Zobrazeno 1 - 10
of 1 306
pro vyhledávání: '"Ávila, Francisco"'
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-B\'enard convection
Autor:
Vasanth, Joel, Rabault, Jean, Alcántara-Ávila, Francisco, Mortensen, Mikael, Vinuesa, Ricardo
Deep reinforcement learning (DRL) has found application in numerous use-cases pertaining to flow control. Multi-agent RL (MARL), a variant of DRL, has shown to be more effective than single-agent RL in controlling flows exhibiting locality and transl
Externí odkaz:
http://arxiv.org/abs/2407.21565
Autor:
Jeon, Joongoo, Rabault, Jean, Vasanth, Joel, Alcántara-Ávila, Francisco, Baral, Shilaj, Vinuesa, Ricardo
Flow control is key to maximize energy efficiency in a wide range of applications. However, traditional flow-control methods face significant challenges in addressing non-linear systems and high-dimensional data, limiting their application in realist
Externí odkaz:
http://arxiv.org/abs/2407.17822
The control efficacy of classical periodic forcing and deep reinforcement learning (DRL) is assessed for a turbulent separation bubble (TSB) at $Re_\tau=180$ on the upstream region before separation occurs. The TSB can resemble a separation phenomeno
Externí odkaz:
http://arxiv.org/abs/2403.20295
The symmetry-based turbulence theory has been used to derive new scaling laws for the streamwise velocity and temperature moments of arbitrary order. For this, it has been applied to an incompressible turbulent channel flow driven by a pressure gradi
Externí odkaz:
http://arxiv.org/abs/2401.16047
Publikováno v:
Biomedical Physics & Engineering Express, 2023
Objective. A detailed analysis of the corneal retardation time $\tau$ as a highly related parameter to the intraocular pressure (IOP), and its plausible role as an indicator of ocular hypertension disease. Approach. A simple theoretical expression fo
Externí odkaz:
http://arxiv.org/abs/2312.04397
In this investigation, we introduce the class of non-archimedean frames in spirit with the topological notion of non-archimedean spaces. We explore various properties of these frames - particularly their spaciality. We attach a base that constitutes
Externí odkaz:
http://arxiv.org/abs/2311.18095
Autor:
Suárez, Pol, Alcántara-Ávila, Francisco, Miró, Arnau, Rabault, Jean, Font, Bernat, Lehmkuhl, Oriol, Vinuesa, R.
This paper presents for the first time successful results of active flow control with multiple independently controlled zero-net-mass-flux synthetic jets. The jets are placed on a three-dimensional cylinder along its span with the aim of reducing the
Externí odkaz:
http://arxiv.org/abs/2309.02462
Autor:
Cohen, Theodore
Publikováno v:
Dictionary of Caribbean and Afro–Latin American Biography, 1 ed., 2016.
Externí odkaz:
http://www.oxfordreference.com/view/10.1093/acref/9780199935796.001.0001/acref-9780199935796-e-1782
Autor:
Vignon, Colin, Rabault, Jean, Vasanth, Joel, Alcántara-Ávila, Francisco, Mortensen, Mikael, Vinuesa, Ricardo
Rayleigh-B\'enard convection (RBC) is a recurrent phenomenon in several industrial and geoscience flows and a well-studied system from a fundamental fluid-mechanics viewpoint. However, controlling RBC, for example by modulating the spatial distributi
Externí odkaz:
http://arxiv.org/abs/2304.02370
Autor:
Varela, Pau, Suárez, Pol, Alcántara-Ávila, Francisco, Miró, Arnau, Rabault, Jean, Font, Bernat, García-Cuevas, Luis Miguel, Lehmkuhl, Oriol, Vinuesa, Ricardo
Deep artificial neural networks (ANNs) used together with deep reinforcement learning (DRL) are receiving growing attention due to their capabilities to control complex problems. This technique has been recently used to solve problems related to flow
Externí odkaz:
http://arxiv.org/abs/2211.02572