Model Reduction and Surrogate Modeling (MORE)

19-23 Sep 2022 Berlin (Germany)

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Program

Week Mon. 19 Tue. 20 Wed. 21 Thu. 22 Fri. 23 List

‹ Wednesday, September 21, 2022 ›

08:00

09:00

10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

›8:30 (45min)

Plenary
Chair: Gianluigi Rozza

› H 1012

8:30 - 9:15 (45min)

Plenary

H 1012

Chair: Gianluigi Rozza

› Simulation-based Bayesian inference and surrogate modeling - Youssef Marzouk, Massachusetts Institute of Technology 08:30-09:15 (45min)

›9:20 (1h15)

Session 4
Chair: Gianluigi Rozza

› H 1012

9:20 - 10:35 (1h15)

Session 4

H 1012

Chair: Gianluigi Rozza

› Deep learning and the dynamical low-rank approximation - Aaron Charous, Massachusetts Institute Of Technology 09:20-09:45 (25min)

› Generalized Neural Closure Models with Interpretability - Abhinav Gupta, Department of Mechanical Engineering [Massachusetts Institute of Technology] 09:45-10:10 (25min)

› Conditional gradient-based Identification of Non-linear Dynamics - Martin Weiser, Zuse Institute Berlin 10:10-10:35 (25min)

›10:35 (25min)

Coffee break

› H 3005/3006

10:35 - 11:00 (25min)

Coffee break

H 3005/3006

›11:00 (1h40)

Parallel Session 5a
Chair: Anthony Nouy

› H 1012

11:00 - 12:40 (1h40)

Parallel Session 5a

H 1012

Chair: Anthony Nouy

› Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds - Silke Glas, University of Twente 11:00-11:25 (25min)

› Model reduction for port-Hamiltonian descriptor systems - Volker Mehrmann, Technische Universität Berlin 11:25-11:50 (25min)

› Dynamic Mode Decomposition for Continuous Port-Hamiltonian Systems - Jonas Nicodemus, Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart 11:50-12:15 (25min)

› A non-intrusive algorithm for parameterized model order reduction of LTI systems with guaranteed dissipativity - Tommaso Bradde, Politecnico di Torino, Department of Electronics and Telecommunications 12:15-12:40 (25min)

›11:00 (1h40)

Parallel Session 5b
Chair: Boris Kramer

› H 1058

11:00 - 12:40 (1h40)

Parallel Session 5b

H 1058

Chair: Boris Kramer

› Model reduction of descriptor systems with quadratic output functional - Jennifer Przybilla, Max Planck Institute for Dynamics of Complex Technical Systems 11:00-11:25 (25min)

› Learning Quadratic Embeddings for Nonlinear Dynamical Systems using Deep Learning - Pawan Goyal, Max Planck Institute for Dynamics of Complex Technical Systems 11:25-11:50 (25min)

› Impact of the Convergence of Series Expansions on Model Reduction of Quadratic-Bilinear Systems - Alejandro Diaz, Rice University 11:50-12:15 (25min)

› Data-Driven Model Reduction for Gas Network Digital Twins - Christian Himpe, University of Munster 12:15-12:40 (25min)

›12:40 (1h20)

Lunch

12:40 - 14:00 (1h20)

Lunch

›14:00 (45min)

Plenary
Chair: Tobias Breiten

› H 1012

14:00 - 14:45 (45min)

Plenary

H 1012

Chair: Tobias Breiten

› Structure-preserving and adaptive reduced order models of conservative dynamical systems - Cecilia Pagliantini, TU/e Eindhoven 14:00-14:45 (45min)

›15:00 (1h30)

Poster Blitz
Chair: Tobias Breiten

› H 1012

15:00 - 16:30 (1h30)

Poster Blitz

H 1012

Chair: Tobias Breiten

› Neural Closure Model for Dynamic Mode Decomposition Forecasts - Tony Ryu, Massachusetts Institute of Technology 15:02-15:04 (02min)

› A Differential Geometric Formulation for Model Order Reduction on Manifolds - Patrick Buchfink, University of Stuttgart 15:04-15:06 (02min)

› A machine learning-based reduced order model for the investigation of the haemodynamics in coronary artery bypass grafts - Pierfrancesco Siena, SISSA 15:06-15:08 (02min)

› Adaptive Gaussian Process Regression for Efficient Building of Surrogate Models in Inverse Problems - Phillip Semler, Zuse Institut Berlin 15:08-15:10 (02min)

› An efficient computational framework for atmospheric and ocean flows - Michele Girfoglio, Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies 15:10-15:12 (02min)

› Analysis of Hyper Reduction for the Computation of Nonlinear Normal Modes - Lukas Bürger, KULeuven 15:12-15:14 (02min)

› Balancing-related model reduction of large-scale sparse systems in MATLAB and Octave with the MORLAB toolbox - Steffen W. R. Werner, Courant Institute of Mathematical Sciences, New York University 15:14-15:16 (02min)

› Bayesian multi-ﬁdelity inverse analysis for computationally demanding models in high stochastic dimensions - Jonas Nitzler, Institute for Computational Mechanics, Professorship of Data-driven Materials Modeling, Technical University of Munich 15:16-15:18 (02min)

› Combining adaptive model order reduction and stochastic collocation for uncertainty quantification of vibroacoustic systems - Ulrich Römer, Institut für Dynamik und Schwingungen, Technische Universität Braunschweig 15:18-15:20 (02min)

› Data enhanced reduced order methods for turbulent flows - Anna Ivagnes, SISSA MathLab [Trieste] 15:20-15:22 (02min)

› Data-driven approaches for system identication and reduction - Dimitrios Karachalios, Max Planck Institute for Dynamics of Complex Technical Systems 15:22-15:24 (02min)

› Data-Driven Linearization of Nonlinear Finite Element Analyses - Giovanni Conni, Department of Mechanical Engineering [Leuven], Department of Computer Science [Leuven] 15:24-15:26 (02min)

› Dictionary-based Online-adaptive Structure-preserving Model Order Reduction for Parametric Hamiltonian Systems - Robin Herkert, University of Stuttgart 15:26-15:28 (02min)

› Dynamical low rank approximation and parametric reduced order models for shallow water moment equations - Julian Koellermeier, University of Groningen - Philipp Krah, Technical University of Berlin - Jonas Kusch, University of Innsbruck 15:28-15:30 (02min)

› Effective A-posteriori Error Estimation for Port-Hamiltonian Systems - Johannes Rettberg, University of Stuttgart, Institute of Engineering and Computational Mechanics 15:30-15:32 (02min)

› Efficient Hyper-Reduction of contact problems treated by Lagrange multipliers. - Simon LE BERRE, Laboratoire de simulation du combustible, CEA/DES/IRESNE/DEC/SESC 15:32-15:34 (02min)

› Hermite kernel surrogates for the value function of high-dimensional nonlinear optimal control problems - Tobias Ehring, University of Stuttgart 15:34-15:36 (02min)

› Hybrid Projection Methods with Recycling for Inverse Problems - Jiahua Jiang, University of Birmingham 15:36-15:38 (02min)

› Interpolatory (P)MOR via low-rank (tensor) approximation in general linear matrix equations - Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems 15:38-15:40 (02min)

› Low-rank methods in large scale constrained optimization - Martin Stoll, TU Chemnitz 15:40-15:42 (02min)

› Low-rank Parareal: a low-rank parallel-in-time integrator - Benjamin Carrel, Department of Mathematics, University of Geneva 15:42-15:44 (02min)

› M-M.E.S.S. 3.0 - Introducing Krylov-based solvers - Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems 15:44-15:46 (02min)

› Machine learning-based reduced order modelling: Towards intelligent digital twins - George Drakoulas, FEAC Engineering P.C., Department of Mechanical Engineering & Aeronautics, University of Patras 15:46-15:48 (02min)

› Mass-conserving and energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions - Henrik Rosenberger, Centrum Wiskunde & Informatica 15:48-15:50 (02min)

› Model order reduction for wave-type problems with band-limited outputs of interest - Muhammad Hamza Khalid, Department of Applied Mathematics, University of Twente 15:50-15:52 (02min)

› Model order reduction via substructuring for a nonlinear, switched, differential-algebraic machine tool model - Julia Vettermann, Technische Universität Chemnitz, Research Group Mathematics in Industry and Technology 15:52-15:54 (02min)

› Multi-fidelity Optimization of an Acoustic Metamaterial using Model Order Reduction and Machine Learning - Sebastian Schopper, Gerhard Müller 15:54-15:56 (02min)

› Non-intrusive adaptive surrogate modeling of parametric frequency-response problems - Davide Pradovera, Faculty of Mathematics, University of Vienna, CSQI, EPFL 15:56-15:58 (02min)

› On Balanced Truncation Error Bound and Sign Parameters - Sean Reiter, Department of Mathematics, Virginia Tech 15:58-16:00 (02min)

› On the use of exponential integrators for large-scale Hamiltonian systems - Michel-Niklas Senn, TU Braunschweig 16:00-16:02 (02min)

› Operator inference method for mechanical systems - Yevgeniya Filanova, Max-Planck-Institut für Dynamik Komplexer Technischer Systeme 16:02-16:04 (02min)

› Parametric model order reduction approach for quasi-static non-linear mechanical problems using an industrial code: application to an elasto-plastic material - Eki Agouzal, Inria Bordeaux - Sud-Ouest, Team Memphis, Institut de Mathématiques de Bordeaux, EDF R&D 16:04-16:06 (02min)

› pyMOR - Model Order Reduction with Python - Stephan Rave, University of Münster 16:06-16:08 (02min)

› Reduced Basis Methods for Time-Harmonic Maxwell's Equations - Anna Sanfilippo, University of Trento 16:08-16:10 (02min)

› Reduced order models for efficient uncertainty quantification of wooden structures with inhomogeneous material properties - Catharina Czech, Technical University of Munich 16:10-16:12 (02min)

› Reduction of single phase flow models in porous media using a quantity of interest - Jana Tarhini, IFP Energies Nouvelles 16:12-16:14 (02min)

› ROM for Large-scale Modelling of Urban Air Pollution - Moaad Khamlich, SISSA Scuola Internazionale Superiore di Studi Avanzati 16:14-16:16 (02min)

› Spectral approximation of Lyapunov operator equations with applications in high dimensional non-linear feedback control - Bernhard Höveler, Technische Universität Berlin 16:16-16:18 (02min)

› Subspace-Distance-Enabled Active Learning for Parametric Model Order Reduction of Dynamical Systems - Harshit Kapadia, Max Planck Institute for Dynamics of Complex Technical Systems 16:18-16:20 (02min)

› Symplectic formulation of PGD reduced-order models for structural dynamics applications - Clement Vella, LaMcube 16:20-16:22 (02min)

› Tensor Galerkin Proper Orthogonal Decomposition for Uncertainty Quantification of PDEs with Random Parameters - Jan Heiland, Max Planck Institute for Dynamics of Complex Technical Systems 16:22-16:24 (02min)

› Time extrapolation technique applied to POD-based ROM - Pablo Solán-Fustero, University of Zaragoza 16:24-16:26 (02min)

› Towards a Benchmark Framework for Model Order Reduction in the Mathematical Research Data Initiative (MaRDI) - Kathryn Lund, Max Planck Institute for Dynamics of Complex Technical Systems 16:26-16:28 (02min)

›16:30 (30min)

Coffee break

› H 3005/3006

16:30 - 17:00 (30min)

Coffee break

H 3005/3006

›17:00 (1h)

Poster Session

› H 3006

17:00 - 18:00 (1h)

Poster Session

H 3006

›19:30 (4h)

Conference Dinner

› Wartehalle

19:30 - 23:30 (4h)

Conference Dinner

Wartehalle

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