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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:

Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics
Salah A. Faroughi, Nikhil M. Pawar, Célio Fernandes, et al.
Journal of Computing and Information Science in Engineering (2024) Vol. 24, Iss. 4
Closed Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

Design of functional and sustainable polymers assisted by artificial intelligence
Tran Doan Huan, Rishi Gurnani, Chiho Kim, et al.
Nature Reviews Materials (2024) Vol. 9, Iss. 12, pp. 866-886
Closed Access | Times Cited: 20
Learning solutions of thermodynamics-based nonlinear constitutive material models using physics-informed neural networks
Shahed Rezaei, Ahmad Moeineddin, Ali M. Harandi
Computational Mechanics (2024) Vol. 74, Iss. 2, pp. 333-366
Closed Access | Times Cited: 15
Explainable chemical artificial intelligence from accurate machine learning of real-space chemical descriptors
Miguel Gallegos, Valentín Vassilev-Galindo, Igor Poltavsky, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 12
Evaluating fatigue onset in metallic materials: Problem, current focus and future perspectives
Enrico Salvati
International Journal of Fatigue (2024) Vol. 188, pp. 108487-108487
Open Access | Times Cited: 11
Phase-field modeling of fracture with physics-informed deep learning
M. Manav, Roberto Molinaro, Siddhartha Mishra, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 429, pp. 117104-117104
Open Access | Times Cited: 8
Deep learning-based prediction of wind-induced lateral displacement response of suspension bridge decks for structural health monitoring
Zhi-wei Wang, Xiao-fan Lu, Wenming Zhang, et al.
Journal of Wind Engineering and Industrial Aerodynamics (2024) Vol. 247, pp. 105679-105679
Closed Access | Times Cited: 6
Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping
Hang Jung Ling, Salomé Bru, Julia Puig, et al.
IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control (2024), pp. 1-1
Open Access | Times Cited: 6
Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning
Seyed Kourosh Mahjour, Jobayed Hossain Badhan, Salah A. Faroughi
Energies (2024) Vol. 17, Iss. 5, pp. 1180-1180
Open Access | Times Cited: 5
Constrained or unconstrained? Neural-network-based equation discovery from data
Grant Norman, Jacqueline Wentz, Hemanth Kolla, et al.
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 436, pp. 117684-117684
Open Access
Geometry physics neural operator solver for solid mechanics
Chawit Kaewnuratchadasorn, Jiaji Wang, Chul‐Woo Kim, et al.
Computer-Aided Civil and Infrastructure Engineering (2025)
Open Access
An Importance Sampling Method for Generating Optimal Interpolation Points in Training Physics-Informed Neural Networks
Hui Li, Yichi Zhang, Zhaoxiong Wu, et al.
Mathematics (2025) Vol. 13, Iss. 1, pp. 150-150
Open Access
Data-driven machine learning approach based on physics-informed neural network for population balance model
Ishtiaq Ali
Advances in Continuous and Discrete Models (2025) Vol. 2025, Iss. 1
Open 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
Physics-inspired deep learning for bridge scour prediction: site-specific and transferable models
Negin Yousefpour, Bo Wang
Georisk Assessment and Management of Risk for Engineered Systems and Geohazards (2025), pp. 1-24
Open Access
A systematic and bibliometric review on physics-based neural networks applications as a solution for structural engineering partial differential equations
Ahed Habib, Ausamah AL Houri, M. Talha Junaid, et al.
Structures (2024) Vol. 69, pp. 107361-107361
Closed Access | Times Cited: 4
Variational Neural Network Embedded with Digital Twins for Probabilistic Structural Damage Quantification
Jiaqi Xu, Xuan Zhou, Marco Giglio, et al.
AIAA Journal (2024), pp. 1-13
Closed Access | Times Cited: 4
A size-dependent nonlinear isogeometric approach of bidirectional functionally graded porous plates
Nam V. Nguyen, Duc-Huynh Phan
Structures (2024) Vol. 68, pp. 107097-107097
Closed Access | Times Cited: 3
Geosystems risk and uncertainty: The application of ChatGPT with targeted prompting
Seyed Kourosh Mahjour, Ramin Soltanmohammadi, Ehsan Heidaryan, et al.
Geoenergy Science and Engineering (2024) Vol. 238, pp. 212889-212889
Open Access | Times Cited: 2
A trainable variational Chan-Vese network based on algorithm unfolding for image segmentation
Zhaolong Cui, Tony Yuxiang Pan, Guangyu Yang, et al.
Mathematical Foundations of Computing (2024)
Open Access | Times Cited: 2
Multi-Fidelity Learned Emulator for Waves and Porous Coastal Structures Interaction Modelling
Pin Zhang, Brian Sheil, Qian Cheng
Computers and Geotechnics (2024) Vol. 176, pp. 106718-106718
Closed Access | Times Cited: 2
Geo-guided deep learning for spatial downscaling of solute transport in heterogeneous porous media
Nikhil M. Pawar, Ramin Soltanmohammadi, Shirko Faroughi, et al.
Computers & Geosciences (2024) Vol. 188, pp. 105599-105599
Open Access | Times Cited: 1
Deep learning-aided active subspace exploration of free-stream effects for fan-shaped film cooling
Feixue Cai, Hua Zhou, Fan Chen, et al.
Physics of Fluids (2024) Vol. 36, Iss. 9
Closed Access | Times Cited: 1
Machine Learning to speed up Computational Fluid Dynamics engineering simulations for built environments: A review
Clément Caron, Philippe Lauret, Alain Bastide
Building and Environment (2024) Vol. 267, pp. 112229-112229
Open Access | Times Cited: 1
Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be?
Jorge F. Urbán, Petros Stefanou, J. A. Pons
Journal of Computational Physics (2024), pp. 113656-113656
Open Access | Times Cited: 1
Physics-guided neural network for predicting international roughness index on flexible pavements considering accuracy, uncertainty and stability
Kun Chen, Mehran Eskandari Torbaghan, Nick Thom, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 142, pp. 109922-109922
Open Access | Times Cited: 1
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