91 citations · 118 across the 10 of their papers we have counts for
12 papers
From resolvent to Gramians: extracting forcing and response modes for control
Benjamin Herrmann, Peter J. Baddoo, Scott T. M. Dawson +3
During the last decade, forcing and response modes produced by resolvent analysis have demonstrated great potential to guide sensor and actuator placement and design in flow contro…
A robust dynamic mode decomposition methodology for an airfoil undergoing transonic shock buffet
Andre Weiner, Richard Semaan
Dynamic mode decomposition (DMD) is a data-driven technique widely used to analyze and model fluid problems including transonic buffet flows. Despite its strengths, DMD is known to…
Bayesian Dynamical System Identification With Unified Sparsity Priors And Model Uncertainty
Prem Ratan Mohan Ram, Ulrich Römer, Richard Semaan
This work is concerned with uncertainty quantification in reduced-order dynamical system identification. Reduced-order models for system dynamics are ubiquitous in design and contr…
Cluster-based network modeling -- automated robust modeling of complex dynamical systems
Daniel Fernex, Bernd R. Noack, Richard Semaan
We propose a universal method for data-driven modeling of complex nonlinear dynamics from time-resolved snapshot data without prior knowledge. Complex nonlinear dynamics govern man…
Data-driven resolvent analysis
Benjamin Herrmann, Peter J. Baddoo, Richard Semaan +2
Resolvent analysis identifies the most responsive forcings and most receptive states of a dynamical system, in an input--output sense, based on its governing equations. Interest in…
Modeling synchronization in forced turbulent oscillator flows
Benjamin Herrmann, Philipp Oswald, Richard Semaan +1
Periodically forced, oscillatory fluid flows have been the focus of intense research for decades due to their richness as a nonlinear dynamical system and their relevance to applic…
SCOUT: Signal Correction and Uncertainty Quantification Toolbox in MATLAB
Richard Semaan, Vikas Yadav
This manuscript describes the software package SCOUT, which analyzes, characterizes, and corrects one-dimensional signals. Specifically, it allows to check and correct for stationa…
Actuation response model from sparse data for wall turbulence drag reduction
Daniel Fernex, Richard Semaan, Marian Albers +3
We compute, model, and predict drag reduction of an actuated turbulent boundary layer at a momentum thickness based Reynolds number of Reθ = 1000. The actuation is performed using…
Drag Reduction and Energy Saving by Spanwise Traveling Transversal Surface Waves for Flat Plate Flow
Marian Albers, Pascal S. Meysonnat, Daniel Fernex +3
Wall-resolved large-eddy simulations are performed to study the impact of spanwise traveling transversal surface waves in zero-pressure gradient turbulent boundary layer flow. Eigh…
Metric for attractor overlap
Rishabh Ishar, Eurika Kaiser, Marek Morzynski +6
We present the first general metric for attractor overlap (MAO) facilitating an unsupervised comparison of flow data sets. The starting point is two or more attractors, i.e., ensem…
Shape optimization of active and passive drag-reducing devices on a D-shaped bluff body
Richard Semaan
Shape optimization of an active and a passive drag-reducing device on a two-dimensional D-shaped bluff body is performed. The two devices are: Coanda actuator, and randomly-shaped…
Optimal sensor placement using machine learning
Richard Semaan
A new method for optimal sensor placement based on variable importance of machine learned models is proposed. With its simplicity, adaptivity, and low computational cost, the metho…