Hui Cai

411 total citations
13 papers, 337 citations indexed

About

Hui Cai is a scholar working on Mechanical Engineering, Civil and Structural Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Hui Cai has authored 13 papers receiving a total of 337 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Mechanical Engineering, 3 papers in Civil and Structural Engineering and 3 papers in Statistical and Nonlinear Physics. Recurrent topics in Hui Cai's work include Advanced Measurement and Metrology Techniques (9 papers), Advanced machining processes and optimization (8 papers) and Structural Health Monitoring Techniques (3 papers). Hui Cai is often cited by papers focused on Advanced Measurement and Metrology Techniques (9 papers), Advanced machining processes and optimization (8 papers) and Structural Health Monitoring Techniques (3 papers). Hui Cai collaborates with scholars based in China. Hui Cai's co-authors include Xinyong Mao, Bo Luo, Bin Li, Fangyu Peng, Hongqi Liu, Bin Li, Feng Li, Bin Li, Kuanmin Mao and Dawei Pan and has published in prestigious journals such as Chemical Engineering Journal, International Journal of Machine Tools and Manufacture and The International Journal of Advanced Manufacturing Technology.

In The Last Decade

Hui Cai

13 papers receiving 328 citations

Peers

Hui Cai

ME

BE

EEE

CSE

IME

Ming‐Chyuan Lu Taiwan

Ichiro MORIWAKI Japan

Jianghai Shi China

Dun Lu China

Seung-Kook Ro South Korea

Jairam Manjunathaiah United States

J.A.J. Oosterling Netherlands

Zengxiong Peng China

Jinming Wu China

Franz Holzweißig Germany

Ming‐Chyuan Lu Taiwan

Hui Cai

315 ×1.1

ME

88 ×1.0

BE

183 ×2.8

EEE

34 ×0.5

CSE

114 ×2.1

IME

Citations per year, relative to Hui Cai Hui Cai (= 1×) peers Ming‐Chyuan Lu

Countries citing papers authored by Hui Cai

Since Specialization

Citations

This map shows the geographic impact of Hui Cai'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 Hui Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hui Cai more than expected).

Fields of papers citing papers by Hui Cai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hui Cai. 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 Hui Cai. The network helps show where Hui Cai may publish in the future.

Co-authorship network of co-authors of Hui Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Hui Cai. A scholar is included among the top collaborators of Hui Cai 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 Hui Cai. Hui Cai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

1.

Cai, Hui, et al.. (2024). Enhancing arsenate removal through interpretable machine learning guiding the modular design of metal–organic frameworks. Chemical Engineering Journal. 497. 155058–155058. 10 indexed citations

2.

Han, Xu, et al.. (2020). Modeling and Simulation of Dynamic Emotion Diffusion in Public Agendas. 58–63. 2 indexed citations

3.

Han, Xu, et al.. (2020). HKML: A Novel Opinion Dynamics Hegselmann-Krause Model with Media Literacy. 52–57. 8 indexed citations

4.

Han, Xu, et al.. (2020). AMHK: A Novel Opinion Dynamics Affection Mobilization-Based Hegselmann–Krause Model. 3421–3426. 5 indexed citations

5.

Mao, Xinyong, et al.. (2016). A complete methodology for identifying dynamics of heavy machine tool through operational modal analysis. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 230(8). 1406–1416. 5 indexed citations

6.

Luo, Bo, Dawei Pan, Hui Cai, et al.. (2015). A method to predict position-dependent structural natural frequencies of machine tool. International Journal of Machine Tools and Manufacture. 92. 72–84. 33 indexed citations

7.

Cai, Hui, Bo Luo, Xinyong Mao, et al.. (2015). A Method for Identification of Machine-tool Dynamics under Machining. Procedia CIRP. 31. 502–507. 22 indexed citations

8.

Luo, Bo, et al.. (2014). Modal Testing for Heavy Machine Tool Using Active Excitation. Applied Mechanics and Materials. 536-537. 1326–1332. 1 indexed citations

9.

Cai, Hui, Xinyong Mao, Bin Li, & Bo Luo. (2014). Estimation of FRFs of machine tools in output-only modal analysis. The International Journal of Advanced Manufacturing Technology. 77(1-4). 117–130. 20 indexed citations

10.

Mao, Xinyong, et al.. (2014). An approach for measuring the FRF of machine tool structure without knowing any input force. International Journal of Machine Tools and Manufacture. 86. 62–67. 25 indexed citations

11.

Li, Bin, Feng Li, Hongqi Liu, et al.. (2013). A measurement strategy and an error-compensation model for the on-machine laser measurement of large-scale free-form surfaces. Measurement Science and Technology. 25(1). 15204–15204. 46 indexed citations

12.

Li, Bin, Bo Luo, Xinyong Mao, et al.. (2013). A new approach to identifying the dynamic behavior of CNC machine tools with respect to different worktable feed speeds. International Journal of Machine Tools and Manufacture. 72. 73–84. 70 indexed citations

13.

Li, Bin, et al.. (2013). Estimation of CNC machine–tool dynamic parameters based on random cutting excitation through operational modal analysis. International Journal of Machine Tools and Manufacture. 71. 26–40. 90 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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