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Parallelized adaptive Bayesian updating with structural reliability methods for inference of large engineering models
- The reassessment of engineering structures, such as bridges, now increasingly involve the integration of models with realworld data. This integration aims to achieve accurate ‘as-is’ analysis within a digital twin framework. Bayesian model updating combines prior knowledge and data with models to enhance the modelling accuracy while consistently handling uncertainties. When updating large engineering models, numerical methods for Bayesian analysis present significant computational challenges due to the need for a substantial number of likelihood evaluations. The novelty of this contribution is to parallelize adaptive Bayesian Updating with Structural reliability methods combined with subset simulation (aBUS) to improve its computational efficiency. To demonstrate the efficiency and practical applicability of the proposed approach, we present a case study on the Maintalbrücke Gemünden, a large railway bridge. We leverage modal property data to update a linear-elastic dynamic structuralThe reassessment of engineering structures, such as bridges, now increasingly involve the integration of models with realworld data. This integration aims to achieve accurate ‘as-is’ analysis within a digital twin framework. Bayesian model updating combines prior knowledge and data with models to enhance the modelling accuracy while consistently handling uncertainties. When updating large engineering models, numerical methods for Bayesian analysis present significant computational challenges due to the need for a substantial number of likelihood evaluations. The novelty of this contribution is to parallelize adaptive Bayesian Updating with Structural reliability methods combined with subset simulation (aBUS) to improve its computational efficiency. To demonstrate the efficiency and practical applicability of the proposed approach, we present a case study on the Maintalbrücke Gemünden, a large railway bridge. We leverage modal property data to update a linear-elastic dynamic structural model of the bridge. The parallelized aBUS approach significantly reduces computational time, making Bayesian updating of large engineering models feasible within reasonable timeframes. The improved efficiency allows for a wider implementation of Bayesian model updating in structural health monitoring and maintenance decision support systems.…


| Autor*innen: | Patrick SimonORCiD, Ronald SchneiderORCiD, Matthias BaeßlerORCiD, Guido Morgenthal |
|---|---|
| Dokumenttyp: | Zeitschriftenartikel |
| Veröffentlichungsform: | Verlagsliteratur |
| Sprache: | Englisch |
| Titel des übergeordneten Werkes (Englisch): | Advances in Structural Engineering |
| Jahr der Erstveröffentlichung: | 2025 |
| Organisationseinheit der BAM: | 7 Bauwerkssicherheit |
| 7 Bauwerkssicherheit / 7.2 Ingenieurbau | |
| Veröffentlichende Institution: | Bundesanstalt für Materialforschung und -prüfung (BAM) |
| Verlag: | Sage |
| Erste Seite: | 1 |
| Letzte Seite: | 26 |
| DDC-Klassifikation: | Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Ingenieurbau |
| Freie Schlagwörter: | Bayesian model updating; Bayesian updating with structural reliability methods; Modal analysis; Parallelization; Railway bridge; Structural health monitoring |
| Themenfelder/Aktivitätsfelder der BAM: | Infrastruktur |
| Infrastruktur / Verkehrsinfrastrukturen | |
| DOI: | 10.1177/13694332251346848 |
| URN: | urn:nbn:de:kobv:b43-633686 |
| ISSN: | 1369-4332 |
| ISSN: | 2048-4011 |
| Verfügbarkeit des Dokuments: | Datei für die Öffentlichkeit verfügbar ("Open Access") |
| Lizenz (Deutsch): | Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International |
| Datum der Freischaltung: | 13.06.2025 |
| Referierte Publikation: | Ja |
| Datum der Eintragung als referierte Publikation: | 23.06.2025 |
| Schriftenreihen ohne Nummerierung: | Wissenschaftliche Artikel der BAM |


