activity
20192021
most citedEfficient Wildland Fire Simulation via Nonlinear Model Order Reduction

16 citations · 20 across the 3 of their papers we have counts for

collaborators

5 papers

math.OC20211 cited

Decomposition of flow data via gradient-based transport optimization

Felix Black, Philipp Schulze, Benjamin Unger

We study an optimization problem related to the approximation of given data by a linear combination of transformed modes. In the simplest case, the optimization problem reduces to…

math.NA202116 cited

Efficient Wildland Fire Simulation via Nonlinear Model Order Reduction

Felix Black, Philipp Schulze, Benjamin Unger

We propose a new hyper-reduction method for a recently introduced nonlinear model reduction framework based on dynamically transformed basis functions and especially well-suited fo…

math.OC2020

Error bounds for port-Hamiltonian model and controller reduction based on system balancing

Tobias Breiten, Riccardo Morandin, Philipp Schulze

We study linear quadratic Gaussian (LQG) control design for linear port-Hamiltonian systems. To this end, we exploit the freedom in choosing the weighting matrices and propose a sp…

math.NA2019

Projection-Based Model Reduction with Dynamically Transformed Modes

Felix Black, Philipp Schulze, Benjamin Unger

We propose a new model reduction framework for problems that exhibit transport phenomena. As in the moving finite element method (MFEM), our method employs time-dependent transform…

math.OC20193 cited

From Time-Domain Data to Low-Dimensional Structured Models

Elliot Fosong, Philipp Schulze, Benjamin Unger

We present a framework for constructing a structured realization of a linear time-invariant dynamical system solely from a discrete sampling of an input and output trajectory of th…