[HTML][HTML] Review of finite element model updating methods for structural applications
At the time of designing structures up to date, the density and magnitude of the load have
increased, and the requirements for regulation have also become more stringent. To ensure …
increased, and the requirements for regulation have also become more stringent. To ensure …
Big data in construction: current applications and future opportunities
Big data have become an integral part of various research fields due to the rapid
advancements in the digital technologies available for dealing with data. The construction …
advancements in the digital technologies available for dealing with data. The construction …
Vibration-based Bayesian model updating of an actual steel truss bridge subjected to incremental damage
As the finite element (FE) model has become increasingly important in engineering, the
model updating method has also received much attention as a means of improving the …
model updating method has also received much attention as a means of improving the …
A probabilistic bond strength model for corroded reinforced concrete based on weighted averaging of non-fine-tuned machine learning models
This paper develops an innovative probabilistic predictive model for bond strength of
corroded reinforced concrete based on the weighted averaging of non-fine-tuned machine …
corroded reinforced concrete based on the weighted averaging of non-fine-tuned machine …
Real-time Bayesian damage identification enabled by sparse PCE-Kriging meta-modelling for continuous SHM of large-scale civil engineering structures
E García-Macías, F Ubertini - Journal of Building Engineering, 2022 - Elsevier
This work presents a surrogate model-based Bayesian model updating (BMU) approach for
automated damage identification of large-scale structures, which outperforms methods …
automated damage identification of large-scale structures, which outperforms methods …
[HTML][HTML] A multi-fidelity surrogate model for structural health monitoring exploiting model order reduction and artificial neural networks
Stochastic approaches to structural health monitoring (SHM) are often inevitably limited by
computational constraints. For instance, for Markov chain Monte Carlo algorithms relying …
computational constraints. For instance, for Markov chain Monte Carlo algorithms relying …
Sparse Bayesian factor analysis for structural damage detection under unknown environmental conditions
Damage detection of civil engineering structures needs to consider the effect of normal
environmental variations on structural dynamic properties. This study develops a novel …
environmental variations on structural dynamic properties. This study develops a novel …
Accounting for amplitude of excitation in model updating through a hierarchical Bayesian approach: Application to a two-story reinforced concrete building
Calibrated linear equivalent models of civil structures are often used for response prediction
and performance assessment. However, these models are only valid for a narrow range of …
and performance assessment. However, these models are only valid for a narrow range of …
Vibration-based damage detection of structures employing Bayesian data fusion coupled with TLBO optimization algorithm
The present paper deals with structural health monitoring of trusses, space frame and plate
structure utilizing the Bayesian data fusion approach. The application of the proposed …
structure utilizing the Bayesian data fusion approach. The application of the proposed …
Sparse Bayesian learning for structural damage identification
Identification of structural parameters can be cast as the process of solving an inverse
problem, in which regularization may be required when the problem is ill-posed. Bayesian …
problem, in which regularization may be required when the problem is ill-posed. Bayesian …