RT journal article
T1 Cylinder drag minimization through wall actuation: A Bayesian Optimization approach
A1 Larroque, Anthony
A1 Fosas de Pando, Miguel Ángel
A1 Lafuente Molinero, Luis
A2 Ingeniería Mecánica y Diseño Industrial
A2 Matemáticas
K1 Bayesian optimization
K1 Drag reduction
K1 Cylinder
K1 Optimization methods
K1 Computational fluid dynamics
AB Bayesian Optimization (BO) has recently gained popularity as an efficient derivative-free method for the global optimization of expensive noisy black-box objective functions. These characteristics render BO a promising tool to tackle optimization problems involving numerical simulations of complex unsteady flows at moderate-tohigh Reynolds numbers. In this work, we assess the efficiency of Bayesian Optimization by considering two canonical flow problems: the drag reduction in the two-dimensional and three-dimensional flow around circular cylinders at, respectively, Re = 500 and Re = 3900, through tangential-velocity actuation at the cylinder wall. The root-mean-square of the drag coefficient with and without penalty terms is considered as the objective function. Several variants of Bayesian Optimization are assessed and compared against competing optimization algorithms such as Particle Swarm Optimization, CMA-ES, Nelder–Mead and the Explorative Gradient Method. Results show that in this case, the serial and the parallel BO techniques outperform other algorithms.
PB Elsevier
SN 0045-7930
YR 2022
FD 2022-03-21
LK http://hdl.handle.net/10498/31078
UL http://hdl.handle.net/10498/31078
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 09-may-2026