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20192021
most citedConstruction of Reduced Order Models for Fluid Flows Using Deep Feedforward Neural Networks

165 citations · 169 across the 4 of their papers we have counts for

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physics.flu-dyn20211 cited

On the application of incomplete FWH surfaces for aeroacoustic predictions

Tulio Ricciardi, William Wolf, Philippe Spalart

This work is motivated by CFD simulations from a realistic landing gear performed modeling only the half bottom of the aircraft fuselage [15]. Hence, in this previous analysis, the…

physics.flu-dyn2021

Extremum seeking control applied to airfoil trailing-edge noise suppression

Tarcísio Costa Déda Oliveira, William Roberto Wolf

Extremum seeking control (ESC) and its slope seeking generalization are applied in a high-fidelity flow simulation framework for reduction of acoustic noise generated by a NACA0012…

physics.flu-dyn2021

Data-Driven Closure of Projection-Based Reduced Order Models for Unsteady Compressible Flows

Victor Zucatti, William Wolf

A data-driven closure modeling based on proper orthogonal decomposition (POD) temporal modes is used to obtain stable and accurate reduced order models (ROMs) of unsteady compressi…

physics.flu-dyn2019

On Secondary Tones Arising in Trailing-Edge Noise at Moderate Reynolds Numbers

Tulio R. Ricciardi, Walter Arias-Ramirez, William R. Wolf

Direct numerical simulations are carried out to investigate the flow features responsible for secondary tones arising in trailing-edge noise at moderate Reynolds numbers. Simulatio…

physics.flu-dyn20193 cited

Active Flow Control for Drag Reduction of a Plunging Airfoil under Deep Dynamic Stall

Brener D'Lélis Oliveira Ramos, William Roberto Wolf, Chi-An Yeh +1

High-fidelity simulations are performed to study active flow control techniques for alleviating deep dynamic stall of a SD7003 airfoil in plunging motion. The flow Reynolds number…

physics.flu-dyn2019165 cited

Construction of Reduced Order Models for Fluid Flows Using Deep Feedforward Neural Networks

Hugo F. S. Lui, William R. Wolf

We present a numerical methodology for construction of reduced order models, ROMs, of fluid flows through the combination of flow modal decomposition and regression analysis. Spect…