Topology optimization of turbulent flows
The aim of this work is to present a fast and viable approach for taking into account
turbulence in topology optimization of complex fluid flow systems, without resorting to any …
turbulence in topology optimization of complex fluid flow systems, without resorting to any …
Comparative analysis of machine learning methods for active flow control
Machine learning frameworks such as genetic programming and reinforcement learning
(RL) are gaining popularity in flow control. This work presents a comparative analysis of the …
(RL) are gaining popularity in flow control. This work presents a comparative analysis of the …
Three-dimensional large-scale aerodynamic shape optimization based on shape calculus
Large-scale three-dimensional aerodynamic shape optimization based on the compressible
Euler equations is considered. Shape calculus is used to derive an exact surface formulation …
Euler equations is considered. Shape calculus is used to derive an exact surface formulation …
[HTML][HTML] A discrete adjoint method for pressure-based algorithms
B Fleischli, L Mangani, A Del Rio, E Casartelli - Computers & Fluids, 2021 - Elsevier
A discrete adjoint method implemented in a coupled pressure-based RANS solver is
presented in this paper. The adjoint equations are solved using an adjoint fixed point …
presented in this paper. The adjoint equations are solved using an adjoint fixed point …
Optimal perturbations for controlling the growth of a Rayleigh–Taylor instability
A discrete adjoint-based method is employed to control multi-mode Rayleigh–Taylor (RT)
instabilities via strategic manipulation of the initial interfacial perturbations. We seek to find …
instabilities via strategic manipulation of the initial interfacial perturbations. We seek to find …
Adjoint-based machine learning for active flow control
We develop neural-network active flow controllers using a deep learning partial differential
equation augmentation method (DPM). The end-to-end sensitivities for optimization are …
equation augmentation method (DPM). The end-to-end sensitivities for optimization are …
A practical discrete-adjoint method for high-fidelity compressible turbulence simulations
Methods and computing hardware advances have enabled accurate predictions of complex
compressible turbulence phenomena, such as the generation of jet noise that motivates the …
compressible turbulence phenomena, such as the generation of jet noise that motivates the …
[書籍][B] Adjoint Navier-Stokes methods for hydrodynamic shape optimisation
A Stück - 2012 - tore.tuhh.de
To efficiently calculate the sensitivity derivative of hydrodynamic objective functionals with
respect to the shape, the adjoint Navier-Stokes equations were derived analytically …
respect to the shape, the adjoint Navier-Stokes equations were derived analytically …
A discrete adjoint approach for the optimization of unsteady turbulent flows
R Roth, S Ulbrich - Flow, turbulence and combustion, 2013 - Springer
In this paper we present a discrete adjoint approach for the optimization of unsteady,
turbulent flows. While discrete adjoint methods usually rely on the use of the reverse mode …
turbulent flows. While discrete adjoint methods usually rely on the use of the reverse mode …
Topology optimization in fluid mechanics using continuous adjoint and the cut-cell method
PY Vrionis, KD Samouchos… - Computers & Mathematics …, 2021 - Elsevier
A topology optimization method for steady-state flows of incompressible fluids which is
capable of imposing accurate boundary conditions along the solid walls of the sought fluid …
capable of imposing accurate boundary conditions along the solid walls of the sought fluid …