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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:

Deeppipe: A two-stage physics-informed neural network for predicting mixed oil concentration distribution
Jian Du, Jianqin Zheng, Yongtu Liang, et al.
Energy (2023) Vol. 276, pp. 127452-127452
Closed Access | Times Cited: 18

Showing 18 citing articles:

Flow prediction of heterogeneous nanoporous media based on physical information neural network
Liang Zhou, Hai Sun, Dongyan Fan, et al.
Gas Science and Engineering (2024) Vol. 125, pp. 205307-205307
Closed Access | Times Cited: 7
An innovative end-to-end PINN-based solution for rapidly simulating homogeneous heat flow problems: An adaptive universal physics-guided auto-solver
Yijie Zhao, Donghe Li, Chunhui Wang, et al.
Case Studies in Thermal Engineering (2024) Vol. 56, pp. 104277-104277
Open Access | Times Cited: 4
A deep learning-based approach for predicting oil production: A case study in the United States
Jian Du, Jianqin Zheng, Yongtu Liang, et al.
Energy (2023) Vol. 288, pp. 129688-129688
Closed Access | Times Cited: 10
Law of conservation-guided neural network with gradient aggregation for improved energy efficiency optimization in industrial processes
Santi Bardeeniz, Chanin Panjapornpon, Moonyong Lee
Energy and AI (2025), pp. 100475-100475
Open Access
An intelligent tool wear monitoring model based on knowledge-data-driven physical-informed neural network for digital twin milling
Xuzhou Fang, Qinghua Song, Xiaojuan Wang, et al.
Mechanical Systems and Signal Processing (2025) Vol. 232, pp. 112736-112736
Closed Access
A novel surrogate model with deep learning for predicting spacial-temporal pressure in coalbed methane reservoirs
Yukun Dong, Xiaodong Zhang, Jiyuan Zhang, et al.
Natural Gas Industry B (2025)
Open Access
Deeppipe: An intelligent framework for predicting mixed oil concentration in multi-product pipeline
Jian Du, Jianqin Zheng, Yongtu Liang, et al.
Energy (2023) Vol. 282, pp. 128810-128810
Closed Access | Times Cited: 8
Soft Sensor Development for Real-Time Interface Tracking in Multiple Product Pipelines Based on Knowledge and Data
Ziyun Yuan, Lei Chen, Yuhan Zhang, et al.
SPE Journal (2024) Vol. 29, Iss. 04, pp. 1742-1757
Closed Access | Times Cited: 2
Machine learning application in batch scheduling for multi-product pipelines: A review
Renfu Tu, Hao Zhang, Bin Xu, et al.
Journal of Pipeline Science and Engineering (2024) Vol. 4, Iss. 3, pp. 100180-100180
Open Access | Times Cited: 2
Soft sensor development for mixed oil interface tracking in multi-product pipelines based on knowledge-informed semi-supervised Variational Bayesian Gaussian mixture regression
Ziyun Yuan, Lei Chen, Gang Liu, et al.
Energy (2024) Vol. 300, pp. 131516-131516
Closed Access | Times Cited: 2
Supercritical Carbon Dioxide Critical Flow Model based on a Physics-informed Neural Network
TianSheng Chen, HaoYang Feng, Yuan Yuan, et al.
Energy (2024), pp. 133863-133863
Closed Access | Times Cited: 1
A 1+ Mechanism Model for Predicting the Mixed-Oil Concentration in Multiproduct Pipelines
Ziyun Yuan, Lei Chen, Gang Liu, et al.
SPE Journal (2024) Vol. 29, Iss. 10, pp. 5487-5501
Closed Access | Times Cited: 1
Physics-guided multistage neural network: A physically guided network for step initial values and dispersive shock wave phenomena
Wen-Xuan Yuan, Rui Guo
Physical review. E (2024) Vol. 110, Iss. 6
Closed Access | Times Cited: 1
Knowledge-informed Variational Bayesian Gaussian mixture regression model for predicting mixed oil length
Ziyun Yuan, Lei Chen, Gang Liu, et al.
Energy (2023) Vol. 285, pp. 129248-129248
Closed Access | Times Cited: 3
Modeling unobserved geothermal structures using a physics-informed neural network with transfer learning of prior knowledge
Akihiro Shima, Kazuya Ishitsuka, Weiren Lin, et al.
Geothermal Energy (2024) Vol. 12, Iss. 1
Open Access
Online detection of mixed oil interface in multi-product pipeline using near-infrared spectroscopy
Qiu Shu-juan, Kaiyu Zhang, Liang Shen, et al.
Microchemical Journal (2024) Vol. 206, pp. 111480-111480
Closed Access
Accurate evaluation on peak shaving capacity of combined-heat-and-power thermal power units based on physical information neural network
Yunxiao Chen, Zizhen Qin, Chaojing Lin, et al.
Applied Thermal Engineering (2024), pp. 124690-124690
Closed Access
DeepPipe: A Multi-Stage Knowledge-Enhanced Physics-Informed Neural Network for Hydraulic Transient Simulation of Multi-Product Pipeline
Jian Du, Hao Li, K. Lu, et al.
Journal of Industrial Information Integration (2024) Vol. 42, pp. 100726-100726
Closed Access
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