12 citations · 12 across the 1 of their papers we have counts for
3 papers
stat.AP2025
Hierarchical Bayesian model updating using Dirichlet process mixtures for structural damage localization
Taro Yaoyama, Tatsuya Itoi, Jun Iyama
Bayesian model updating provides a rigorous probabilistic framework for calibrating finite element (FE) models with quantified uncertainties, thereby enhancing damage assessment, r…
stat.AP2024★ 12 cited
Probabilistic Model Updating of Steel Frame Structures Using Strain and Acceleration Measurements: A Multitask Learning Framework
Taro Yaoyama, Tatsuya Itoi, Jun Iyama
This paper proposes a multitask learning framework for probabilistic model updating by jointly using strain and acceleration measurements. This framework can enhance the structural…
stat.AP2024
Stress Resultant-Based Approach to Mass Assumption-Free Bayesian Model Updating of Frame Structures
Taro Yaoyama, Tatsuya Itoi, Jun Iyama
Bayesian model updating facilitates the calibration of analytical models based on observations and the quantification of uncertainties in model parameters such as stiffness and mas…