ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView’s batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data. (Source:

References in zbMATH (referenced in 145 articles )

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  1. Allendes, Alejandro; Naranjo, César; Otárola, Enrique: Stabilized finite element approximations for a generalized Boussinesq problem: a posteriori error analysis (2020)
  2. Dougherty, E. T.; Turner, J. C.; Vogel, Frank: A computational investigation of preconditioning strategies and iterative methods for finite element based neurostimulation simulations (2020)
  3. 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)
  4. Hinz, Jochen; Helmig, Jan; Möller, Matthias; Elgeti, Stefanie: Boundary-conforming finite element methods for twin-screw extruders using spline-based parameterization techniques (2020)
  5. Jahn, Mischa; Montalvo-Urquizo, Jonathan: Modeling and simulation of keyhole-based welding as multi-domain problem using the extended finite element method (2020)
  6. Kasemer, Matthew; Dawson, Paul: A finite element methodology to incorporate kinematic activation of discrete deformation twins in a crystal plasticity framework (2020)
  7. Lorenzo, Guillermo; Hughes, T. J. R.; Reali, A.; Gomez, H.: A numerical simulation study of the dual role of (5\alpha)-reductase inhibitors on tumor growth in prostates enlarged by benign prostatic hyperplasia via stress relaxation and apoptosis upregulation (2020)
  8. Markus Frings, Norbert Hosters, Corinna Müller, Max Spahn, Christoph Susen, Konstantin Key, Stefanie Elgeti: SplineLib: A Modern Multi-Purpose C++ Spline Library (2020) arXiv
  9. Modarreszadeh, Amir; Timofeev, Evgeny: High-order numerical simulation of axisymmetric wave phase conjugation (2020)
  10. Tom Gustafsson; G. D. McBain: scikit-fem: A Python package for finite element assembly (2020) not zbMATH
  11. Vico, Felipe; Greengard, Leslie; O’Neil, Michael; Rachh, Manas: A fast boundary integral method for high-order multiscale mesh generation (2020)
  12. Agathos, Konstantinos; Chatzi, Eleni; Bordas, Stéphane P. A.: A unified enrichment approach addressing blending and conditioning issues in enriched finite elements (2019)
  13. Berger-Vergiat, Luc; Chen, Xiaocui; Waisman, Haim: Explicit and implicit methods for shear band modeling at high strain rates (2019)
  14. Castelli, G. F.; Dörfler, Willy: The numerical study of a microscale model for lithium-ion batteries (2019)
  15. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in Python using sfepy (2019)
  16. Dunbar, Oliver R. A.; Lam, Kei Fong; Stinner, Björn: Phase field modelling of surfactants in multi-phase flow (2019)
  17. Fang, Rui; Kronbichler, Martin; Wurzer, Maximilian; Wall, Wolfgang A.: Parallel, physics-oriented, monolithic solvers for three-dimensional, coupled finite element models of Lithium-ion cells (2019)
  18. Feng, Xinzeng; Hormuth, David A. II; Yankeelov, Thomas E.: An adjoint-based method for a linear mechanically-coupled tumor model: application to estimate the spatial variation of murine glioma growth based on diffusion weighted magnetic resonance imaging (2019)
  19. Frérot, Lucas; Bonnet, Marc; Molinari, Jean-François; Anciaux, Guillaume: A Fourier-accelerated volume integral method for elastoplastic contact (2019)
  20. Frolov, Roman: An efficient algorithm for the multicomponent compressible Navier-Stokes equations in low- and high-Mach number regimes (2019)

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