TAU

Overview of the hybrid RANS code TAU. A brief introduction is given which first describes the history of frame in which the TAU code was developed before explaining the main advantages which were the drivers for the selection of the approach. In the following an algorithmic overview describes shortly the code functionality before a section about the code design gives some more insight about the implementation and its scripting capability.


References in zbMATH (referenced in 47 articles , 1 standard article )

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  1. Lozano, Carlos: On mesh sensitivities and boundary formulas for discrete adjoint-based gradients in inviscid aerodynamic shape optimization (2017)
  2. Pinto, Runa Nivea; Afzal, Asif; D’Souza, Loyan Vinson; Ansari, Zahid; Mohammed Samee, A. D.: Computational fluid dynamics in turbomachinery: a review of state of the art (2017)
  3. Stück, Arthur: Dual-consistency study for Green-Gauss gradient schemes in an unstructured Navier-Stokes method (2017)
  4. Wasserman, M.; Mor-Yossef, Y.; Greenberg, J. B.: A positivity-preserving, implicit defect-correction multigrid method for turbulent combustion (2016)
  5. Schillings, C.; Schulz, V.: On the influence of robustness measures on shape optimization with stochastic uncertainties (2015)
  6. Stück, Arthur: An adjoint view on flux consistency and strong wall boundary conditions to the Navier-Stokes equations (2015)
  7. Langer, Stefan: Agglomeration multigrid methods with implicit Runge-Kutta smoothers applied to aerodynamic simulations on unstructured grids (2014)
  8. Brandfass, B.; Alrutz, T.; Gerhold, T.: Rank reordering for MPI communication optimization (2013) ioport
  9. Kowollik, D.; Tini, V.; Reese, S.; Haupt, M.: 3D fluid-structure interaction analysis of a typical liquid rocket engine cycle based on a novel viscoplastic damage model (2013)
  10. Rosenbaum, Benjamin; Schulz, Volker: Efficient response surface methods based on generic surrogate models (2013)
  11. Zimmermann, R.: On the maximum likelihood training of gradient-enhanced spatial Gaussian processes (2013)
  12. Auerswald, Torsten; Bange, Jens; Knopp, Tobias; Weinman, Keith; Radespiel, Rolf: Large-Eddy Simulations of realistic atmospheric turbulence with the DLR-TAU-code initialized by in situ airborne measurements (2012)
  13. Borzì, Alfio; Schulz, Volker: Computational optimization of systems governed by partial differential equations (2012)
  14. Langer, Stefan: Investigation and application of point implicit Runge-Kutta methods to inviscid flow problems (2012)
  15. Lozano, Carlos: Discrete surprises in the computation of sensitivities from boundary integrals in the continuous adjoint approach to inviscid aerodynamic shape optimization (2012)
  16. Michler, Andreas K.; Heinrich, Ralf: Surrogate-enhanced simulation of aircraft in trimmed state (2012)
  17. Rosenbaum, Benjamin; Schulz, Volker: Comparing sampling strategies for aerodynamic kriging surrogate models (2012)
  18. Michler, Andreas K.: Aircraft control surface deflection using RBF-based mesh deformation (2011)
  19. Ray, J.; Armstrong, R.; Safta, C.; Debusschere, B. J.; Allan, B. A.; Najm, H. N.: Computational frameworks for advanced combustion simulations (2011)
  20. Özkaya, Emre; Gauger, Nicolas R.: Automatic transition from simulation to one-shot shape optimization with Navier-Stokes equations (2010)

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Further publications can be found at: http://tau.dlr.de/literature/