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Herman Van der Auweraer

Researcher at Siemens

Publications -  159
Citations -  2734

Herman Van der Auweraer is an academic researcher from Siemens. The author has contributed to research in topics: Modal analysis & Modal. The author has an hindex of 20, co-authored 156 publications receiving 2401 citations. Previous affiliations of Herman Van der Auweraer include UGS Corp. & Katholieke Universiteit Leuven.

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The PolyMAX Frequency-Domain Method: A New Standard for Modal Parameter Estimation?

TL;DR: In this paper, a non-iterative frequency-domain parameter estimation method is proposed based on a weighted least-squares approach and uses multiple-input-multiple-output frequency response functions as primary data.
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Multiphysics NVH Modeling: Simulation of a Switched Reluctance Motor for an Electric Vehicle

TL;DR: This paper presents a multiphysics modeling of a switched reluctance motor (SRM) to simulate the acoustic radiation of the electrical machine using a 2-D finite-element model of the motor to simulate its magnetic properties and aMultiphysics mechatronic model ofThe motor and controls to simulate operating conditions.
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Operational modal analysis for estimating the dynamic properties of a stadium structure during a football game

TL;DR: In this paper, the ambient vibrations at the roof of a football stadium were recorded during a football game and the data set was also split in shorter segments corresponding to certain events before, during and after the game to investigate the influence of varying operational conditions on the dynamic properties.
Posted Content

Digital Twins.

TL;DR: The concept of Digital Twins and the chances for novel industrial applications are reviewed, and Mathematics are a key enabler and the impact will be highlighted along four specific examples addressing Digital Product Twins democratizing Design, Digital Production Twins enabling robots to mill, digital Production Twins driving industrialization of additive manufacturing, and Digital Performance Twins boosting operations.
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Output-Only Subspace-Based Structural Identification: From Theory to Industrial Testing Practice

TL;DR: In this paper, the problem of structural model identification during normal operating conditions and thus with uncontrolled, unmeasured, and nonstationary excitation is addressed, and the use of output-only and covariance-driven subspace-based stochastic identification methods is advocated.