FEBio: Finite Elements for Biomechanics. FEBio is a nonlinear finite element solver that is specifically designed for biomechanical applications. It offers modeling scenarios, constitutive models and boundary conditions that are relevant to many research areas in biomechanics. All features can be used together seamlessly, giving the user a powerful tool for solving 3D problems in computational biomechanics. The software is open-source, and pre-compiled executables for Windows, Mac OS X and Linux platforms are available.

References in zbMATH (referenced in 19 articles )

Showing results 1 to 19 of 19.
Sorted by year (citations)

  1. McLoone, Maryrose; Quinlan, Nathan J.: Coupling of the meshless finite volume particle method and the finite element method for fluid-structure interaction with thin elastic structures (2022)
  2. Florian Gacon; Christophe Godin; Olivier Ali: BVPy: A FEniCS-based Python package to ease the expression and study of boundary value problems in Biology. (2021) not zbMATH
  3. Mei, Yue; Liu, Jiahao; Guo, Xu; Zimmerman, Brandon; Nguyen, Thao D.; Avril, Stéphane: General finite-element framework of the virtual fields method in nonlinear elasticity (2021)
  4. Nikpasand, Maryam; Mahutga, Ryan R.; Bersie-Larson, Lauren M.; Gacek, Elizabeth; Barocas, Victor H.: A hybrid microstructural-continuum multiscale approach for modeling hyperelastic fibrous soft tissue (2021)
  5. Pybus, Hannah J.; Tatler, Amanda L.; Edgar, Lowell T.; O’Dea, Reuben D.; Brook, Bindi S.: Reduced biomechanical models for precision-cut lung-slice stretching experiments (2021)
  6. Guo, Liwei; Vardakis, John C.; Chou, Dean; Ventikos, Yiannis: A multiple-network poroelastic model for biological systems and application to subject-specific modelling of cerebral fluid transport (2020)
  7. Latorre, Marcos; Humphrey, Jay D.: Fast, rate-independent, finite element implementation of a 3D constrained mixture model of soft tissue growth and remodeling (2020)
  8. Meister, Felix; Passerini, Tiziano; Mihalef, Viorel; Tuysuzoglu, Ahmet; Maier, Andreas; Mansi, Tommaso: Deep learning acceleration of total Lagrangian explicit dynamics for soft tissue mechanics (2020)
  9. Cheng, Jie; Zhang, Lucy T.: A general approach to derive stress and elasticity tensors for hyperelastic isotropic and anisotropic biomaterials (2018)
  10. Kevin M Moerman: GIBBON: The Geometry and Image-Based Bioengineering add-On (2018) not zbMATH
  11. Mei, Yue; Hurtado, Daniel E.; Pant, Sanjay; Aggarwal, Ankush: On improving the numerical convergence of highly nonlinear elasticity problems (2018)
  12. Mihai, L. Angela; Safar, Alexander; Wyatt, Hayley: Debonding of cellular structures with fibre-reinforced cell walls under shear deformation (2018)
  13. Berger, Lorenz; Bordas, Rafel; Kay, David; Tavener, Simon: A stabilized finite element method for finite-strain three-field poroelasticity (2017)
  14. Mihai, L. Angela; Wyatt, Hayley; Goriely, Alain: A microstructure-based hyperelastic model for open-cell solids (2017)
  15. Rausch, Manuel K.; Humphrey, Jay D.: A computational model of the biochemomechanics of an evolving occlusive thrombus (2017)
  16. Weis, Jared A.; Miga, Michael I.; Yankeelov, Thomas E.: Three-dimensional image-based mechanical modeling for predicting the response of breast cancer to neoadjuvant therapy (2017)
  17. Casoni, E.; Jérusalem, A.; Samaniego, C.; Eguzkitza, B.; Lafortune, P.; Tjahjanto, D. D.; Sáez, X.; Houzeaux, G.; Vázquez, M.: Alya: computational solid mechanics for supercomputers (2015)
  18. Pauletti, M. Sebastian; Martinelli, Massimiliano; Cavallini, Nicola; Antolin, Pablo: Igatools: an isogeometric analysis library (2015)
  19. Tomic, Aleksandar; Grillo, Alfio; Salvatore, Federico: Poroelastic materials reinforced by statistically oriented fibres -- numerical implementation and application to articular cartilage (2014)

Further publications can be found at: http://febio.org/publications/