Changcong Zhou

1.0k total citations
70 papers, 785 citations indexed

About

Changcong Zhou is a scholar working on Statistics, Probability and Uncertainty, Civil and Structural Engineering and Mechanics of Materials. According to data from OpenAlex, Changcong Zhou has authored 70 papers receiving a total of 785 indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Statistics, Probability and Uncertainty, 37 papers in Civil and Structural Engineering and 26 papers in Mechanics of Materials. Recurrent topics in Changcong Zhou's work include Probabilistic and Robust Engineering Design (65 papers), Fatigue and fracture mechanics (24 papers) and Advanced Multi-Objective Optimization Algorithms (23 papers). Changcong Zhou is often cited by papers focused on Probabilistic and Robust Engineering Design (65 papers), Fatigue and fracture mechanics (24 papers) and Advanced Multi-Objective Optimization Algorithms (23 papers). Changcong Zhou collaborates with scholars based in China, Chile and Germany. Changcong Zhou's co-authors include Zhenzhou Lü, Haodong Zhao, Zhufeng Yue, Zhenzhou Lü, Pengfei Wei, Hangshan Gao, Zheng Zhang, Fuchao Liu, Xiukai Yuan and Luyi Li and has published in prestigious journals such as Computer Methods in Applied Mechanics and Engineering, AIAA Journal and International Journal for Numerical Methods in Engineering.

In The Last Decade

Changcong Zhou

66 papers receiving 767 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Changcong Zhou China 18 628 370 232 208 107 70 785
Z. Zhang China 15 838 1.3× 508 1.4× 174 0.8× 337 1.6× 67 0.6× 19 1.0k
Diego A. Álvarez Colombia 15 607 1.0× 474 1.3× 154 0.7× 185 0.9× 70 0.7× 29 873
Bingyu Ni China 18 783 1.2× 552 1.5× 162 0.7× 286 1.4× 118 1.1× 44 1.0k
Chengning Zhou China 9 384 0.6× 198 0.5× 110 0.5× 222 1.1× 101 0.9× 21 559
Shui Yu China 14 424 0.7× 180 0.5× 128 0.6× 169 0.8× 69 0.6× 23 536
Xiukai Yuan China 15 584 0.9× 301 0.8× 146 0.6× 190 0.9× 28 0.3× 32 703
Nicolas Relun France 5 569 0.9× 241 0.7× 139 0.6× 286 1.4× 48 0.4× 7 642
Junfu Zhang China 9 376 0.6× 194 0.5× 142 0.6× 145 0.7× 167 1.6× 32 582
Yicheng Zhou China 13 468 0.7× 255 0.7× 82 0.4× 266 1.3× 54 0.5× 31 657
Ruoxue Zhang United States 8 392 0.6× 285 0.8× 151 0.7× 85 0.4× 86 0.8× 12 707

Countries citing papers authored by Changcong Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Changcong Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Changcong Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Changcong Zhou. A scholar is included among the top collaborators of Changcong Zhou 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 Changcong Zhou. Changcong Zhou 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.
2.
Zhou, Changcong, et al.. (2025). A volume-ratio index for sensitivity analysis of time-dependent models with interval uncertainty inputs. Aerospace Science and Technology. 160. 110077–110077. 2 indexed citations
3.
Jiao, Yaqi, Changcong Zhou, J Gu, et al.. (2025). Synergistic degradation of phenanthrene by birnessite-Fe (VI) system: Mechanism, kinetics and environmental risk assessment. Colloids and Surfaces A Physicochemical and Engineering Aspects. 725. 137515–137515.
4.
Chang, Chao, et al.. (2025). Mesoscopically understanding stress distribution and sensitivity in layered-porous sintered silver for high-power electronics. Soldering and Surface Mount Technology. 37(4). 296–307. 2 indexed citations
5.
6.
Zhou, Changcong, et al.. (2025). Time-dependent reliability sensitivity analysis of mechanisms with interval uncertainties. Structural and Multidisciplinary Optimization. 68(7).
7.
Zhao, Haodong & Changcong Zhou. (2024). An imprecise multiscale uncertainty quantification framework for fiber reinforced composites. Probabilistic Engineering Mechanics. 78. 103686–103686. 1 indexed citations
8.
Liu, Jun‐Chao, Luyi Li, & Changcong Zhou. (2024). Efficient Methods for Reliability Sensitivity Analysis of Distribution Parameters and Their Application. AIAA Journal. 62(4). 1461–1476. 1 indexed citations
9.
Zhang, Feng, et al.. (2023). Reliability Optimization of the Honeycomb Sandwich Structure Based on A Neural Network Surrogate Model. Materials. 16(23). 7465–7465. 2 indexed citations
10.
Zhao, Haodong, Changcong Zhou, Hanlin Zhang, & Huan Liu. (2023). A mechanism motion error sensitivity analysis method based on principal component analysis and artificial neural network. Probabilistic Engineering Mechanics. 72. 103416–103416. 5 indexed citations
11.
Zhou, Changcong, et al.. (2023). Hybrid time‐dependent reliability analysis under a mixture of random and interval uncertainties. International Journal for Numerical Methods in Engineering. 124(11). 2529–2551. 4 indexed citations
12.
Zhou, Changcong, et al.. (2021). Reliability and sensitivity analysis of composite structures by an adaptive Kriging based approach. Composite Structures. 278. 114682–114682. 32 indexed citations
13.
Lü, Zhenzhou, et al.. (2021). Advanced single-loop Kriging surrogate model method by combining the adaptive reduction of candidate sample pool for safety lifetime analysis. Applied Mathematical Modelling. 100. 580–595. 10 indexed citations
14.
Liu, Fuchao, Pengfei Wei, Changcong Zhou, & Zhufeng Yue. (2020). Reliability and reliability sensitivity analysis of structure by combining adaptive linked importance sampling and Kriging reliability method. Chinese Journal of Aeronautics. 33(4). 1218–1227. 29 indexed citations
15.
Li, Lei, et al.. (2019). Sensitivity Analysis-Based Optimization: A Case Study with the MTBF of an Aeronautical Hydraulic Pipeline System. International Journal of Computational Methods. 17(5). 1940019–1940019. 3 indexed citations
16.
Gao, Hangshan, et al.. (2018). Extending the global reliability sensitivity analysis to the systems under double-stochastic uncertainty. Advances in Structural Engineering. 22(3). 626–640. 3 indexed citations
17.
Gao, Hangshan, et al.. (2018). Reliability sensitivity analysis method for time-dependent problem based on first-passage method. Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering. 233(4). 787–802. 6 indexed citations
18.
Zhou, Changcong, et al.. (2014). Moment independent sensitivity analysis with correlations. Applied Mathematical Modelling. 38(19-20). 4885–4896. 21 indexed citations
19.
Zhou, Changcong, Zhenzhou Lü, & Bo Ren. (2013). Point estimate-based importance analysis for structural models with correlated variables. International Journal of Systems Science. 46(2). 317–331. 4 indexed citations
20.
Li, Luyi, Zhenzhou Lü, & Changcong Zhou. (2011). Importance analysis for models with correlated input variables by the state dependent parameters method. Computers & Mathematics with Applications. 62(12). 4547–4556. 14 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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2026