Deep reinforcement learning for the control of conjugate heat transfer
From MaRDI portal
Publication:2131088
DOI10.1016/j.jcp.2021.110317OpenAlexW3108383420MaRDI QIDQ2131088
Elie Hachem, Jonathan Viquerat, Hassan Ghraieb, Aurélien Larcher, Philippe Meliga
Publication date: 25 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2011.15035
computational fluid dynamicsartificial neural networksconjugate heat transferthermal controldeep reinforcement learning
Basic methods in fluid mechanics (76Mxx) Incompressible viscous fluids (76Dxx) Diffusion and convection (76Rxx)
Related Items (5)
Multi-condition multi-objective optimization using deep reinforcement learning ⋮ Deep reinforcement learning for optimal well control in subsurface systems with uncertain geology ⋮ Multi-agent reinforcement learning aided sampling algorithms for a class of multiscale inverse problems ⋮ Multi-fidelity reinforcement learning framework for shape optimization ⋮ Reinforcement-learning-based control of convectively unstable flows
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Global modes in a confined impinging jet: application to heat transfer and control
- Metric construction by length distribution tensor and edge based error for anisotropic adaptive meshing
- A consistent approximate upwind Petrov-Galerkin method for convection- dominated problems
- Stabilized finite element method for incompressible flows with high Reynolds number
- Laminar and turbulent natural convection in an enclosed cavity
- Variational multiscale residual-based turbulence modeling for large eddy simulation of incompressible flows
- Simulation of high Rayleigh number natural convection in a square cavity using the lattice Boltzmann method
- Streamline upwind/Petrov-Galerkin formulations for convection dominated flows with particular emphasis on the incompressible Navier-Stokes equations
- The variational multiscale method -- a paradigm for computational mechanics
- Buoyancy-driven heat transfer enhancement in a two-dimensional enclosure utilizing nanofluids.
- Stabilization of incompressibility and convection through orthogonal sub-scales in finite element methods
- Robin-type boundary control problems for the nonlinear Boussinesq type equations
- Stabilized finite element approximation of transient incompressible flows using orthogonal subscales
- Comparison of some finite element methods for solving the diffusion-convection-reaction equation
- Time-accurate calculation and bifurcation analysis of the incompressible flow over a square cavity using variational multiscale modeling
- An optimal control problem for a generalized Boussinesq model: the time dependent case
- 3D tetrahedral, unstructured and anisotropic mesh generation with adaptation to natural and multidomain metric
- Advanced parallel computing in material forming with CIMLib
- Stabilized finite element solution to handle complex heat and fluid flows in industrial furnaces using the immersed volume method
- Immersed stress method for fluid-structure interaction using anisotropic mesh adaptation
- Immersed volume method for solving natural convection, conduction and radiation of a hat‐shaped disk inside a 3D enclosure
- Machine Learning for Fluid Mechanics
- Natural convection in a square cavity: A comparison exercise
- Natural convection flow in a square cavity revisited: Laminar and turbulent models with wall functions
- Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control
- Control of chaotic systems by deep reinforcement learning
- Learning representations by back-propagating errors
- Analysis of a Stabilized Finite Element Approximation of the Transient Convection‐Diffusion Equation Using an ALE Framework
- Optimization of semiconductor melts
This page was built for publication: Deep reinforcement learning for the control of conjugate heat transfer
