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OpenAlex Citation Counts

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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:

Bridge damage identification under the moving vehicle loads based on the method of physics-guided deep neural networks
Xinfeng Yin, Zhou Huang, Yang Liu
Mechanical Systems and Signal Processing (2023) Vol. 190, pp. 110123-110123
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Digital twin-driven framework for fatigue life prediction of welded structures considering residual stress
Anyin Peng, Yafei Ma, Ke Huang, et al.
International Journal of Fatigue (2024) Vol. 181, pp. 108144-108144
Closed Access | Times Cited: 30
Automated ultrasonic-based diagnosis of concrete compressive damage amidst temperature variations utilizing deep learning
Lei Wang, Shanchang Yi, Yang Yu, et al.
Mechanical Systems and Signal Processing (2024) Vol. 221, pp. 111719-111719
Open Access | Times Cited: 29
Physics-informed machine learning: A comprehensive review on applications in anomaly detection and condition monitoring
Yuandi Wu, Brett Sicard, S. Andrew Gadsden
Expert Systems with Applications (2024) Vol. 255, pp. 124678-124678
Open Access | Times Cited: 15
BFRP bars reinforced geopolymer-based coral aggregate concrete beams with sustainable and high seawater erosion resistance: Flexural durability, economic, and ecological analysis
Bai Zhang, Hong Zhu, Zhiyuan Yang, et al.
Engineering Structures (2025) Vol. 330, pp. 119910-119910
Closed Access | Times Cited: 1
Bridge damage identification under varying environmental and operational conditions combining Deep Learning and numerical simulations
Ana Fernández-Navamuel, David Pardo, Filipe Magalhães, et al.
Mechanical Systems and Signal Processing (2023) Vol. 200, pp. 110471-110471
Open Access | Times Cited: 22
Partial‐Model‐Based Damage Identification of Long‐Span Steel Truss Bridge Based on Stiffness Separation Method
Feng Xiao, Yuxue Mao, Geng Tian, et al.
Structural Control and Health Monitoring (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 13
Recent progress and future outlook of digital twins in structural health monitoring of civil infrastructure
M. Sakr, Ayan Sadhu
Smart Materials and Structures (2024) Vol. 33, Iss. 3, pp. 033001-033001
Open Access | Times Cited: 10
Prediction of construction cable forces of CFST arch bridge based on DNN
Weiwei Xie, Xiaohang Zhou, Dayan Qin, et al.
Structures (2024) Vol. 61, pp. 106012-106012
Closed Access | Times Cited: 7
Finite element model-informed deep learning for equivalent force estimation and full-field response calculation
Yixian Li, Peng Ni, Limin Sun, et al.
Mechanical Systems and Signal Processing (2023) Vol. 206, pp. 110892-110892
Closed Access | Times Cited: 21
Physics-informed neural networks for acoustic boundary admittance estimation
Johannes D. Schmid, Philipp Bauerschmidt, Caglar Gurbuz, et al.
Mechanical Systems and Signal Processing (2024) Vol. 215, pp. 111405-111405
Open Access | Times Cited: 6
Physics-guided deep learning based on modal sensitivity for structural damage identification with unseen damage patterns
Yongzhi Lei, Jun Li, Hong Hao
Engineering Structures (2024) Vol. 316, pp. 118510-118510
Open Access | Times Cited: 5
Moving load induced dynamic response analysis of bridge based on physics-informed neural network
Yifan Li, Wen-Yu He, Wei‐Xin Ren, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103215-103215
Closed Access
Machine learning-empowered intelligent vehicle–bridge systems: Current status and future prospects
Jin Zhu, Cheng Wei, Tingpeng Zhang, et al.
Structures (2025) Vol. 74, pp. 108598-108598
Closed Access
State-of-art review on load identification and response reconstruction to realize digital twin of infrastructures
Yixian Li, Lanxin Luo, Xiaoyou Wang, et al.
Advances in Structural Engineering (2025)
Closed Access
Overloaded vehicle identification for long-span bridges based on physics-informed multi-task deep learning leveraging influence line
Jun Liu, Yuqin Li, Shoubin Dong, et al.
Engineering Structures (2025) Vol. 333, pp. 120163-120163
Closed Access
Frequency Identification of Equal-Span Continuous Girder Bridge Based on Moving Vehicle Responses
Kui Luo, Si-Qi Li, Xiuyan Wang, et al.
International Journal of Structural Stability and Dynamics (2024) Vol. 24, Iss. 22
Closed Access | Times Cited: 4
Damage identification of truss bridges based on feature transferable digital twins
Zhou Huang, Xinfeng Yin, Yang Liu, et al.
Measurement (2024) Vol. 233, pp. 114735-114735
Closed Access | Times Cited: 4
Intelligent identification of the evolution process of damage on RC bridge piers under vessel collision considering multi-hazards
W. Wang, Shuai Wang, Jiahui Fu
Ocean Engineering (2025) Vol. 322, pp. 120434-120434
Closed Access
A novel preconditioned modified conjugate gradient method for vehicle–bridge moving force identification
Linjun Wang, Hongchun Wu, Chengsheng Luo, et al.
Structures (2025) Vol. 73, pp. 108322-108322
Closed Access
Bridge damage identification using a small amount of damage labeling data
Hongshuo Sun, Li Song, Zhiwu Yu
Computer-Aided Civil and Infrastructure Engineering (2025)
Open Access
Physics-informed neural network for load sway prediction in travelling autonomous mobile cranes
Zhuomin Zhou, Brandon Johns, Yihai Fang, et al.
Advanced Engineering Informatics (2025) Vol. 65, pp. 103269-103269
Open Access
Cross-domain damage identification of bridge based on generative adversarial and deep adaptation networks
Xiaohang Zhou, Mufeng Li, Yuxin Liu, et al.
Structures (2024) Vol. 64, pp. 106540-106540
Closed Access | Times Cited: 2
Probabilistic prediction and early warning for bridge bearing displacement using sparse variational Gaussian process regression
Yafei Ma, Bachao Zhang, Ke Huang, et al.
Structural Safety (2024), pp. 102564-102564
Closed Access | Times Cited: 2
Bridge Displacement Prediction from Dynamic Responses of a Passing Vehicle Using CNN‐GRU Networks
Xiaotong Sun, Zuo‐Cai Wang, Fei Zhang, et al.
Structural Control and Health Monitoring (2024) Vol. 2024, Iss. 1
Open Access | Times Cited: 1
Discussing the spectrum of physics-enhanced machine learning: a survey on structural mechanics applications
Marcus Haywood-Alexander, Wei Liu, Kiran Bacsa, et al.
Data-Centric Engineering (2024) Vol. 5
Open Access | Times Cited: 1
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