The conventional model updating based on sensitivity analysis generally employs l 1-norm
regularizer to characterize the sparsity of the structural damage. However, the l 1-norm …

The traditional finite element (FE) model updating method based on a static surrogate model
often suffers from high calculation costs and low updating accuracy. To address these …

Sparse Bayesian learning methods have been successfully applied to the community of
structural damage identification, which commonly assumes that the uncertainties from …

Optimal design of tuned mass damper (TMD) parameters should be implemented before
device installation to achieve the desired vibration reduction effects for tall and quite slender …

Vibration-based global damage detection based on updating of finite element (FE) model by
targeting the modal measurements is a significant area of interest in structural health …

Structural health monitoring (SHM) system provides valuable information for the fatigue
assessment of existing rail-cum-road bridges. This paper aims to develop an effective …

The sparse regularization (SReg) model has been prove to be an effective tool for the
structural damage identification. However, the SReg model overly penalizes the larger …

Civil engineering structures exhibit nonlinearities. Finite element model updating of these
structures is significant to obtain a more accurate numerical model for various applications …

Traditional updating methods based on numerical simulation are computationally expensive
and are not suitable for model updating with limited resources or time constraints. The …