Advances of the Python-based Fluid-Structure Interaction capabilities included in SU2
Nicola Fonzi, Vittorio Cavalieri, Alessandro De Gaspari, Sergio Ricci

TL;DR
This paper enhances the open-source SU2 code's Python-based Fluid-Structure Interaction framework, enabling efficient, high-fidelity aeroelastic simulations with standardized interfaces and a native solver, validated through diverse test cases.
Contribution
The authors extended SU2's FSI capabilities with a standardized interface, a native structural solver, and improved mesh deformation, facilitating easier, high-fidelity aeroelastic simulations.
Findings
Code performs well across all test cases
Validated against analytical, experimental, and wind tunnel data
Demonstrates potential for industrial aeroelastic applications
Abstract
Current research efforts in aeroelasticity aim at including higher fidelity aerodynamic results into the simulation frameworks. In the present effort, the Python--based Fluid--Structure Interaction framework of the well known SU2 code has been updated and extended to allow for efficient and fully open-source simulations of detailed aeroelastic phenomena. The interface has been standardised for easier inclusion of other external solvers and the comunication scheme between processors revisited. A native solver has been introduced to solve the structural equations coming from a Nastran--like Finite Element Model. The use of high level programming allows to perform simulations with ease and minimum human work. On the other hand, the Computational Fluid Dynamics code of choice has efficient lower level functions that provide a quick turnaround time. Further, the aerodynamic code is currently…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputational Fluid Dynamics and Aerodynamics · Fluid Dynamics and Vibration Analysis · Model Reduction and Neural Networks
