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SU2 code
ReleaseJanuary 2012; 14 years ago (2012-01)
Stable release
8.5.0[1] / 27 April 2026; 51 days ago (27 April 2026)
Written inC++, Python
Operating systemUnix/Linux/OS X/Windows
TypeComputational fluid dynamics, Simulation software
LicenseGNU Lesser General Public License, version 2.1
Websitesu2code.github.io
Repository


SU2 (formerly Stanford University Unstructured) is a suite of open-source software tools written in C++ and Python for the numerical solution of partial differential equations (PDE) and performing PDE-constrained optimization.[2] While initially developed for aerodynamics and compressible flow, it has evolved into a general-purpose multiphysics framework capable of simulating incompressible and compressible flows across all Mach regimes, species transport, conjugate heat transfer and combustion.

The framework is specialized for gradient-based design optimization using integrated continuous and discrete adjoint solvers. A distinguishing feature for researchers is its use of algorithmic differentiation (AD) to provide exact discrete adjoint sensitivities for complex multiphysics chains, including fluid-structure interaction (FSI) and conjugate heat transfer.[3] It supports unstructured meshes and offers extensibility through User Defined Functions (UDFs) and high-level Python wrappers.

To stimulate development and use of the software, the SU2 Foundation was established as a non-profit organization to coordinate the global community of users and developers. SU2 is released under the GNU Lesser General Public License (LGPL) version 2.1.


Developers

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SU2 is being developed by individuals and organized teams around the world. The original SU2 Lead Developers are: Dr. Francisco Palacios and Dr. Thomas D. Economon.

The most active groups developing SU2 are:


Capabilities

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SU2 is a general-purpose multiphysics suite designed for the simulation of partial differential equations (PDE) on unstructured meshes. The framework is built to handle complex multi-physics interactions through a multi-zone approach, allowing different physical models to be solved in connected domains.[2] Its current capabilities include:

  • Flow Regimes: Compressible and incompressible solvers for Euler, Navier-Stokes, and RANS equations across all Mach regimes (low-speed to hypersonic). For low Mach incompressible flow problems, preconditioning methods are used.
  • Turbulence & Transition Modeling:
  • Design Optimization: Gradient-based shape optimization using integrated continuous and discrete adjoint solvers. It utilizes algorithmic differentiation (via CoDiPack) for exact sensitivities in complex multiphysics chains.[10]
  • Topology Optimization: Gradient-based structural topology optimization with length scale control via black-white filters [11]
  • Multiphysics & Structures:
    • Solid Mechanics: Solvers for linear elasticity to model structural deformation.[2]
    • Thermal Analysis: Capability for conjugate heat transfer (CHT) to simulate heat exchange between fluid and solid regions.[12]
    • Fluid-Structure Interaction (FSI): Static and dynamic coupling between fluid and structural solvers.
  • Chemistry & Hypersonics:
    • Combustion: Reacting flow modeling using the Flamelet generated manifold (FGM) method.[13]
    • Hypersonics (NEMO): Simulation of high-enthalpy flows including thermo-chemical non-equilibrium and ionization with detailed chemistry modeling.[14]
  • Advanced Numerics: Support for high-order Discontinuous Galerkin Method (DG) for improved accuracy in vortex-dominated simulations.
  • User Interface & Ecosystem:
    • SU2-GUI: A graphical user interface for mesh importation and solver configuration.[15]
    • Automation: A high-level Python interface for workflow automation and support for User Defined Functions (UDFs).

License

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SU2 is free and open source software, released under the GNU General Public License version 3 (SU2 v1.0 and v2.0) and GNU Lesser General Public License version 2.1 (SU2 v2.0.7 and later versions).

Alternative software

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See also: List of computational fluid dynamics software

Free and open-source software

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Proprietary software

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References

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  1. ^ "Release 8.5.0". 27 April 2026. Retrieved 28 April 2026.
  2. ^ a b c Economon, Thomas D.; Palacios, Francisco; Copeland, Sean R.; Lukaczyk, Trent W.; Alonso, Juan J. (March 2016). "SU2: An Open-Source Suite for Multiphysics Simulation and Design". AIAA Journal. 54 (3): 828–846. Bibcode:2016AIAAJ..54..828E. doi:10.2514/1.J053813.
  3. ^ Albring, M.; Sagebaum, M.; Gauger, N. R. (June 2016). "Efficient Aerodynamic Design using the Discrete Adjoint Method in SU2". 17th AIAA/ISSMO MDAO Conference. doi:10.2514/6.2016-3518. ISBN 978-1-62410-439-8.
  4. ^ a b "SU2 Dev. Team at Stanford". su2code.github.io. Retrieved 15 March 2025.
  5. ^ a b "SU2/AUTHORS.md at master · su2code/SU2". GitHub. Retrieved 15 March 2025.
  6. ^ "SU2 Dev. Team at University of Kaiserslautern". su2code.github.io. Retrieved 15 March 2025.
  7. ^ Rausa, A.; et al. (2025). "SU2 results for the Fifth High Lift Prediction Workshop". AIAA SCITECH 2025 Forum. doi:10.2514/6.2025-0276.
  8. ^ Molina, E.; Zhou, B. Y.; Alonso, J. J.; Righi, M.; Silva, R. G. (2019). "Flow and Noise Predictions Around Tandem Cylinders using DDES approach with SU2". AIAA Scitech 2019 Forum. doi:10.2514/6.2019-0326.
  9. ^ Rausa, A.; Guardone, A; Auteri, F. (2023). "Implementation of the $\gamma-Re_\theta$ and one-equation transition model within SU2: model validation and verification". AIAA 2023. doi:10.2514/6.2023-1570. hdl:11311/1242117.
  10. ^ Albring, M.; Sagebaum, M.; Gauger, N. R. (June 2016). "Efficient Aerodynamic Design using the Discrete Adjoint Method in SU2". 17th AIAA/ISSMO MDAO Conference. doi:10.2514/6.2016-3518. ISBN 978-1-62410-439-8.
  11. ^ Gomes, P., Palacios, R. Aerodynamic-driven topology optimization of compliant airfoils. Struct Multidisc Optim 62, 2117–2130 (2020). https://doi.org/10.1007/s00158-020-02600-9
  12. ^ Burghardt, O.; Gauger, N. (2019). "Coupled Adjoints for Conjugate Heat Transfer in Variable Density Incompressible Flows". AIAA. doi:10.2514/6.2019-3668. ISBN 978-1-62410-589-0.
  13. ^ Mayer, D.; Beishuizen, N.; Pitsch, H.; Economon, T. D.; Carrigan, T. (August 2024). "Automatic adjoint-based design optimization for laminar combustion applications". Fuel. 370 131751. Bibcode:2024Fuel..37031751M. doi:10.1016/j.fuel.2024.131751.
  14. ^ Maier, W.; Needles, J.; Garbacz, C.; Morgado, F.; Alonso, J. J.; Fossati, M. (2021). "SU2-NEMO: An Open-Source Framework for High-Mach Nonequilibrium Multi-Species Flows". Aerospace. 8 (7): 193. Bibcode:2021Aeros...8..193M. doi:10.3390/aerospace8070193.
  15. ^ "SU2-GUI". github.com. Retrieved 18 April 2026.
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Official resources

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Community resources

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Further reading

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