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| SU2 code | |
|---|---|
 | |
| Initial release | January 2012 |
| Stable release | 8.4.0[1]
/ 12 January 2026 |
| Written in | C++, Python |
| Operating system | Unix/Linux/OS X/Windows |
| Type | Computational fluid dynamics, Simulation software |
| License | GNU Lesser General Public License, version 2.1 |
| Website | su2code |
| 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
[edit]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:
- Prof. Juan J. Alonso's group at Stanford University.[4]
- Prof. Piero Colonna's group at Delft University of Technology.[5]
- Prof. Nicolas R. Gauger's group at Kaiserslautern University of Technology.[6]
- Prof. Alberto Guardone's group at Polytechnic University of Milan.[5]
- Prof. Rafael Palacios' group at Imperial College London.[4]
Capabilities
[edit]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:
- RANS Models: Includes several variants of the Spalart-Allmaras (SA) and Menter's Shear Stress Transport (SST) models, including curvature and rotation corrections (QCR).[7]. The turbulence models include classical wall functions.
- Scale-Resolving Methods: Support for Large eddy simulation (LES), Detached eddy simulation (DES), and Delayed Detached Eddy Simulation (DDES) for unsteady separated flows.[8]
- Transition Modeling: transition model.[9]
- 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
[edit]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
[edit]Free and open-source software
[edit]- Advanced Simulation Library (AGPL)
- Code Saturne (GPL)
- FreeFem++
- Gerris Flow Solver (GPL)
- OpenFOAM
Proprietary software
[edit]References
[edit]- ^ "Release 8.4.0". 12 January 2026. Retrieved 7 April 2026.
- ^ 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.
- ^ 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.
- ^ a b "SU2 Dev. Team at Stanford". su2code.github.io. Retrieved 15 March 2025.
- ^ a b "SU2/AUTHORS.md at master · su2code/SU2". GitHub. Retrieved 15 March 2025.
- ^ "SU2 Dev. Team at University of Kaiserslautern". su2code.github.io. Retrieved 15 March 2025.
- ^ Rausa, A.; et al. (2025). "SU2 results for the Fifth High Lift Prediction Workshop". AIAA SCITECH 2025 Forum. doi:10.2514/6.2025-0276.
- ^ 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.
- ^ 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.
- ^ 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.
- ^ 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
- ^ 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.
- ^ 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.
- ^ 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.
- ^ "SU2-GUI". github.com. Retrieved 18 April 2026.
External links
[edit]Further reading
[edit]- Economon, T. D.; Palacios, F.; Copeland, S. R.; Lukaczyk, T. W.; Alonso, J. 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.
- Bluhdorn, J.; Gomes, P.; Aehle, M.; Gauger, N. (March 2025). "Hybrid parallel discrete adjoints in SU2". Computers & Fluids. 289 106528. doi:10.1016/j.compfluid.2024.106528.
- 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.
- Rubino, A.; Vitale, S.; Colonna, P.; Pini, M. (2020). "Fully-turbulent adjoint method for the unsteady shape optimization of multi-row turbomachinery". Aerospace Science and Technology. 106 106132. Bibcode:2020AeST..10606132R. doi:10.1016/j.ast.2020.106132.
External links
[edit]- Official website
- SU2 Foundation – Official non-profit organization site
- SU2 on GitHub – Source code and development repository