Work

Adaptive Localized Reduced Basis Methods for Large Scale Parameterized Systems

Year: 2023

Type: preprint

Abstract: In this contribution, we introduce and numerically evaluate a certified and adaptive localized reduced basis method as a local model in a trust-region optimization method for parameter optimization constrained by partial differential equations.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2303.03074

Authors: Keil, Tim, Ohlberger, Mario, Schindler, Felix

Institution: University of Münster

Language: English

Topic: Model Reduction and Neural Networks

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders: Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung

Awards: G1652504919, EXC 2044: Mathematik Münster: Dynamik – Geometrie – Struktur, Verbundprojekt 05M2020 - ML-MORE: Maschinelles Lernen und Modelordnungs-Reduktion zur Vorhersage der Effizienz katalytischer Filter. Teilprojekt 1: Modellreduktion., G6938060324, G83450632

OpenAlex ID: W4323570397

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