3 citations · 4 across the 3 of their papers we have counts for
7 papers
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…