud, Chris Mitchell, Eric Hu, Fayyaz Ahamed, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Toward Real-Time Muscle Force Inference and Device Control via Optical-Flow-Tracked Muscle Deformation." In IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). IEEE, 2021. (Under review.)
Laura Hallock, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Muscle deformation correlates with output force during isometric contraction." In IEEE RAS/EMBS International Conference on Biomedical Robotics & Biomechatronics (BioRob). IEEE, 2020. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2020biorob.)
Yonatan Nozik*, Laura A. Hallock*, Daniel Ho, Sai Mandava, Chris Mitchell, Thomas Hui Li, and Ruzena Bajcsy, "OpenArm 2.0: Automated Segmentation of 3D Tissue Structures for Multi-Subject Study of Muscle Deformation Dynamics," in International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2019. *Equal contribution. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/nozikhallock2019embc.)
Laura Hallock, Akira Kato, and Ruzena Bajcsy. "Empirical quantification and modeling of muscle deformation: Toward ultrasound-driven assistive device control." In IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2018icra.)
This project is currently in development in the Human-Assistive Robotic Technologies (HART) Lab at the University of California, Berkeley (http://hart.berkeley.edu). | |
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Registered: 2018-11-28 20:40 |
SimVascular: Examples and Clinical Cases
- We invite you to download and try these examples and clinical case projects, which are all compatible with the open source SimVascular cardiovascular modeling software package. Each case includes image data of a healthy or diseased individual, a 3D anatomic model created from the image data, and simulation job files which specify initial conditions, boundary conditions and various parameters required to run the simulation. Many of the cases are already organized as SV projects, which means you can easily load them into SimVascular and view or try out various project components. Following the guides in the SimVascular documentation website, you can also create new models and run simulations with different conditions, based on these example cases.
You are free to download the examples and cases provided that you properly reference the source. The cases are part of the academic output of the researcher cited and should be referred to as such. Permission is granted to use these cases for research purposes, but for commercial use please contact the director of the Cardiovascular Biomechanics Computation Lab, Alison Marsden (amarsden@stanford.edu).
The examples and clinical cases included are:
Example: Demo Project
Example: Cylinder Project (no image, for simulation)
Clinical Case: Coronary Normal
Clinical Case: Aortofemoral Normal 1
Clinical Case: Aortofemoral Normal 2
Clinical Case: Healthy Pulmonary
SimVascular is available for download at our project website at:
https://simtk.org/projects/simvascular
Comprehensive documentation is available on the SimVascular website at:
http://www.simvascular.org
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Activity Percentile: 94.86 Registered: 2014-03-14 20:12 |
Grand Challenge Competition to Predict In Vivo Knee Loads
- Knowledge of muscle and joint contact forces during gait is necessary to characterize muscle coordination and function as well as joint and soft-tissue loading. Musculoskeletal modeling and simulation is required to estimate muscle and joint contact forces, since direct measurement is not feasible under normal conditions. This project provides the biomechanics community with a unique and comprehensive data set to validate muscle and contact force estimates in the knee. This data set includes motion capture, ground reaction, EMG, tibial contact force, and strength data collected from a subject implanted with an instrumented knee prosthesis. | |
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Activity Percentile: 93.46 Registered: 2009-07-14 23:24 |
Statistical analysis of conformational ensembles
- This project provides computational tools and methods to analyze conformational ensembles of biomolecules, as well as their assemblies, such as those obtained from molecular simulations.
(A) PROTEINS: The molecular understanding of the functional regulation of proteins requires assessment of various states, including active and inactive states, as well as their interdependencies. For several proteins, their various states can be distinguished from each other on the basis of their minimum energy 3D structures. For many other proteins, like GPCRs, PDZ domains, nuclear transcription factors, heat shock proteins, T-cell receptors and viral attachment proteins, their states can be distinguished categorically from each other only when their finite-temperature conformational ensembles are considered alongside their minimum-energy structures. We are developing tools/methods for:
(A1) Direct comparison of conformational ensembles - The traditional approach to compare two or more conformational ensembles is to compare their respective summary statistics. This approach is, however, prone to artifactual bias, as data is compared after dimensionality reduction. The proper way to compare ensembles is to compare them directly with each other and prior to any dimensionality reduction. g_ensemble_comp is a tool we have developed that does just that and reports the difference between ensembles in terms of a true metric defined by the zeroth law of thermodynamics.
(A2) Prediction of allosteric signaling networks - method under development.
(B) LIPID MEMBRANES: The surface area of a lipid bilayer is related fundamentally to many other observables, such as thermal phase transitions and domain formation in mixed lipid bilayers. We have developed g_tessellate_area to compute the 3D surface area of a bilayer using Delunay tessellation. | |
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Activity Percentile: 92.99 Registered: 2015-09-15 17:52 |
Are subject-specific musculoskeletal models robust to parameter identification?
- This study analyzed the sensitivity of the predictions of an MRI-based musculoskeletal model (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the unavoidable uncertainties in parameter identification, i.e., body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. | |
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Activity Percentile: 92.52 Registered: 2014-11-10 15:19 |
Full Body Model for use in Dynamic Simulations of Human Gait
- Our paper describes a full body OpenSim model with musculotendon parameters derived from experimental measurements of 21 cadaver lower limbs and magnetic resonance images of 24 young adult subjects. Our model is derived from the lower body model published by Arnold et al. (2010) and the tracking upper body by Hamner et al. (2013), but updates the muscle force distribution to reflect those of a young, healthy population, includes a new knee model to accurately represent internal forces, and simplified muscle wrapping surfaces to increase computation speed in CMC and other muscle-driven simulations. | |
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Activity Percentile: 91.59 Registered: 2012-06-11 22:52 |
SCONE: Open Source Software for Predictive Simulation
- If SCONE is helpful for your research, please cite the following paper:
Geijtenbeek, T (2019). SCONE: Open Source Software for Predictive Simulation of Biological Motion. Journal of Open Source Software, 4(38), 1421, https://doi.org/10.21105/joss.01421 | |
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Registered: 2016-10-27 13:07 |
Validation of Subject-Specific Knee Models from In Vivo Measurements
- Working models, data, code, and results for work to validate that in vivo methods for measuring laxity and obtaining knee geometry are comparable to methods previously standard for knee modeling of in vitro specimens.
This dataset is part of an ongoing manuscript to validate that sources of data from currently available in vivo methods are sufficient to create computational models of the knee compared with existing in vitro techniques. The data included in this repository is for the S192803 specimen of that dataset and includes experimental data, working models, code, and results obtained for that model and used in that manuscript.
The dataset contains experimental data, models, code, and results for the S192803 specimen data. This dataset is one of two model datasets used in the paper Validation of Subject-Specific Knee Models from In Vivo Measurements, which is in review at the Journal of Biomechanical Engineering. The dataset contained herein is derived from the experimental data collected during a previous publication in the Journal of Medical Devices, entitled: "Apparatus for In Vivo Knee Laxity Assessment Using High-Speed Stereo Radiography". Available at: https://doi.org/10.1115/1.4051834
A similar dataset exists for the other specimen, S193761.
Work was created by Dr. Thor E. Andreassen, Dr. Donald R. Hume, Dr. Landon D. Hamilton, Stormy L. Hegg, Sean E. Higinbotham, and Dr. Kevin B. Shelburne at the Center for Orthopaedic Biomechanics at the University of Denver.
The work was funded by the NIH National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Biomedical Imaging and Bioengineering, and the National Institute of Child Health and Human Development (Grant U01 AR072989).
If you have any questions, please email the main author, Dr. Thor Andreassen, at thor.andreassen@du.edu
Sharing/USE
This Code/Software is free to use for any reason. However, we ask that if you use any part of this work, that you cite the original two works that made it possible:
Andreassen, T. E., Hamilton, L. D., Hume, D., Higinbotham, S. E., Behnam, Y., Clary, C., and Shelburne, K. B. (September 10, 2021). "Apparatus for In Vivo Knee Laxity Assessment Using High-Speed Stereo Radiography." ASME. J. Med. Devices. December 2021; 15(4): 041004. https://doi.org/10.1115/1.4051834
Andreassen, T. E., Hume, D. R., Hamilton, L. D., Hegg, S.L., Higinbotham, S. E., and Shelburne, K. B. "Validation of Subject-Specific Knee Models from In Vivo Measurements." ASME. J. Biomech, Engineering.
Liability Agreement
The Data is provided “as is” with no express or implied warranty or guarantee. The University of Denver and the Center for Orthopaedic Biomechanics do not accept any liability or provide any guarantee in connection with uses of the Data, including but not limited to, fitness for a particular purpose and noninfringement. The University of Denver and the Center for Orthopaedic Biomechanics are not liable for direct or indirect losses or damage, of any kind, which may arise through the use of this data. | |
Registered: 2023-12-12 23:13 |
Delft Shoulder and Elbow Model
- This project is for development and support for users of the Delft Shoulder and Elbow Model, a large-scale, 3D musculoskeletal model. Development is ingoing, with a number of enhancements since the original description in van der Helm (1994), and the model has been widely used. | |
Registered: 2009-12-04 10:32 |
Model of the Scapulothoracic Joint
- In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapula kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapula kinematics to be accurate to within 2 mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications, is freely available as an OpenSim 3.2 plugin, and is customizable and usable with other OpenSim models. | |
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Activity Percentile: 85.98 Registered: 2015-01-14 23:10 |
Evertor and invertor muscle co-activation prevents ankle inversion injury
- The study described in this publication used musculoskeletal simulations to compare the capacity of planned invertor/evertor co-activation versus stretch reflexes with physiologic delay to prevent ankle inversion injuries. To achieve this, developed a novel model, muscle stretch controllers, and muscle reflex controllers for simulating landing in OpenSim. By freely providing the models, software plugins defining the controllers, and the resulting simulations, we hope to enable others to answer questions about landing control and injuries using simulations.
All models, data, and simulation results are provided in the downloads area of this project.
For software and sourcecode defining the novel stretch feedback controller and stretch reflex controller, see the related repository on GitHub.
https://github.com/msdemers/opensim-reflex-controllers
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Activity Percentile: 85.05 Registered: 2015-07-20 20:18 |
OpenSim Moco
- OpenSim Moco is a software toolkit to solve optimal control problems with musculoskeletal models defined in OpenSim, including those with kinematic constraints. Using the direct collocation method, Moco can solve a wide range of problems, including motion tracking, motion prediction, and parameter optimization. The design of Moco focuses on ease-of-use, customizability, and extensibility. Just like OpenSim itself, Moco has interfaces in XML/command-line, Matlab, Python, Java, and C++.
<ul style="line-height: 100%;">
<li><a href="https://opensim.stanford.edu/moco">Read the <b>documentation</b></a></li>
<li><a href="https://github.com/opensim-org/opensim-moco">View the source code, report bugs, suggest features, or contribute on <b>GitHub</b></a></li>
<li><a href="https://www.biorxiv.org/content/10.1101/839381v1">Read the Moco preprint on <b>bioRxiv</b></a></li>
<li><a href="https://github.com/stanfordnmbl/mocopaper">Obtain the models, data, and code used to produce the Moco preprint</a></li>
<li><a href="https://opensim.stanford.edu/support/event_details.php?id=236&title=Webinar-OpenSim-Moco-Software-to-optimize-the-motion-and-control-of-OpenSim-models">Watch the recording of the Moco <b>webinar</b> from November, 2019</a></li>
</ul> | |
Registered: 2019-11-03 22:27 |
Dynamic Arm Simulator
- This project aims to develop a musculoskeletal model for the real-time, dynamic simulation of arm movement. It features a large-scale model of the shoulder and elbow, including the joints of the shoulder girdle and scapulo-thoracic contact. The simulation is implemented using a Matlab MEX function and uses OpenSim for pre-processing and visualisation. | |
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Registered: 2008-07-24 18:10 |
Practical Annotation and Exchange of Virtual Anatomy
- Representation of anatomy in a virtual form is at the heart of clinical decision making, biomedical research, and medical training. Virtual anatomy is not limited to description of geometry but also requires appropriate and efficient labeling of regions - to define spatial relationships and interactions between anatomical objects; effective strategies for pointwise operations - to define local properties, biological or otherwise; and support for diverse data formats and standards - to facilitate exchange between clinicians, scientists, engineers, and the general public. Development of aeva, a free and open source software package (library, user interfaces, extensions) capable of automated and interactive operations for virtual anatomy annotation and exchange, is in response to these currently unmet requirements. This site serves for aeva outreach, including dissemination the software and use cases. The use cases drive design and testing of aeva features and demonstrate various workflows that rely on virtual anatomy.
aeva downloads:
Downloads (https://simtk.org/frs/?group_id=1767)
Kitware data repository (https://data.kitware.com/#folder/5e7a4690af2e2eed356a17f2)
aeva documentation:
Guides and tutorials (https://aeva.readthedocs.io)
aeva videos:
Short instructions (https://www.youtube.com/channel/UCubfUe40LXvBs86UyKci0Fw)
aeva source code:
Kitware source code repository (https://gitlab.kitware.com/aeva)
aeva forum:
Forums (https://simtk.org/plugins/phpBB/indexPhpbb.php?group_id=1767 ) | |
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Registered: 2019-08-28 01:27 |
149 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5> <6> <7> <8>