arXiv:2609.17160v1 Announce Type: new
Abstract: Machine-learning surrogate models offer a promising alternative to high-fidelity Computational Fluid Dynamics (CFD) simulations for aerodynamic analysi...
By Lionel Salesses, Caroline Sainvitu, Tariq Benamara
arXiv:2512. 17534v2 Announce Type: replace-cross Abstract: Modeling and controlling fluids is critical across science and engineering.
By Christian Lagemann, Sajeda Mokbel, Miro Gondrum, Mario R\"uttgers, Yuning Wang, Pol Su\'arez, Ludger Paehler, Deniz A. Bezgin, Aaron B. Buhendwa, Jared L. Callaham, Samuel Ahnert, Nicholas Zolman, Xiao Shao, Jean-Christophe Loiseau, Nikolaus Adams, Matthias Meinke, Wolfgang Schr\"oder, Kai Lagemann, Esther Lagemann, Ricardo Vinuesa, Steven L. Brunton
The paper presents a method where self‑evolving scientific agents design explicit, neural‑network‑free white‑box controllers for fluid dynamics tasks. By iteratively interpreting simulation data, the agents accumulate control knowledge and refine controller code, ultimately achieving robust control of an underactuated two‑joint swimmer in unsteady flows. The resulting controllers generalize across varying target positions, wake geometries, cylinder counts, and inflow speeds, and 2D control priors successfully transfer to accelerate 3D adaptation.
By Boai Sun, Wenjin Guo, Zongmin Yu, Liu Yang
The paper introduces a self‑evolving scientific agent that uses large language models and iterative code generation to build interpretable, physically‑reasoned white‑box controllers for complex systems. The agent deploys candidate controllers in simulations, diagnoses dynamic behavior from multimodal evidence, and refines source code until a robust policy is achieved. Applied to a nonlinear fluid‑structure interaction problem—a two‑joint dogfish swimmer navigating an unsteady wake—the agent autonomously designs a controller that consistently reaches targets across a wide range of conditions without retraining.
By Boai Sun, Wenjin Guo, Zongmin Yu, Liu Yang
arXiv:2606. 06077v1 Announce Type: cross Abstract: Autonomous underwater vehicle (AUV) launch and recovery (LAR) into the hull of an advancing host platform requires traversal of a complex, three-dimensional propeller wake whose hydrodynamic structure cannot be characterised by a uniform current model.
By Zachary Cooper-Baldock, Paulo E. Santos, Russell S. A. Brinkworth, Karl Sammut
arXiv:2608.29069v1 Announce Type: cross
Abstract: Operator-learning surrogates have been benchmarked largely on single-field, single-interface problems, leaving unclear whether architectural choices...
By Muhammad Abid, Arth Sojitra, Omer San