GiD is a universal, adaptive and user-friendly pre and postprocessor for numerical simulations in science and engineering. It has been designed to cover all the common needs in the numerical simulations field from pre to post-processing: geometrical modeling, effective definition of analysis data, meshing, data transfer to analysis software, as well as the visualization of numerical results. Universal: GiD is ideal for generating all the information required for the analysis of any problem in science and engineering using numerical methods: structured, unstructured or particle based meshes, boundary and loading conditions, material types, visualization of numerical results, etc. Adaptive: GiD is extremely easy to adapt to any numerical simulation code. In fact, GiD can be defined by the user to read and write data in an unlimited number of formats. GiD’s input and output formats can be customised and made compatible with an existing in-house software. The different menus can be tailored to the specific needs and desires of the user. User-friendly: the development of GiD has been focused on the needs of the user and on the simplicity, speed, effectiveness and accuracy the user demands at input data preparation and results visualization levels.

References in zbMATH (referenced in 18 articles )

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  1. Lee, Dong Seop; Periaux, Jacques; Lee, Sung Wook: Fast Nash hybridized evolutionary algorithms for single and multi-objective design optimization in engineering (2014)
  2. Neto, D.M.; Oliveira, M.C.; Menezes, L.F.; Alves, J.L.: Applying Nagata patches to smooth discretized surfaces used in 3D frictional contact problems (2014)
  3. Soudah, Eduardo; Rossi, Riccardo; Idelsohn, Sergio; Oñate, Eugenio: A reduced-order model based on the coupled 1D-3D finite element simulations for an efficient analysis of hemodynamics problems (2014)
  4. Barros, Felício B.; de Barcellos, Clovis S.; Duarte, C.Armando; Torres, Diego A.F.: Subdomain-based error techniques for generalized finite element approximations of problems with singular stress fields (2013)
  5. Otin, Ruben: ERMES: a nodal-based finite element code for electromagnetic simulations in frequency domain (2013)
  6. Dadvand, Pooyan; Rossi, Riccardo; Oñate, Eugenio: An Object-Oriented Environment For Developing Finite Element Codes For Multi-Disciplinary Applications (2010)
  7. Makrodimopoulos, Athanasios; Bhaskar, Atul; Keane, Andy J.: Second-order cone programming formulations for a class of problems in structural optimization (2010)
  8. Phansri, Bupavech; Park, Kyung-Ho; Warnitchai, Pennung: A BEM formulation for inelastic transient dynamic analysis using domain decomposition and particular integrals (2010)
  9. Lam, X.B.; Kim, Y.S.; Hoang, A.D.; Park, C.W.: Coupled aerostructural design optimization using the Kriging model and integrated multiobjective optimization algorithm (2009)
  10. Castelló, Walter B.; Flores, Fernando G.: A triangular finite element with local remeshing for the large strain analysis of axisymmetric solids (2008)
  11. Owatsiriwong, A.; Park, K.H.: A BEM formulation for transient dynamic elastoplastic analysis via particular integrals (2008)
  12. Peratta, A.: 3D low frequency electromagnetic modelling of the human eye with boundary elements: application to conductive keratoplasty (2008)
  13. Logg, Anders: Automating the finite element method (2007)
  14. Hauke, Guillermo; Doweidar, Mohamed H.; Miana, Mario: The multiscale approach to error estimation and adaptivity (2006)
  15. Mora, Javier; Otín, Rubén; Dadvand, Pooyan; Escolano, Enrique; Pasenau, Miguel A.; Oñate, Eugenio: Open tools for electromagnetic simulation programs (2006)
  16. Oñate, Eugenio; Arteaga, Joaquin; García, Julio; Flores, Roberto: Error estimation and mesh adaptivity in incompressible viscous flows using a residual power approach (2006)
  17. Idelsohn, Sergio R.; Calvo, Nestor; Oñate, Eugenio: Polyhedrization of an arbitrary 3D point set. (2003)
  18. Chiandussi, G.; Bugeda, G.; Oñate, E.: Shape variable definiton with $C^0$, $C^1$ and $C^2$ continuity functions (2000)