most citedImplementation of a discrete Immersed Boundary Method in OpenFOAM

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn2023

Synchronization and optimization of Large Eddy Simulation using an online Ensemble Kalman Filter

Lucas Villanueva, Karine Truffin, Marcello Meldi

An online Data Assimilation strategy based on the Ensemble Kalman Filter (EnKF) is used to improve the predictive capabilities of Large Eddy Simulation (LES) for the analysis of th…

physics.flu-dyn20231 cited

A physics-infused Immersed Boundary Method using online sequential Data Assimilation

Miguel M. Valero, Marcello Meldi

A physics-infused strategy relying on the Ensemble Kalman Filter (EnKF) is here used to augment the accuracy of a continuous Immersed Boundary Method (IBM). The latter is a classic…

physics.flu-dyn2023

Augmented state estimation of urban settings using intrusive sequential Data Assimilation

Lucas Villanueva, Miguel Martinez Valero, Anina Sarkic Glumac +1

A data-driven investigation of the flow around a high-rise building is performed combining heterogeneous experimental samples and RANS CFD. The coupling is performed using techniqu…

physics.flu-dyn2023

A Discrete Immersed Boundary Method for the numerical simulation of heat transfer in compressible flows

Hamza Riahi, Eric Goncalves, Marcello Meldi

In the present study, a discrete forcing Immersed Boundary Method (IBM) is proposed for the numerical simulation of high-speed flow problems including heat exchange. The flow field…

physics.flu-dyn20162 cited

Implementation of a discrete Immersed Boundary Method in OpenFOAM

E. Constant, C. Li, J. Favier +3

In this paper, the Immersed Boundary Method (IBM) proposed by Pinelli is implemented for finite volume approximations of incompressible Navier-Stokes equations solutions in the ope…