[HTML][HTML] Review of finite element model updating methods for structural applications

S Ereiz, I Duvnjak, JF Jiménez-Alonso - Structures, 2022 - Elsevier
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 …

Machine learning techniques for diagnosis of alzheimer disease, mild cognitive disorder, and other types of dementia

G Mirzaei, H Adeli - Biomedical Signal Processing and Control, 2022 - Elsevier
Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …

State of the art in structural health monitoring of offshore and marine structures

H Pezeshki, H Adeli, D Pavlou… - Proceedings of the …, 2023 - icevirtuallibrary.com
This paper deals with state of the art in structural health monitoring (SHM) methods in
offshore and marine structures. Most SHM methods have been developed for onshore …

A Bayesian deep learning approach for random vibration analysis of bridges subjected to vehicle dynamic interaction

H Li, T Wang, G Wu - Mechanical Systems and Signal Processing, 2022 - Elsevier
Vehicle actions represent the main operational loading for various types of bridges. It is
essential to conduct random vibration analysis due to the unavoidable uncertainties arising …

A finite element model updating method based on the trust region and adaptive surrogate model

Y Bai, Z Peng, Z Wang - Journal of Sound and Vibration, 2023 - Elsevier
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 …

Vision‐aided three‐dimensional damage quantification and finite element model geometric updating for reinforced concrete structures

Q Kong, J Gu, B Xiong, C Yuan - Computer‐Aided Civil and …, 2023 - Wiley Online Library
This article presents a vision‐aided framework to achieve three‐dimensional (3D) concrete
damage quantification and finite element (FE) model geometric updating for reinforced …

Elastic structural analysis based on graph neural network without labeled data

LH Song, C Wang, JS Fan… - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Artificial intelligence is gaining increasing popularity in structural analysis. However, at the
structural system level, the appropriateness of data representation, the paucity of data, and …

Improved Levenberg–Marquardt backpropagation neural network by particle swarm and whale optimization algorithms to predict the deflection of RC beams

J Zhao, H Nguyen, T Nguyen-Thoi, PG Asteris… - Engineering with …, 2022 - Springer
The aim of this study is to develop a novel computer-aided method for the prediction of the
deflection of reinforced concrete beams (DRCB) under concentrated loads. To this end, in …

Systemic reliability of bridge networks with mobile sensing‐based model updating for postevent transportation decisions

E Ozer, A Malekloo, W Ramadan… - Computer‐Aided Civil …, 2023 - Wiley Online Library
This paper proposes the upscaling of conventional individual bridge health monitoring
problems into urban regions and transportation networks via mobile and smart sensing …

Active learning structural model updating of a multisensory system based on Kriging method and Bayesian inference

Y Yuan, FTK Au, D Yang… - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Abstract Model updating techniques are often applied to calibrate the numerical models of
bridges using structural health monitoring data. The updated models can facilitate damage …