A theoretical analysis of mass scaling techniques

Mass scaling is widely used in finite element models of structural dynamics for increasing the critical time step of explicit time integration methods. While the field has been flourishing over the years, it still lacks a strong theoretical basis and mostly relies on numerical experiments as the only means of assessment. This contribution thoroughly reviews existing methods and connects them to established linear algebra results to derive rigorous eigenvalue bounds and condition number estimates. Our results cover some of the most successful mass scaling techniques, unraveling for the first time well-known numerical observations.

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Publication Details

Journal
Computational Mechanics
Published
2025-03-07
DOI
https://doi.org/10.1007/s00466-025-02611-7
Citations
5
Primary Topic
Numerical methods for differential equations
Type
article
Field-Weighted Citation Impact
13.14

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article

A theoretical analysis of mass scaling techniques

Espen Sande, Yannis Voet, Annalisa Buffa
5 citations
Computational Mechanics
Numerical methods for differential equations
13.14
article

A theoretical analysis of mass scaling techniques

Espen Sande, Yannis Voet, Annalisa Buffa
article en
5 citations

Abstract

Mass scaling is widely used in finite element models of structural dynamics for increasing the critical time step of explicit time integration methods. While the field has been flourishing over the years, it still lacks a strong theoretical basis and mostly relies on numerical experiments as the only means of assessment. This contribution thoroughly reviews existing methods and connects them to established linear algebra results to derive rigorous eigenvalue bounds and condition number estimates. Our results cover some of the most successful mass scaling techniques, unraveling for the first time well-known numerical observations.

Computational MechanicsVol. 76(2)
École Polytechnique Fédérale de Lausanne (CH)
École Polytechnique Fédérale de Lausanne, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 1%
Numerical methods for differential equations
13.14
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