Qingzhen Lu

498 total citations
48 papers, 343 citations indexed

About

Qingzhen Lu is a scholar working on Mechanics of Materials, Mechanical Engineering and Control and Systems Engineering. According to data from OpenAlex, Qingzhen Lu has authored 48 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Mechanics of Materials, 20 papers in Mechanical Engineering and 18 papers in Control and Systems Engineering. Recurrent topics in Qingzhen Lu's work include Mechanical stress and fatigue analysis (36 papers), Vibration and Dynamic Analysis (15 papers) and Engineering Structural Analysis Methods (9 papers). Qingzhen Lu is often cited by papers focused on Mechanical stress and fatigue analysis (36 papers), Vibration and Dynamic Analysis (15 papers) and Engineering Structural Analysis Methods (9 papers). Qingzhen Lu collaborates with scholars based in China, Norway and Singapore. Qingzhen Lu's co-authors include Jun Yan, Qianjin Yue, Zhixun Yang, Andrew Palmer, Qi Su, Jinlong Chen, Jinlong Chen, Svein Sævik, Haitao Hu and Rundong Li and has published in prestigious journals such as Polymers, The International Journal of Advanced Manufacturing Technology and Ocean Engineering.

In The Last Decade

Qingzhen Lu

43 papers receiving 332 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qingzhen Lu China 11 207 115 114 92 68 48 343
Zhixun Yang China 10 152 0.7× 93 0.8× 94 0.8× 79 0.9× 56 0.8× 50 294
Iwona Adamiec–Wójcik Poland 10 97 0.5× 223 1.9× 126 1.1× 88 1.0× 38 0.6× 48 374
Feihong Yun China 13 160 0.8× 47 0.4× 211 1.9× 37 0.4× 107 1.6× 59 388
Xiangyu Wang China 11 121 0.6× 46 0.4× 167 1.5× 24 0.3× 62 0.9× 37 307
Yinshui Liu China 9 146 0.7× 100 0.9× 286 2.5× 54 0.6× 98 1.4× 27 368
Jingwei Cao China 10 288 1.4× 31 0.3× 261 2.3× 91 1.0× 36 0.5× 39 368
Quan Duan China 12 363 1.8× 43 0.4× 275 2.4× 151 1.6× 58 0.9× 28 516
Jie Pan Australia 11 95 0.5× 74 0.6× 85 0.7× 266 2.9× 30 0.4× 44 431
Jijun Gu China 13 136 0.7× 281 2.4× 140 1.2× 111 1.2× 84 1.2× 36 502
Lotfollah Pahlavan Netherlands 12 197 1.0× 47 0.4× 131 1.1× 232 2.5× 90 1.3× 35 409

Countries citing papers authored by Qingzhen Lu

Since Specialization
Citations

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

Fields of papers citing papers by Qingzhen Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qingzhen Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Qingzhen Lu. A scholar is included among the top collaborators of Qingzhen Lu 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 Qingzhen Lu. Qingzhen Lu 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.
Lu, Qingzhen, et al.. (2025). Application of machine learning methods incorporating Archard model for wear prediction of submarine cables. Ocean Engineering. 337. 121901–121901.
3.
Lu, Qingzhen, et al.. (2025). A Finite Element Analysis of Lateral Buckling of Tensile Armor Layers of Flexible Pipes Considering Machining Geometry Defects. Journal of Marine Science and Engineering. 13(3). 580–580.
4.
Wu, Wenhua, et al.. (2025). Digital twin framework for safety operation and maintenance of marine dynamic flexible cables. Ocean & Coastal Management. 263. 107597–107597.
5.
Wang, Shichao, et al.. (2024). Nonlinear behavior analysis of smooth bore unbonded flexible pipes under radial compression. Marine Structures. 97. 103661–103661. 2 indexed citations
6.
Su, Qi, Jun Yan, Zhixun Yang, et al.. (2024). Short-term extreme response estimation methodology for marine umbilical cables with two configuration types. Ocean Engineering. 310. 118710–118710. 2 indexed citations
7.
Xu, Qi, et al.. (2024). Deep learning-driven optimization design for the configuration of lazy-wave umbilical cables. Applied Ocean Research. 150. 104097–104097. 5 indexed citations
8.
Lu, Qingzhen, et al.. (2024). Study on contact force between umbilical and overboarding chute in deepwater S-lay process. Ocean Engineering. 302. 117693–117693. 1 indexed citations
9.
Yang, Liang, et al.. (2024). Thermo-Mechanical Coupling Analysis of the Sealing Structure Stress of LNG Cryogenic Hose Fittings. Journal of Marine Science and Engineering. 12(4). 581–581. 1 indexed citations
10.
Long, Ming, et al.. (2024). Enhanced analytical modeling of lazy wave risers: Addressing boundary-layer effects for improved configuration and force predictions. Ocean Engineering. 313. 119632–119632. 1 indexed citations
11.
Lu, Qingzhen, et al.. (2024). Study on the Sealing Performance of Flexible Pipe End-Fittings Considering the Creep Behavior of PVDF Material at Different Temperatures. Journal of Marine Science and Engineering. 12(12). 2362–2362.
12.
Zhang, Tao, Qingzhen Lu, Jun Yan, et al.. (2023). Numerical Study on Flexible Pipe End Fitting Progressive Failure Behavior Based on Cohesive Zone Model. Journal of Marine Science and Engineering. 11(1). 116–116. 5 indexed citations
13.
Yan, Jun, et al.. (2023). Time series prediction based on LSTM neural network for top tension response of umbilical cables. Marine Structures. 91. 103448–103448. 19 indexed citations
14.
Li, Hongxia, et al.. (2023). Numerical Simulation of the Pouring Process in Deep-Water Flexible Pipe End Fittings. Polymers. 15(6). 1397–1397.
15.
Yan, Jun, et al.. (2022). Experimental Study on the Influence of Cross-Section Type of Marine Cable Conductors on the Bending Performance. China Ocean Engineering. 36(4). 629–637. 6 indexed citations
16.
Yan, Jun, et al.. (2022). Data-driven prediction of critical collapse pressure of flexible pipeline carcass layer. Ocean Engineering. 249. 110948–110948. 7 indexed citations
17.
Lu, Qingzhen, et al.. (2021). Experimental study on the interlayer friction and wear mechanism between armor wires of umbilicals. Marine Structures. 80. 103102–103102. 9 indexed citations
18.
Yang, Zhixun, et al.. (2021). Study on the optimization algorithm of the cross-sectional layout of an umbilical based on the layering strategy. Ocean Engineering. 232. 109120–109120. 9 indexed citations
19.
20.
Lu, Qingzhen, et al.. (2015). Buckling collapse study for the carcass layer of flexible pipes using a strain energy equivalence method. Ocean Engineering. 111. 209–217. 40 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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