PetIGA

PetIGA: high-performance isogeometric analysis. This software framework implements a NURBS-based Galerkin finite element method (FEM), popularly known as isogeometric analysis (IGA). It is heavily based on PETSc, the Portable, Extensible Toolkit for Scientific Computation. PETSc is a collection of algorithms and data structures for the solution of scientific problems, particularly those modeled by partial differential equations (PDEs). PETSc is written to be applicable to a range of problem sizes, including large-scale simulations where high performance parallel is a must. PetIGA can be thought of as an extension of PETSc, which adds the NURBS discretization capability and the integration of forms. The PetIGA framework is intended for researchers in the numeric solution of PDEs who have applications which require extensive computational resources.


References in zbMATH (referenced in 53 articles , 1 standard article )

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  1. Ashour, Mohammed; Valizadeh, Navid; Rabczuk, Timon: Isogeometric analysis for a phase-field constrained optimization problem of morphological evolution of vesicles in electrical fields (2021)
  2. de Lucio, Mario; Bures, Miguel; Ardekani, Arezoo M.; Vlachos, Pavlos P.; Gomez, Hector: Isogeometric analysis of subcutaneous injection of monoclonal antibodies (2021)
  3. Hapla, Vaclav; Knepley, Matthew G.; Afanasiev, Michael; Boehm, Christian; van Driel, Martin; Krischer, Lion; Fichtner, Andreas: Fully parallel mesh I/O using PETSc DMPlex with an application to waveform modeling (2021)
  4. Kamensky, David: Open-source immersogeometric analysis of fluid-structure interaction using FEniCS and tIGAr (2021)
  5. Moutsanidis, Georgios; Li, Weican; Bazilevs, Yuri: Reduced quadrature for FEM, IGA and meshfree methods (2021)
  6. Widlund, O. B.; Zampini, S.; Scacchi, S.; Pavarino, L. F.: Block FETI-DP/BDDC preconditioners for mixed isogeometric discretizations of three-dimensional almost incompressible elasticity (2021)
  7. Bazilevs, Yuri; Kamensky, David; Moutsanidis, Georgios; Shende, Shaunak: Residual-based shock capturing in solids (2020)
  8. Du, Xiaoxiao; Zhao, Gang; Wang, Wei; Guo, Mayi; Zhang, Ran; Yang, Jiaming: NLIGA: a MATLAB framework for nonlinear isogeometric analysis (2020)
  9. Medina, David; Valizadeh, Navid; Samaniego, Esteban; Jerves, Alex X.; Rabczuk, Timon: Isogeometric analysis of insoluble surfactant spreading on a thin film (2020)
  10. Moutsanidis, Georgios; Long, Christopher C.; Bazilevs, Yuri: IGA-MPM: the isogeometric material point method (2020)
  11. Takacs, Stefan: Fast multigrid solvers for conforming and non-conforming multi-patch isogeometric analysis (2020)
  12. Temizer, İ.; Motamarri, P.; Gavini, V.: NURBS-based non-periodic finite element framework for Kohn-Sham density functional theory calculations (2020)
  13. Zhang, Xiaoxuan; Garikipati, Krishna: Machine learning materials physics: multi-resolution neural networks learn the free energy and nonlinear elastic response of evolving microstructures (2020)
  14. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in Python using sfepy (2019)
  15. Clavijo, S. P.; Sarmiento, A. F.; Espath, L. F. R.; Dalcin, L.; Cortes, A. M. A.; Calo, V. M.: Reactive (n)-species Cahn-Hilliard system: a thermodynamically-consistent model for reversible chemical reactions (2019)
  16. Garcia, Daniel; Pardo, David; Calo, Victor M.: Refined isogeometric analysis for fluid mechanics and electromagnetics (2019)
  17. Kamensky, David; Bazilevs, Yuri: \textsctIGAr: automating isogeometric analysis with \textscFEniCS (2019)
  18. Teichert, G. H.; Natarajan, A. R.; Van der Ven, A.; Garikipati, K.: Machine learning materials physics: integrable deep neural networks enable scale bridging by learning free energy functions (2019)
  19. Thai, H. P.; Chamoin, L.; Ha-Minh, C.: \textitAposteriori error estimation for isogeometric analysis using the concept of constitutive relation error (2019)
  20. Valizadeh, Navid; Rabczuk, Timon: Isogeometric analysis for phase-field models of geometric PDEs and high-order PDEs on stationary and evolving surfaces (2019)

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