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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:

Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics
Wenzhao Wu, Mitchell Daneker, Matthew A. Jolley, et al.
Applied Mathematics and Mechanics (2023) Vol. 44, Iss. 7, pp. 1039-1068
Open Access | Times Cited: 27

Showing 1-25 of 27 citing articles:

Physics-informed Neural Networks (PINN) for computational solid mechanics: Numerical frameworks and applications
Haoteng Hu, Lehua Qi, Xujiang Chao
Thin-Walled Structures (2024) Vol. 205, pp. 112495-112495
Closed Access | Times Cited: 35
A comprehensive review of advances in physics-informed neural networks and their applications in complex fluid dynamics
Chi Zhao, Feifei Zhang, Wenqiang Lou, et al.
Physics of Fluids (2024) Vol. 36, Iss. 10
Closed Access | Times Cited: 17
Reduced and All-at-Once Approaches for Model Calibration and Discovery in Computational Solid Mechanics
Ulrich Römer, Stefan Hartmann, Jendrik‐Alexander Tröger, et al.
Applied Mechanics Reviews (2024), pp. 1-51
Open Access | Times Cited: 9
Physics-constrained deep learning approach for solving inverse problems in composite laminated plates
Yang Li, Detao Wan, Zhe Wang, et al.
Composite Structures (2024) Vol. 348, pp. 118514-118514
Closed Access | Times Cited: 6
Data-driven nonparametric identification of material behavior based on physics-informed neural network with full-field data
I.K. Jeong, Maenghyo Cho, Hayoung Chung, et al.
Computer Methods in Applied Mechanics and Engineering (2023) Vol. 418, pp. 116569-116569
Closed Access | Times Cited: 15
Identifying Heterogeneous Micromechanical Properties of Biological Tissues via Physics‐Informed Neural Networks
Wensi Wu, Mitchell Daneker, Kevin T. Turner, et al.
Small Methods (2024)
Open Access | Times Cited: 5
A physics-informed neural network framework for multi-physics coupling microfluidic problems
Runze Sun, Hyogu Jeong, Jiachen Zhao, et al.
Computers & Fluids (2024) Vol. 284, pp. 106421-106421
Open Access | Times Cited: 5
Prediction of velocity and pressure of gas-liquid flow using spectrum-based physics-informed neural networks
Nanxi Ding, Hengzhen Feng, H. Lou, et al.
Applied Mathematics and Mechanics (2025) Vol. 46, Iss. 2, pp. 341-356
Closed Access
Scientific Machine Learning for Guided Wave and Surface Acoustic Wave (SAW) Propagation: PgNN, PeNN, PINN, and Neural Operator
Nafisa Mehtaj, Sourav Banerjee
Sensors (2025) Vol. 25, Iss. 5, pp. 1401-1401
Open Access
Progressive Domain Decomposition for Efficient Training of Physics-Informed Neural Network
Dawei Luo, Soo-Ho Jo, Taejin Kim
Mathematics (2025) Vol. 13, Iss. 9, pp. 1515-1515
Open Access
Physics-informed UNets for discovering hidden elasticity in heterogeneous materials
Ali Kamali, Kaveh Laksari
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials (2023) Vol. 150, pp. 106228-106228
Open Access | Times Cited: 10
Deep Learning for Solving and Estimating Dynamic Macro-finance Models
Benjamin Fan, Edward Qiao, Anran Jiao, et al.
Computational Economics (2024)
Closed Access | Times Cited: 3
PHYSICS-INFORMED POINTNET: ON HOW MANY IRREGULAR GEOMETRIES CAN IT SOLVE AN INVERSE PROBLEM SIMULTANEOUSLY? APPLICATION TO LINEAR ELASTICITY
Ali Kashefi, Leonidas Guibas, Tapan Mukerji
Journal of Machine Learning for Modeling and Computing (2023) Vol. 4, Iss. 4, pp. 1-25
Open Access | Times Cited: 8
Transfer Learning on Physics-Informed Neural Networks for Tracking the Hemodynamics in the Evolving False Lumen of Dissected Aorta
Mitchell Daneker, Shengze Cai, Ying Qian, et al.
Deleted Journal (2024) Vol. 1, Iss. 2, pp. 100016-100016
Open Access | Times Cited: 2
Seismic Wavefields Modeling With Variable Horizontally Layered Velocity Models via Velocity-Encoded PINN
Jiayang Zou, Cai Liu, Pengfei Zhao, et al.
IEEE Transactions on Geoscience and Remote Sensing (2024) Vol. 62, pp. 1-11
Closed Access | Times Cited: 2
A physics-informed neural networks framework for model parameter identification of beam-like structures
Rafael de Oliveira Teloli, R Tittarelli, Maël Bigot, et al.
Mechanical Systems and Signal Processing (2024) Vol. 224, pp. 112189-112189
Open Access | Times Cited: 2
Physics-informed neural networks for inverse problems in structural dynamics
Rafael de Oliveira Teloli, Maël Bigot, Lucas Coelho, et al.
(2024), pp. 19-19
Closed Access | Times Cited: 1
Physics-Informed Neural Networks for Modeling Dynamic Linear Elasticity
Venkatesh Gopinath, Vijay Kag
(2024)
Closed Access | Times Cited: 1
Estimating Soil Hydraulic Parameters for Unsaturated Flow Using Physics-Informed Neural Networks
S. Vemuri, Tim Büchner, Joachim Denzler
Lecture notes in computer science (2024), pp. 338-351
Closed Access | Times Cited: 1
A transfer learning enhanced physics-informed neural network for parameter identification in soft materials
Jing’ang Zhu, Yiheng Xue, Zishun Liu
Applied Mathematics and Mechanics (2024) Vol. 45, Iss. 10, pp. 1685-1704
Closed Access | Times Cited: 1
Computational Sensing, Understanding, and Reasoning: An Artificial Intelligence Approach to Physics-Informed World Modeling
Beatriz Moya, Alberto Badías, David González, et al.
Archives of Computational Methods in Engineering (2023) Vol. 31, Iss. 4, pp. 1897-1914
Closed Access | Times Cited: 3
A Physics-Informed Neural Networks Framework for Multi-Physics Coupling Microfluidic Problems
Runze Sun, Hyogu Jeong, Jiachen Zhao, et al.
(2024)
Closed Access
Transfer Learning Enhanced Physics-Informed Neural Networks for Parameter Identification in Soft Materials
Jing-Ang Zhu, Yiheng Xue, Zishun Liu
(2024)
Closed Access
A novel machine learning-based computational framework for predicting microscale morphological changes of plant cells during drying
Chanaka Prabuddha Batuwatta Gamage
(2024)
Open Access
Inversion of Spatially Distributed Elastic Moduli of 2.5d Woven Composites Based on Dic Strain Field Using Pinn Method
Hongyue Wang, Guodong Fang, Bo Gao, et al.
(2024)
Closed Access
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