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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 for determining a near-optimal topological design without any iteration
Yonggyun Yu, Taeil Hur, Jaeho Jung, et al.
Structural and Multidisciplinary Optimization (2018) Vol. 59, Iss. 3, pp. 787-799
Open Access | Times Cited: 94

Showing 1-25 of 94 citing articles:

Artificial intelligence and machine learning in design of mechanical materials
Kai Guo, Zhenze Yang, Chi‐Hua Yu, et al.
Materials Horizons (2020) Vol. 8, Iss. 4, pp. 1153-1172
Open Access | Times Cited: 431
Deep learning for topology optimization of 2D metamaterials
Hunter T. Kollmann, Diab W. Abueidda, Seid Korić, et al.
Materials & Design (2020) Vol. 196, pp. 109098-109098
Open Access | Times Cited: 274
Machine Learning Meets Computation and Communication Control in Evolving Edge and Cloud: Challenges and Future Perspective
Tiago Koketsu Rodrigues, Katsuya Suto, Hiroki Nishiyama, et al.
IEEE Communications Surveys & Tutorials (2019) Vol. 22, Iss. 1, pp. 38-67
Closed Access | Times Cited: 229
Invited review: Machine learning for materials developments in metals additive manufacturing
Nathan S. Johnson, Praveen S. Vulimiri, Albert C. To, et al.
Additive manufacturing (2020) Vol. 36, pp. 101641-101641
Open Access | Times Cited: 177
Topology optimization of 2D structures with nonlinearities using deep learning
Diab W. Abueidda, Seid Korić, Nahil Sobh
Computers & Structures (2020) Vol. 237, pp. 106283-106283
Open Access | Times Cited: 168
TOuNN: Topology Optimization using Neural Networks
Aaditya Chandrasekhar, Krishnan Suresh
Structural and Multidisciplinary Optimization (2020) Vol. 63, Iss. 3, pp. 1135-1149
Closed Access | Times Cited: 158
Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy
Li Zheng, Siddhant Kumar, Dennis M. Kochmann
Computer Methods in Applied Mechanics and Engineering (2021) Vol. 383, pp. 113894-113894
Open Access | Times Cited: 139
TopologyGAN: Topology Optimization Using Generative Adversarial Networks Based on Physical Fields Over the Initial Domain
Zhenguo Nie, Tong Lin, Haoliang Jiang, et al.
Journal of Mechanical Design (2021) Vol. 143, Iss. 3
Open Access | Times Cited: 137
Inverse design of shell-based mechanical metamaterial with customized loading curves based on machine learning and genetic algorithm
Yongzhen Wang, Qinglei Zeng, Jizhen Wang, et al.
Computer Methods in Applied Mechanics and Engineering (2022) Vol. 401, pp. 115571-115571
Closed Access | Times Cited: 84
Generative Design by Reinforcement Learning: Enhancing the Diversity of Topology Optimization Designs
Seowoo Jang, Soyoung Yoo, Namwoo Kang
Computer-Aided Design (2022) Vol. 146, pp. 103225-103225
Open Access | Times Cited: 71
A novel interval dynamic topology optimization methodology of piezoelectric structures under reliable active control
Wang Zhao, Sheng Wang
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 421, pp. 116766-116766
Closed Access | Times Cited: 23
Hierarchical Deep Learning Neural Network (HiDeNN): An artificial intelligence (AI) framework for computational science and engineering
Sourav Saha, Zhengtao Gan, Lin Cheng, et al.
Computer Methods in Applied Mechanics and Engineering (2020) Vol. 373, pp. 113452-113452
Open Access | Times Cited: 133
Deep Generative Design: Integration of Topology Optimization and Generative Models
Sangeun Oh, Yongsu Jung, Seongsin Kim, et al.
Journal of Mechanical Design (2019) Vol. 141, Iss. 11
Open Access | Times Cited: 119
A deep learning–based method for the design of microstructural materials
Ren Kai Tan, Nevin L. Zhang, Wenjing Ye
Structural and Multidisciplinary Optimization (2019) Vol. 61, Iss. 4, pp. 1417-1438
Closed Access | Times Cited: 108
CNN-based image recognition for topology optimization
Seunghye Lee, Hyunjoo Kim, Qui X. Lieu, et al.
Knowledge-Based Systems (2020) Vol. 198, pp. 105887-105887
Closed Access | Times Cited: 97
Universal machine learning for topology optimization
Heng Chi, Yuyu Zhang, Tsz Ling Elaine Tang, et al.
Computer Methods in Applied Mechanics and Engineering (2020) Vol. 375, pp. 112739-112739
Closed Access | Times Cited: 96
TONR: An exploration for a novel way combining neural network with topology optimization
Zeyu Zhang, Yu Li, Weien Zhou, et al.
Computer Methods in Applied Mechanics and Engineering (2021) Vol. 386, pp. 114083-114083
Closed Access | Times Cited: 67
A machine learning-based surrogate model for optimization of truss structures with geometrically nonlinear behavior
Hau T., Joo‐Won Kang, Jaehong Lee
Finite Elements in Analysis and Design (2021) Vol. 196, pp. 103572-103572
Closed Access | Times Cited: 63
Two-stage convolutional encoder-decoder network to improve the performance and reliability of deep learning models for topology optimization
Gorkem Can Ates, Recep M. Gorguluarslan
Structural and Multidisciplinary Optimization (2021) Vol. 63, Iss. 4, pp. 1927-1950
Closed Access | Times Cited: 60
Extreme gradient boosting-inspired process optimization algorithm for manufacturing engineering applications
Seungro Lee, Joonhee Park, Naksoo Kim, et al.
Materials & Design (2023) Vol. 226, pp. 111625-111625
Open Access | Times Cited: 32
Diffusion Models Beat GANs on Topology Optimization
François Mazé, Faez Ahmed
Proceedings of the AAAI Conference on Artificial Intelligence (2023) Vol. 37, Iss. 8, pp. 9108-9116
Open Access | Times Cited: 28
Accelerating gradient-based topology optimization design with dual-model artificial neural networks
Chao Qian, Wenjing Ye
Structural and Multidisciplinary Optimization (2020) Vol. 63, Iss. 4, pp. 1687-1707
Closed Access | Times Cited: 60
A deep convolutional neural network for topology optimization with perceptible generalization ability
Dalei Wang, Xiang Cheng, Yue Pan, et al.
Engineering Optimization (2021) Vol. 54, Iss. 6, pp. 973-988
Closed Access | Times Cited: 53
Deep-learning-based isogeometric inverse design for tetra-chiral auxetics
Zhongyuan Liao, Yingjun Wang, Liang Gao, et al.
Composite Structures (2021) Vol. 280, pp. 114808-114808
Closed Access | Times Cited: 52
Intelligent layout design of curvilinearly stiffened panels via deep learning-based method
Peng Hao, Dachuan Liu, Kunpeng Zhang, et al.
Materials & Design (2020) Vol. 197, pp. 109180-109180
Open Access | Times Cited: 50
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