Zhong-Rong Lu

2.7k citations
134 papers · 2.1k indexed · h-index 25

Zhong-Rong Lu

122 papers receiving 2.0k citations

Peers

Zhong-Rong Lu
Comparison fields: 5 of 78
  • Civil and Structural Engineering 1.7k
  • Statistics, Probability and Uncertainty 357
  • Mechanics of Materials 670
  • Control and Systems Engineering 293
  • Modeling and Simulation 58
Replace Daniel Shevitz with:
Daniel Shevitz United States
Rubens Sampaio Brazil
Paulo B. Gonçalves Brazil
Sau‐Lon James Hu United States
Luis E. Suárez Puerto Rico
Elena Atroshchenko Australia
Huanlin Zhou China
Jonathan E. Cooper United Kingdom
Souvik Chakraborty India
Giuseppe Quaranta Italy
Zhong-Rong Lu relative to Daniel Shevitz United States Daniel Shevitz's profile →
Citations per field
00.5×5.3×
Daniel Shevitz · 1×
Citations per year

Countries citing papers authored by Zhong-Rong Lu

Since Specialization
Citations

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

Fields of papers citing papers by Zhong-Rong Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Zhong-Rong Lu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Zhong-Rong Lu Line = papers co-authored together Zhong-Rong Lu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
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13 20201
14 202018
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16 20176
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18 20174
19 201630
20
Structural damage identification based on Cuckoo search algorithm
20152

About Zhong-Rong Lu

Zhong-Rong Lu is a scholar working on Civil and Structural Engineering, Statistics, Probability and Uncertainty and Mechanics of Materials, having authored 134 papers that have together received 2.1k indexed citations. Recurring topics across this work include Structural Health Monitoring Techniques (101 papers), Ultrasonics and Acoustic Wave Propagation (33 papers), Probabilistic and Robust Engineering Design (33 papers), Optical measurement and interference techniques (14 papers), Structural Engineering and Vibration Analysis (13 papers), Non-Destructive Testing Techniques (12 papers), Vibration and Dynamic Analysis (12 papers) and Bladed Disk Vibration Dynamics (12 papers). The work is most often cited by research in Civil and Structural Engineering (1.7k citations), Statistics, Probability and Uncertainty (357 citations) and Mechanics of Materials (670 citations). Zhong-Rong Lu has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Stephen Law, Li Wang, Jike Liu, Zhenghao Ding, J.K. Liu, Liu Guang, Min Huang, Jun Li, Y.M. Chen and Hong Hao. Their work appears in journals such as Journal of Sound and Vibration, STRUCTURAL ENGINEERING AND MECHANICS, Mechanical Systems and Signal Processing, Nonlinear Dynamics and Inverse Problems in Science and Engineering.

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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