63368 2025 eng 1 26 article Sage 1 -- -- -- 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 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. Advances in Structural Engineering 1369-4332 2048-4011 10.1177/13694332251346848 urn:nbn:de:kobv:b43-633686 publish 23.06.2025 Creative Commons - CC BY-NC - Namensnennung - Nicht kommerziell 4.0 International Patrick Simon Ronald Schneider Matthias Baeßler Guido Morgenthal eng uncontrolled Bayesian model updating eng uncontrolled Bayesian updating with structural reliability methods eng uncontrolled Structural health monitoring eng uncontrolled Parallelization eng uncontrolled Modal analysis eng uncontrolled Railway bridge Ingenieurbau 7 Bauwerkssicherheit 7.2 Ingenieurbau Infrastruktur Verlagsliteratur Datei für die Öffentlichkeit verfügbar ("Open Access") Wissenschaftliche Artikel der BAM Verkehrsinfrastrukturen Bundesanstalt für Materialforschung und -prüfung (BAM) https://opus4.kobv.de/opus4-bam/files/63368/Simon et al. - 2025 - Parallelized adaptive Bayesian updating with struc.pdf