TY - JOUR A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Morgenthal, Guido T1 - Parallelized adaptive Bayesian updating with structural reliability methods for inference of large engineering models N2 - 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. KW - Bayesian model updating KW - Bayesian updating with structural reliability methods KW - Structural health monitoring KW - Parallelization KW - Modal analysis KW - Railway bridge PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-633686 DO - https://doi.org/10.1177/13694332251346848 SN - 1369-4332 SN - 2048-4011 SP - 1 EP - 26 PB - Sage AN - OPUS4-63368 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Auersch, Lutz T1 - The role of vehicle dynamics in train-induced ground vibrations and the detection of irregular axle-pulse responses due to a varying track support stiffness N2 - Train-induced ground vibrations are all generated by the vehicle, by static or dynamic vehicle loads. The most important and most accepted excitation are the dynamic wheel loads from the passage over track irregularities. Dynamic wheel loads will be compared from parallel axle-box and ground vibration measurements at more than seven sites. Some low-frequency excitation of ground vibrations, typically between 10 and 30 Hz, cannot be found in the axle-box measurements. Therefore, other vehicle modes, such as rigid bogie modes, flexible carriage modes, rigid and flexible wheelset modes, have been analysed for additional excitation forces. These vehicle dynamics analyses give an explanation for higher axle-box results at high frequencies, but not for the excitation of the higher low-frequency ground-vibration component. Finally, the effect of the moving static train loads will be analysed. For a regular track and soil, the moving static train loads yield the quasi-static response which exists only in the low-frequency nearfield of the track. If the support stiffness is randomly varying along the track, the pulses on the track generate an additional low-frequency component which is called the irregular pulse responses. This component will be demonstrated by numerical analysis where all axle pulses are superposed in frequency domain. KW - Wheelset KW - Vehicle-track interaction KW - Rail roughness KW - Random dynamics and vibrations KW - Modal analysis PY - 2022 DO - https://doi.org/10.1177/09544097221086064 SN - 0954-4097 VL - 236 IS - 10 SP - 1218 EP - 1233 PB - Sage CY - London AN - OPUS4-55000 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -