FUN3D

The solver has been applied to a number of complex large-scale problems by groups at NASA Langley, industry, and academia. (See the Applications section of this manual.) Internally, the software has been used to study airframe noise, space transportation vehicles, flow control devices using synthetic jets, the design of wind tunnel and flight experiments, and so forth. Boeing, Lockheed, Cessna, New Piper, and others have used the tools for applications such as high-lift, cruise performance, and studies of revolutionary concepts. The software has also been used for military applications, large-scale computer science research at national labs, as well as algorithmic studies performed at universities around the country. For example, researchers at Georgia Tech have been using FUN3D as their base for rotorcraft work.


References in zbMATH (referenced in 39 articles )

Showing results 1 to 20 of 39.
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  1. Ahrabi, Behzad R.; Mavriplis, Dimitri J.: An implicit block ILU smoother for preconditioning of Newton-Krylov solvers with application in high-order stabilized finite-element methods (2020)
  2. Chen, Wenqian; Ju, Yaping; Zhang, Chuhua: A collocated-grid spectral difference method for compressible flows (2020)
  3. Falsafioon, Mehdi; Arabi, Sina; Camarero, Ricardo; Guibault, Francois: Moving meshes in complex configurations using the composite sliding grid method (2020)
  4. Komala-Sheshachala, Sanjay; Sevilla, Ruben; Hassan, Oubay: A coupled HDG-FV scheme for the simulation of transient inviscid compressible flows (2020)
  5. Kumar, Vinay; Sharma, Atul; Singh, R. K.: Central upwind scheme based immersed boundary method for compressible flows around complex geometries (2020)
  6. Nishikawa, Hiroaki: A hyperbolic Poisson solver for tetrahedral grids (2020)
  7. Nishikawa, Hiroaki: On the loss and recovery of second-order accuracy with U-MUSCL (2020)
  8. Nishikawa, Hiroaki; White, Jeffery A.: An efficient cell-centered finite-volume method with face-averaged nodal-gradients for triangular grids (2020)
  9. Roget, Beatrice; Sitaraman, Jay; Lakshminarayan, Vinod; Wissink, Andrew: Prismatic mesh generation using minimum distance fields (2020)
  10. Rumpfkeil, Markus P.; Beran, Philip: Multi-fidelity surrogate models for flutter database generation (2020)
  11. Zhang, Xin-Lei; Michelén-Ströfer, Carlos; Xiao, Heng: Regularized ensemble Kalman methods for inverse problems (2020)
  12. Zhong, Dongdong; Sheng, Chunhua: A new method towards high-order weno schemes on structured and unstructured grids (2020)
  13. Ching, Eric J.; Lv, Yu; Gnoffo, Peter; Barnhardt, Michael; Ihme, Matthias: Shock capturing for discontinuous Galerkin methods with application to predicting heat transfer in hypersonic flows (2019)
  14. Du, Pan; Agarwal, Ramesh K.: Numerical drag prediction of NASA Common research models using different turbulence models (2019)
  15. Ahrabi, Behzad R.; Mavriplis, Dimitri J.: A scalable solution strategy for high-order stabilized finite-element solvers using an implicit line preconditioner (2018)
  16. Bakhvalov, Pavel; Kozubskaya, Tatiana: Reprint of: “EBR-WENO scheme for solving gas dynamics problems with discontinuities on unstructured meshes” (2018)
  17. Dong, Yidao; Deng, Xiaogang; Gao, Xiang; Xiong, Min; Wang, Guangxue: A comparative study of boundary conditions for the density-based solvers in the framework of OpenFoam (2018)
  18. Garicano-Mena, Jesús; Lani, Andrea; Degrez, Gérard: An entropy-variables-based formulation of residual distribution schemes for non-equilibrium flows (2018)
  19. Pan, Dongxin; Zhong, Chengwen; Zhuo, Congshan: An implicit gas-kinetic scheme for turbulent flow on unstructured hybrid mesh (2018)
  20. Antoniadis, Antonis F.; Tsoutsanis, Panagiotis; Drikakis, Dimitris: Assessment of high-order finite volume methods on unstructured meshes for RANS solutions of aeronautical configurations (2017)

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