Long Peng

632 total citations
34 papers, 363 citations indexed

About

Long Peng is a scholar working on Ocean Engineering, Mechanical Engineering and Control and Systems Engineering. According to data from OpenAlex, Long Peng has authored 34 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Ocean Engineering, 9 papers in Mechanical Engineering and 7 papers in Control and Systems Engineering. Recurrent topics in Long Peng's work include Reservoir Engineering and Simulation Methods (13 papers), Oil and Gas Production Techniques (8 papers) and Drilling and Well Engineering (7 papers). Long Peng is often cited by papers focused on Reservoir Engineering and Simulation Methods (13 papers), Oil and Gas Production Techniques (8 papers) and Drilling and Well Engineering (7 papers). Long Peng collaborates with scholars based in China, United States and Switzerland. Long Peng's co-authors include John Z. H. Zhang, Xiao Liu, Guoqing Han, Yifan Zhou, Youzhi Zhang, Liying Zhu, He Ma, Xiaolong Chai, Leng Tian and Xiaodong Wu and has published in prestigious journals such as Journal of Applied Physics, Journal of Chemical Theory and Computation and Journal of Physics Condensed Matter.

In The Last Decade

Long Peng

31 papers receiving 350 citations

Peers

Long Peng
Atul Dubey United States
Zhu Li China
Kang‐Hyun Lee South Korea
Jing Gong China
Zhen Guan China
Long Peng
Citations per year, relative to Long Peng Long Peng (= 1×) peers Mingji Wei

Countries citing papers authored by Long Peng

Since Specialization
Citations

This map shows the geographic impact of Long Peng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Long Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Long Peng more than expected).

Fields of papers citing papers by Long Peng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Long Peng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Long Peng. The network helps show where Long Peng may publish in the future.

Co-authorship network of co-authors of Long Peng

This figure shows the co-authorship network connecting the top 25 collaborators of Long Peng. A scholar is included among the top collaborators of Long Peng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Long Peng. Long Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
4.
Peng, Long, Long Feng, Jianjun Zhu, et al.. (2025). Real-Time ESP Management Framework Using Hybrid Physics-Based and ML Models. 1 indexed citations
5.
Peng, Long, et al.. (2024). A fully coupled compositional wellbore/reservoir model for predicting liquid loading in vertical and inclined gas wells. Geoenergy Science and Engineering. 239. 212874–212874. 7 indexed citations
9.
Han, Guoqing, et al.. (2022). Study on Microscopic Distribution Characteristics of the Remaining Oil in Polymer-Flooded Reservoirs. ACS Omega. 7(31). 27196–27205. 5 indexed citations
10.
Peng, Long, et al.. (2022). Real-time anomaly detection methodology in the electric submersible pump systems. Petroleum Science and Technology. 40(21). 2669–2684. 7 indexed citations
12.
Chai, Xiaolong, Leng Tian, Kaiqiang Zhang, et al.. (2021). Integrated Hierarchy–Correlation Model for Evaluating Water-Driven Oil Reservoirs. ACS Omega. 6(50). 34460–34469. 4 indexed citations
13.
Peng, Long, et al.. (2021). Predictive Approach to Perform Fault Detection in Electrical Submersible Pump Systems. ACS Omega. 6(12). 8104–8111. 11 indexed citations
14.
Peng, Long, et al.. (2021). A Predictive Model to Detect the Impending Electric Submersible Pump Trips and Failures. SPE Annual Technical Conference and Exhibition. 6 indexed citations
15.
Zhang, Xujing, Aolin Zhang, Yi Jing, et al.. (2020). A heavy atom free semiconducting polymer with high singlet oxygen quantum yield for photodynamic and photothermal synergistic therapy. Materials & Design. 197. 109263–109263. 10 indexed citations
16.
Wu, Xiaodong, et al.. (2020). Liquid Film Model for Prediction and Identification of Liquid Loading in Vertical and Inclined Gas Wells. Journal of Petroleum Science and Engineering. 188. 106896–106896. 14 indexed citations
17.
Xu, Chengcheng, Junyi Ji, Pan Liu, & Long Peng. (2018). Forecasting the Travel Demand of the Station-Free Sharing Bike Using a Deep Learning Approach. Transportation Research Board 97th Annual MeetingTransportation Research Board. 2 indexed citations
18.
Peng, Long, Bin Jiao, Hai Liu, & Ting Zhang. (2015). The Fault Diagnosis of Wind Turbine Gearbox Based on Improved KNN. 3. 8–13. 1 indexed citations
19.
Huang, Junwei, et al.. (2012). Spin reorientation and spin-flop transition in multiferroic manganites Y1–xTbxMnO3 (x = 0, 0.1, 0.2) single crystals. Journal of Applied Physics. 111(8). 11 indexed citations
20.
Ling, Weiwei, Huaiwu Zhang, Yuanxun Li, et al.. (2009). Electromagnetic properties of ferroelectric/ferromagnetic composite materials base on low temperature cofired ceramic technology. Journal of Applied Physics. 105(7). 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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