D. Train

634 citations
25 papers · 493 · h-index 10

Impact in

Papers in

D. Train

23 papers receiving 453 citations

Peers

D. Train
Comparison fields: 5 of 77
  • Pharmaceutical Science 182
  • Fluid Flow and Transfer Processes 39
  • Analytical Chemistry 62
  • Mechanical Engineering 171
  • Computational Mechanics 87
Replace Kimio Kawakita with:
Kimio Kawakita Japan
N. Harnby United Kingdom
Pirjo Luukkonen Finland
Laila J. Jallo United States
Josefina Nordström Sweden
Abderrahim Michrafy France
Harona Diarra France
Ilgaz Akseli United States
Juan G. Osorio United States
Yoshifumi Osako Japan
D. Train relative to Kimio Kawakita Japan Kimio Kawakita's profile →
Citations per field
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Kimio Kawakita · 1×
Citations per year

Countries citing papers authored by D. Train

Since Specialization
Citations

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

Fields of papers citing papers by D. Train

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside D. Train, 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 D. Train Line = papers co-authored together D. Train links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1956134
2 1958131
3
Transmission forces through a powder mass during the process of pelleting
195775
4 198519
5 196019
6 196017
7 196513
8 196013
9 198312
10 196512
11 19749
12 19657
13 19777
14 19746
15 19884
16 19762
17 19732
18 19792
19 19752
20 20032

About D. Train

D. Train is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Mechanical Engineering, Control and Systems Engineering and Mechanics of Materials, having authored 25 papers that have together received 493 indexed citations. Recurring topics across this work include High voltage insulation and dielectric phenomena (12 papers), Power Transformer Diagnostics and Insulation (9 papers), Powder Metallurgy Techniques and Materials (8 papers), Thermal Analysis in Power Transmission (5 papers), Advanced materials and composites (3 papers), Injection Molding Process and Properties (2 papers), Electrostatic Discharge in Electronics (2 papers) and High-Voltage Power Transmission Systems (2 papers). The work is most often cited by research in Pharmaceutical Science (182 citations), Fluid Flow and Transfer Processes (39 citations), Analytical Chemistry (62 citations), Mechanical Engineering (171 citations) and Computational Mechanics (87 citations). D. Train has collaborated with scholars based in Canada, United Kingdom and Mexico. Frequent co-authors include John A. Hersey, Chris Lewis, Ryszard Malewski, E. So, N.G. Trinh and H. Anis. Their work appears in journals such as Journal of Pharmacy and Pharmacology, Powder Metallurgy, IEEE Transactions on Power Delivery, IEEE Power Engineering Review and IEEE Transactions on Power Apparatus and Systems.

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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