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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:

Deep learning in computational mechanics: a review
Leon Herrmann, Stefan Kollmannsberger
Computational Mechanics (2024) Vol. 74, Iss. 2, pp. 281-331
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

DeepOKAN: Deep operator network based on Kolmogorov Arnold networks for mechanics problems
Diab W. Abueidda, Panos Pantidis, Mostafa E. Mobasher
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 436, pp. 117699-117699
Open Access | Times Cited: 7
State-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering
Hongchen Liu, Huaizhi Su, Lizhi Sun, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 6
Data-driven methods for flow and transport in porous media: A review
Yang Guang, Ran Xu, Yusong Tian, et al.
International Journal of Heat and Mass Transfer (2024) Vol. 235, pp. 126149-126149
Open Access | Times Cited: 5
Accelerating composite sandwich plate analysis: A hybrid higher-order XFEM and ANN approach for natural frequency prediction
Siddharth Suman, Kishan Dwivedi, Ahmed Raza, et al.
Mechanics Based Design of Structures and Machines (2025), pp. 1-13
Closed Access
Implementation of isotropic hyperelastic material models: a »template« approach
Sascha Eisenträger, Lukas Mäurer, Daniel Juhre, et al.
Acta Mechanica (2025)
Open Access
An efficient Poisson solver and a data-driven surrogate model for magnetic stray field calculations
Rainer Niekamp, Johanna Niemann, Maximilian Reichel, et al.
Computational Mechanics (2025)
Open Access
StructureGraph: a universal performance evaluation method for engineering structures via heterogeneous graph neural network
Yongcheng Li, Changsheng Wang, Shuyu Lv, et al.
Structural and Multidisciplinary Optimization (2025) Vol. 68, Iss. 3
Closed Access
A Plastic Damage Model With Mixed Isotropic–Kinematic Hardening for Low‐Cycle Fatigue in 7020 Aluminum
Alireza Daneshyar, Dorina Siebert, Christina Radlbeck, et al.
Fatigue & Fracture of Engineering Materials & Structures (2025)
Open Access
Data publishing in mechanics and dynamics: challenges, guidelines, and examples from engineering design
Henrik Ebel, Jan van Delden, Timo Lüddecke, et al.
Data-Centric Engineering (2025) Vol. 6
Open Access
A universal surrogate modeling method based on heterogeneous graph neural network for nonlinear analysis
Yongcheng Li, Changsheng Wang, Wenbin Hou
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 437, pp. 117793-117793
Closed Access
Predictions of transient vector solution fields with sequential deep operator network
Junyan He, Shashank Kushwaha, Jaewan Park, et al.
Acta Mechanica (2024) Vol. 235, Iss. 8, pp. 5257-5272
Open Access | Times Cited: 2
Predicting and explaining nonlinear material response using deep physically guided neural networks with internal variables
Jacobo Ayensa-Jiménez, Javier Orera-Echeverría, M. Doblaré
Mathematics and Mechanics of Solids (2024)
Open Access | Times Cited: 2
On neural networks for generating better local optima in topology optimization
Leon Herrmann, Ole Sigmund, V. Li, et al.
Structural and Multidisciplinary Optimization (2024) Vol. 67, Iss. 11
Open Access | Times Cited: 2
Physics-informed neural networks for V-notch stress intensity factor calculation
Mengchen Yu, Xiangyun Long, Chao Jiang, et al.
Theoretical and Applied Fracture Mechanics (2024) Vol. 134, pp. 104717-104717
Closed Access | Times Cited: 1
I-FENN with Temporal Convolutional Networks: Expediting the load-history analysis of non-local gradient damage propagation
Panos Pantidis, Habiba Eldababy, Diab W. Abueidda, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 425, pp. 116940-116940
Open 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
A Finite Operator Learning Technique for Mapping the Elastic Properties of Microstructures to Their Mechanical Deformations
Shahed Rezaei, Reza Najian Asl, Shirko Faroughi, et al.
International Journal for Numerical Methods in Engineering (2024)
Open Access | Times Cited: 1
Leveraging physics-informed neural networks for wavefield analysis in laser ultrasonic testing
Yang Li, Bin Xu, Yun Zou, et al.
Nondestructive Testing And Evaluation (2024), pp. 1-23
Closed Access | Times Cited: 1
Transfer Learning Enhanced Physics-Informed Neural Networks for Parameter Identification in Soft Materials
Jing-Ang Zhu, Yiheng Xue, Zishun Liu
(2024)
Closed Access
Pcnn-Rs: Physics-Constrained Neural Networks as Multi-Material Riemann Solvers Without Labeled Data
Liang Xu, Ziyan Liu, Yiwei Feng, et al.
(2024)
Closed Access
Automated Detection of Malaria-Infected Cells Using Convolutional Neural Networks
Sahil Khan
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 7, pp. 1619-1624
Open Access
Data-driven computational mechanics: comparison of model-free and model-based methods in constitutive modeling
Julien Philipp Stöcker, Selina Heinzig, Abhinav Anil Khedkar, et al.
Archive of Applied Mechanics (2024) Vol. 94, Iss. 9, pp. 2683-2718
Open Access
Experimental Learning of a Hyperelastic Behavior with a Physics-Augmented Neural Network
Clément Jailin, Antoine Benady, R. Legroux, et al.
Experimental Mechanics (2024) Vol. 64, Iss. 9, pp. 1465-1481
Open Access
Optimization of Single-Layer Reticulate Shell Assembly Sequence Using Deep Reinforcement Learning Graph Embedding Method
Hongyu Wu, Yuching Wu, Peng Zhu, et al.
Buildings (2024) Vol. 14, Iss. 12, pp. 3825-3825
Open Access
Unsupervised neural-network solvers for multi-material Riemann problems
Liang Xu, Ziyan Liu, Yiwei Feng, et al.
Computer Physics Communications (2024) Vol. 308, pp. 109470-109470
Closed Access
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