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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Probabilistic damage identification of a designed 9-story building using modal data in the presence of modeling errors
Iman Behmanesh, Babak Moaveni, Costas Papadimitriou
Engineering Structures (2016) Vol. 131, pp. 542-552
Open Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

Review on the new development of vibration-based damage identification for civil engineering structures: 2010–2019
Rongrong Hou, Yong Xia
Journal of Sound and Vibration (2020) Vol. 491, pp. 115741-115741
Open Access | Times Cited: 462
Recurrent neural network model with Bayesian training and mutual information for response prediction of large buildings
Carlos A. Perez-Ramirez, Juan P. Amézquita-Sánchez, Martin Valtierra‐Rodriguez, et al.
Engineering Structures (2018) Vol. 178, pp. 603-615
Closed Access | Times Cited: 212
A comprehensive review of digital twin—part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives
Adam Thelen, Xiaoge Zhang, Olga Fink, et al.
Structural and Multidisciplinary Optimization (2022) Vol. 66, Iss. 1
Closed Access | Times Cited: 76
Towards vibration-based damage detection of civil engineering structures: overview, challenges, and future prospects
Ali Zar, Zahoor Hussain, Muhammad Akbar, et al.
International Journal of Mechanics and Materials in Design (2024) Vol. 20, Iss. 3, pp. 591-662
Open Access | Times Cited: 14
State-of-the-art review on Bayesian inference in structural system identification and damage assessment
Yong Huang, Changsong Shao, Biao Wu, et al.
Advances in Structural Engineering (2018) Vol. 22, Iss. 6, pp. 1329-1351
Open Access | Times Cited: 149
Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes
Yang Yang, Yao Zhang, Xiaokun Tan
Symmetry (2021) Vol. 13, Iss. 11, pp. 1998-1998
Open Access | Times Cited: 100
The damage effect on the dynamic characteristics of FRP-strengthened reinforced concrete structures
Umberto De Maio, Daniele Gaetano, Fabrizio Greco, et al.
Composite Structures (2023) Vol. 309, pp. 116731-116731
Open Access | Times Cited: 38
Damage detection in structural systems utilizing artificial neural networks and proper orthogonal decomposition
Saeed Eftekhar Azam, Ahmed Rageh, Daniel G. Linzell
Structural Control and Health Monitoring (2018) Vol. 26, Iss. 2, pp. e2288-e2288
Open Access | Times Cited: 77
Structural health monitoring and fatigue damage estimation using vibration measurements and finite element model updating
Dimitrios Giagopoulos, Αλέξανδρος Αραϊλόπουλος, Vasilis Dertimanis, et al.
Structural Health Monitoring (2018) Vol. 18, Iss. 4, pp. 1189-1206
Closed Access | Times Cited: 71
Transfer-learning guided Bayesian model updating for damage identification considering modeling uncertainty
Zhiming Zhang, Chao Sun, Beibei Guo
Mechanical Systems and Signal Processing (2021) Vol. 166, pp. 108426-108426
Closed Access | Times Cited: 49
Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost
Azin Mehrjoo, Mingming Song, Babak Moaveni, et al.
Mechanical Systems and Signal Processing (2022) Vol. 169, pp. 108787-108787
Open Access | Times Cited: 31
A recursive nonlinear virtual sensing method for joint input-state-parameter estimation of partially measured structures
Zihao Liu, Mohsen Ebrahimzadeh Hassanabadi, Sima Abolghasemi, et al.
Engineering Structures (2025) Vol. 330, pp. 119828-119828
Open Access
Effects of model uncertainty in nonlinear structural finite element model updating by numerical simulation of building structures
Rodrigo Astroza, Andrés Alessandri
Structural Control and Health Monitoring (2018) Vol. 26, Iss. 3, pp. e2297-e2297
Open Access | Times Cited: 53
Steel railway bridge fatigue damage detection using numerical models and machine learning: Mitigating influence of modeling uncertainty
Ahmed Rageh, Saeed Eftekhar Azam, Daniel G. Linzell
International Journal of Fatigue (2019) Vol. 134, pp. 105458-105458
Closed Access | Times Cited: 44
Bayesian damage identification based on autoregressive model and MH-PSO hybrid MCMC sampling method
Jin Luo, Minshui Huang, Chunyan Xiang, et al.
Journal of Civil Structural Health Monitoring (2022) Vol. 12, Iss. 2, pp. 361-390
Closed Access | Times Cited: 23
Effects of variability in ambient vibration data on model updating and damage identification of a 10-story building
Amin Nozari, Iman Behmanesh, Seyedsina Yousefianmoghadam, et al.
Engineering Structures (2017) Vol. 151, pp. 540-553
Open Access | Times Cited: 46
Bayesian model updating of nonlinear systems using nonlinear normal modes
Mingming Song, Ludovic Renson, Jean‐Philippe Noël, et al.
Structural Control and Health Monitoring (2018) Vol. 25, Iss. 12
Open Access | Times Cited: 43
Bayesian structural identification of a long suspension bridge considering temperature and traffic load effects
André Jesus, P.E. Brommer, Robert Westgate, et al.
Structural Health Monitoring (2018) Vol. 18, Iss. 4, pp. 1310-1323
Open Access | Times Cited: 40
An innovative continuous Bayesian model updating method for base-isolated RC buildings using vibration monitoring data
Laura Ierimonti, Ilaria Venanzi, Nicola Cavalagli, et al.
Mechanical Systems and Signal Processing (2020) Vol. 139, pp. 106600-106600
Closed Access | Times Cited: 35
Accounting for Modeling Errors and Inherent Structural Variability through a Hierarchical Bayesian Model Updating Approach: An Overview
Mingming Song, Iman Behmanesh, Babak Moaveni, et al.
Sensors (2020) Vol. 20, Iss. 14, pp. 3874-3874
Open Access | Times Cited: 33
Data-driven probabilistic quantification and assessment of the prediction error model in damage detection applications
Nicholas Ε. Silionis, Konstantinos N. Anyfantis
Probabilistic Engineering Mechanics (2023) Vol. 71, pp. 103412-103412
Closed Access | Times Cited: 12
Recent advances in uncertainty quantification in structural response characterization and system identification
Kai Zhou, Zequn Wang, Qingbin Gao, et al.
Probabilistic Engineering Mechanics (2023) Vol. 74, pp. 103507-103507
Closed Access | Times Cited: 11
Two‐stage nonparametric framework for missing data imputation, uncertainty quantification, and incorporation in system identification
Wenjing Zhang, Ka‐Veng Yuen, Wang‐Ji Yan
Computer-Aided Civil and Infrastructure Engineering (2024) Vol. 39, Iss. 19, pp. 2881-2902
Open Access | Times Cited: 3
Fast Bayesian frequency domain modal identification from seismic response data
Yan‐Chun Ni, Feng‐Liang Zhang
Computers & Structures (2018) Vol. 212, pp. 225-235
Closed Access | Times Cited: 32
Model-based damage identification of railway bridges using genetic algorithms
Vinicius Alves, Matheus Miranda de Oliveira, Diogo Ribeiro, et al.
Engineering Failure Analysis (2020) Vol. 118, pp. 104845-104845
Closed Access | Times Cited: 29
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