Kun Xu

15.4k total citations · 5 hit papers
509 papers, 11.3k citations indexed

About

Kun Xu is a scholar working on Computational Mechanics, Applied Mathematics and Electrical and Electronic Engineering. According to data from OpenAlex, Kun Xu has authored 509 papers receiving a total of 11.3k indexed citations (citations by other indexed papers that have themselves been cited), including 235 papers in Computational Mechanics, 216 papers in Applied Mathematics and 141 papers in Electrical and Electronic Engineering. Recurrent topics in Kun Xu's work include Gas Dynamics and Kinetic Theory (215 papers), Computational Fluid Dynamics and Aerodynamics (195 papers) and Fluid Dynamics and Turbulent Flows (91 papers). Kun Xu is often cited by papers focused on Gas Dynamics and Kinetic Theory (215 papers), Computational Fluid Dynamics and Aerodynamics (195 papers) and Fluid Dynamics and Turbulent Flows (91 papers). Kun Xu collaborates with scholars based in China, Hong Kong and United States. Kun Xu's co-authors include Zhaoli Guo, Juan-Chen Huang, Chang Liu, Yajun Zhu, K. H. Prendergast, Liang Pan, Chengwen Zhong, Ruijie Wang, Qibing Li and Pubing Yu and has published in prestigious journals such as Advanced Materials, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Kun Xu

474 papers receiving 10.9k citations

Hit Papers

A Gas-Kinetic BGK Scheme for the Navier–Stokes Equations ... 2001 2026 2009 2017 2001 2010 2013 2015 2016 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Kun Xu China 51 6.9k 5.5k 2.1k 1.8k 930 509 11.3k
C. Shu Singapore 70 13.4k 1.9× 1.1k 0.2× 5.7k 2.7× 3.2k 1.8× 417 0.4× 529 22.1k
D. D. Joseph United States 60 8.0k 1.2× 938 0.2× 1.2k 0.6× 524 0.3× 246 0.3× 222 13.9k
F. Durst Germany 69 12.1k 1.7× 424 0.1× 2.0k 1.0× 2.8k 1.6× 559 0.6× 501 17.5k
Vigor Yang United States 63 10.0k 1.5× 545 0.1× 810 0.4× 7.4k 4.2× 184 0.2× 402 15.6k
Suhas V. Patankar United States 46 10.5k 1.5× 887 0.2× 857 0.4× 2.7k 1.6× 118 0.1× 210 16.4k
Jun Zhang China 40 1.4k 0.2× 682 0.1× 601 0.3× 697 0.4× 142 0.2× 264 5.4k
J. U. Brackbill United States 39 8.5k 1.2× 423 0.1× 1.7k 0.8× 974 0.6× 562 0.6× 92 13.3k
Jason M. Reese United Kingdom 42 3.0k 0.4× 2.4k 0.4× 643 0.3× 952 0.5× 468 0.5× 169 5.2k
Yonghao Zhang China 45 3.3k 0.5× 1.4k 0.2× 1.5k 0.7× 617 0.4× 328 0.4× 245 6.1k
Xudong Liu China 24 3.1k 0.5× 972 0.2× 642 0.3× 458 0.3× 57 0.1× 113 5.3k

Countries citing papers authored by Kun Xu

Since Specialization
Citations

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

Fields of papers citing papers by Kun Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Kun Xu. A scholar is included among the top collaborators of Kun Xu 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 Kun Xu. Kun Xu 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
1.
Xu, Kun, et al.. (2024). Design and analysis of a novel deployable grasping manipulator for space object capture. Acta Astronautica. 224. 266–280. 1 indexed citations
2.
Ding, Xiaoxi, et al.. (2024). Knowledge-informed FIR-based cross-category filtering framework for interpretable machinery fault diagnosis under small samples. Reliability Engineering & System Safety. 254. 110610–110610. 7 indexed citations
3.
Wang, Shunjiang, et al.. (2024). A novel scenario generation and forecasting method for multiple future states at source side based on combinatorial models. Energy Conversion and Management. 310. 118464–118464. 2 indexed citations
4.
Xu, Kun, Xiaofu Sun, Shuaiqiang Jia, et al.. (2024). Electrochemical CO2 reduction to C2+ products with ampere-level current on carbon-modified copper catalysts. Acta Physico-Chimica Sinica. 41(3). 100024–100024. 3 indexed citations
5.
Wei, Yinghui, Ming Jin, Shuhong Huang, et al.. (2024). Enhanced C‐To‐T and A‐To‐G Base Editing in Mitochondrial DNA with Engineered DdCBE and TALED (Adv. Sci. 3/2024). Advanced Science. 11(3). 1 indexed citations
6.
Liang, Zhaofeng, et al.. (2023). Design and Analysis of a Burrowing Mechanism Inspired by Mole Incisors for Planetary Exploration. 1912–1917. 1 indexed citations
7.
Ji, Xing, et al.. (2023). Direct modeling for computational fluid dynamics and the construction of high-order compact scheme for compressible flow simulations. Journal of Computational Physics. 477. 111921–111921. 5 indexed citations
8.
Yang, Yaqing, Liang Pan, & Kun Xu. (2023). Three-dimensional third-order gas-kinetic scheme on hybrid unstructured meshes for Euler and Navier–Stokes equations. Computers & Fluids. 255. 105834–105834. 10 indexed citations
9.
Guo, Zhaoli, Jiequan Li, & Kun Xu. (2023). Unified preserving properties of kinetic schemes. Physical review. E. 107(2). 25301–25301. 25 indexed citations
10.
Li, Wenfei, et al.. (2021). Estimation of Vehicle Dynamic Parameters Based on the Two-Stage Estimation Method. Sensors. 21(11). 3711–3711. 9 indexed citations
11.
Pan, Liang, et al.. (2021). High-order gas-kinetic scheme with parallel computation for direct numerical simulation of turbulent flows. Journal of Computational Physics. 448. 110739–110739. 17 indexed citations
12.
Ji, Xing, et al.. (2021). A compact high-order gas-kinetic scheme on unstructured mesh for acoustic and shock wave computations. Journal of Computational Physics. 449. 110812–110812. 17 indexed citations
13.
Zhu, Yajun, Chengwen Zhong, & Kun Xu. (2021). Numerical Transport Process of Splitting Kinetic Schemes in the Navier–Stokes–Fourier Limit. International journal of computational fluid dynamics. 35(8). 653–665. 3 indexed citations
14.
Zhao, Yanhui, Amparo Lázaro, Huan Liang, et al.. (2021). Morphological trait‐matching in plant–Hymenoptera and plant–Diptera mutualisms across an elevational gradient. Journal of Animal Ecology. 91(1). 196–209. 12 indexed citations
15.
Li, Weiming, Chang Liu, Yajun Zhu, Jiwei Zhang, & Kun Xu. (2020). Unified gas-kinetic wave-particle methods III: Multiscale photon transport. Journal of Computational Physics. 408. 109280–109280. 33 indexed citations
16.
Zhu, Yajun, et al.. (2020). A three-dimensional unified gas-kinetic wave-particle solver for flow computation in all regimes. Physics of Fluids. 32(9). 41 indexed citations
17.
Zhu, Yajun, Chengwen Zhong, & Kun Xu. (2020). Ray effect in rarefied flow simulation. Journal of Computational Physics. 422. 109751–109751. 8 indexed citations
18.
Wang, Yichuan, et al.. (2019). Hypoxia-active nanoparticles used in tumor theranostic. SHILAP Revista de lepidopterología. 2 indexed citations
19.
Zhu, Yajun, Chengwen Zhong, & Kun Xu. (2016). Implicit unified gas-kinetic scheme for steady state solutions in all flow regimes. Journal of Computational Physics. 315. 16–38. 105 indexed citations
20.
Josyula, Eswar, William F. Bailey, & Kun Xu. (2004). Nonequilibrium Relaxation in High Speed Flows. 11 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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