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Learning effective reinforcement learning (RL) policies to solve real-world complex tasks can be quite challenging without a high-fidelity simulation environment. In most cases, we are only given imperfect simulators with simplified…

Machine Learning · Computer Science 2025-10-16 Haoyi Niu , Shubham Sharma , Yiwen Qiu , Ming Li , Guyue Zhou , Jianming Hu , Xianyuan Zhan

In ancient times, electricity was viewed as a spirit or soul residing in an inanimate substance. A fluid image was introduced in an attempt to visualize its movement. It was also an effort to concretize its nature into the realm of physical…

Physics Education · Physics 2019-10-30 Gerald Tembrevilla , Marina Milner-Bolotin , Stephen Petrina

This paper presents a Sim2Real (Simulation to Reality) approach to bridge the gap between a trained agent in a simulated environment and its real-world implementation in navigating a robot in a similar setting. Specifically, we focus on…

Robotics · Computer Science 2025-01-07 Murad Mehrab Abrar , Souryadeep Mondal , Michelle Hickner

In this contributed chapter, I review our current understanding of the applicability of hydrodynamics to modeling the quark-gluon plasma (QGP), focusing on the question of hydrodynamization/thermalization of the QGP and the anisotropic…

Nuclear Theory · Physics 2024-02-16 Michael Strickland

Hydrodynamic interactions between fluid-dispersed particles are ubiquitous in soft matter and biological systems and they give rise to intriguing collective phenomena. While it was reported that these interactions can facilitate…

Soft Condensed Matter · Physics 2022-08-29 Eric Cereceda-López , Dominik Lips , Antonio Ortiz-Ambriz , Artem Ryabov , Philipp Maass , Pietro Tierno

We consider the motion of rigid bodies in a potential fluid subject to certain nonholonomic constraints and show that it is described by Euler--Poincar\'e--Suslov equations. In the 2-dimensional case, when the constraint is realized by a…

Mathematical Physics · Physics 2013-06-20 Yuri N. Fedorov , Luis C. Garcia-Naranjo

We demonstrate experimentally the feasibility of applying reinforcement learning (RL) in flow control problems by automatically discovering active control strategies without any prior knowledge of the flow physics. We consider the turbulent…

Fluid Dynamics · Physics 2020-03-10 Dixia Fan , Liu Yang , Michael S Triantafyllou , George Em Karniadakis

The simulation-to-reality (sim-to-real) transfer of large-scale hydraulic robots presents a significant challenge in robotics because of the inherent slow control response and complex fluid dynamics. The complex dynamics result from the…

Robotics · Computer Science 2026-01-19 Minho Lee , Hyeonseok Kim , Jin Tak Kim , Sangshin Park , Jeong Hyun Lee , Jungsan Cho , Jemin Hwangbo

A 2D numerical hydrodynamics approach is considered for modelling recent experimental results on the oscillation and collective behavior of convective flows. Our simulations consider the rising dynamics of heated fluid columns in a…

Fluid Dynamics · Physics 2022-07-07 Attila Gergely , Zoltán Néda

In this paper, we study a nonlinear system of first order partial differential equations describing the macroscopic behavior of an ensemble of interacting self-propelled rigid bodies. Such system may be relevant for the modelling of bird…

Analysis of PDEs · Mathematics 2022-10-31 Pierre Degond , Amic Frouvelle , Sara Merino-Aceituno , Ariane Trescases

We present an investigation of vibrational features in water clusters performed by means of our recently established divide-and-conquer semiclassical approach [M. Ceotto, G. Di Liberto, and R. Conte, Phys. Rev. Lett. 119, 010401 (2017)].…

Chemical Physics · Physics 2018-04-05 Giovanni Di Liberto , Riccardo Conte , Michele Ceotto

We present the concepts of physics-based learning models (PBLM) and their relevance and application to the field of ship hydrodynamics. The utility of physics-based learning is motivated by contrasting generic learning models for regression…

Fluid Dynamics · Physics 2014-01-17 Gabriel D. Weymouth , Dick K. P. Yue

The world of nanoscales in fluidics is the frontier where the continuum of fluid mechanics meets the atomic, and even quantum, nature of matter. While water dynamics remains largely classical under extreme confinement, several experiments…

Mesoscale and Nanoscale Physics · Physics 2025-01-03 Baptiste Coquinot , Anna T. Bui , Damien Toquer , Angelos Michaelides , Nikita Kavokine , Stephen J. Cox , Lydéric Bocquet

To date it has not been possible to prove whether or not the three-dimensional incompressible Euler equations develop singular behaviour in finite time. Some possible singular scenarios, as for instance shock-waves, are very important from…

Fluid Dynamics · Physics 2009-11-11 Carlos Escudero

Recent development of a hydrodynamic model is discussed by putting an emphasis on realistic treatment of the early and late stages in relativistic heavy ion collisions. The model, which incorporates a hydrodynamic description of the…

Nuclear Theory · Physics 2008-11-26 Tetsufumi Hirano

Fish schooling is often modeled with self-propelled particles subject to phenomenological behavioral rules. Although fish are known to sense and exploit flow features, these models usually neglect hydrodynamics. Here, we propose a novel…

Biological Physics · Physics 2018-05-16 Audrey Filella , François Nadal , Clément Sire , Eva Kanso , Christophe Eloy

The recently developed framework of anisotropic hydrodynamics is generalized to describe the dynamics of coupled quark and gluon fluids. The quark and gluon components of the fluids are characterized by different dynamical anisotropy…

Nuclear Theory · Physics 2013-04-02 Wojciech Florkowski , Radoslaw Maj , Radoslaw Ryblewski , Michael Strickland

Viscous hydrodynamics serves as a successful mesoscopic description of the Quark-Gluon Plasma produced in relativistic heavy-ion collisions. In order to investigate, how such an effective description emerges from the underlying microscopic…

High Energy Physics - Theory · Physics 2023-11-16 Stephan Ochsenfeld , Sören Schlichting

We introduce a reinforcement learning (RL) environment to design and benchmark control strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The environment provides a framework for computationally-efficient,…

Fluid Dynamics · Physics 2023-02-09 L. Guastoni , J. Rabault , P. Schlatter , H. Azizpour , R. Vinuesa

Reinforcement learning-based quadruped robots excel across various terrains but still lack the ability to swim in water due to the complex underwater environment. This paper presents the development and evaluation of a data-driven…

Robotics · Computer Science 2024-10-02 Cong Wang , Aoming Liang , Fei Han , Xinyu Zeng , Zhibin Li , Dixia Fan , Jens Kober