A. John Arul

679 citations
57 papers · 466 · h-index 12

Impact in

Papers in

A. John Arul

54 papers receiving 452 citations

Peers

A. John Arul
Comparison fields: 5 of 54
  • Statistics, Probability and Uncertainty 156
  • Aerospace Engineering 260
  • Control and Systems Engineering 174
  • Safety, Risk, Reliability and Quality 47
  • Software 17
Replace Hadi Davilu with:
Hadi Davilu Iran
Peiwei Sun China
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L. Burgazzi Italy
Mohammad B. Ghofrani Iran
G.E. Wilson United States
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Chunkuan Shih Taiwan
Jinsen Xie China
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Citations per field
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Citations per year

Countries citing papers authored by A. John Arul

Since Specialization
Citations

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

Fields of papers citing papers by A. John Arul

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. John Arul. 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 A. John Arul. The network helps show where A. John Arul may publish in the future.

Co-authors

The 25 scholars most cited alongside A. John Arul, 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 A. John Arul Line = papers co-authored together A. John Arul links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202047
2 200839
3 202230
4 202125
5 200524
6 202220
7 200920
8 202019
9 202119
10 202218
11 200416
12 200916
13 201311
14 201910
15 201110
16 199410
17 20109
18 20238
19 20227
20 20117

About A. John Arul

A. John Arul is a scholar working on Aerospace Engineering, Statistics, Probability and Uncertainty, Control and Systems Engineering, Materials Chemistry and Safety, Risk, Reliability and Quality, having authored 57 papers that have together received 466 indexed citations. Recurring topics across this work include Nuclear reactor physics and engineering (28 papers), Nuclear Engineering Thermal-Hydraulics (20 papers), Risk and Safety Analysis (15 papers), Fault Detection and Control Systems (15 papers), Nuclear Materials and Properties (10 papers), Probabilistic and Robust Engineering Design (8 papers), Reliability and Maintenance Optimization (7 papers) and Advanced Control Systems Optimization (7 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (156 citations), Aerospace Engineering (260 citations), Control and Systems Engineering (174 citations), Safety, Risk, Reliability and Quality (47 citations) and Software (17 citations). A. John Arul has collaborated with scholars based in India and United Kingdom. Frequent co-authors include S. R. Shimjith, Jiamei Deng, Victor M. Becerra, Chandan Kumar, Nils Bausch, M. Ramakrishnan, Om Pal Singh, K. Velusamy, Akbar Sheikh-Akbari and P. Mohanakrishnan. Their work appears in journals such as Annals of Nuclear Energy, Nuclear Engineering and Design, Progress in Nuclear Energy, IEEE Access and Nuclear 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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