Daigen Fukayama

668 citations
11 papers · 518 indexed · h-index 6
Topics
Fluid Dynamics and Turbulent Flows (6 papers)Wind and Air Flow Studies (4 papers)Neural dynamics and brain function (3 papers)
Partner nations
JapanIsraelUnited States

In The Last Decade

Daigen Fukayama

11 papers receiving 501 citations

Peers

Daigen Fukayama
Comparison fields: 5 of 54
  • Computational Mechanics 396
  • Environmental Engineering 171
  • Global and Planetary Change 122
  • Atmospheric Science 98
  • Ocean Engineering 97
Replace Gerardo Ruíz Chavarria with:
Gerardo Ruíz Chavarria Mexico
Janet D. Scheel United States
Jean-Philippe Laval France
Jin-Qiang Zhong China
Cristian C. Lalescu United States
Alexander Praskovsky United States
Fujihiro Hamba Japan
Anurag Juneja United States
Brindesh Dhruva United States
Richard Kerswell United States
Daigen Fukayama relative to Gerardo Ruíz Chavarria Mexico Gerardo Ruíz Chavarria's profile →
Citations per field
00.5×3.3×
Gerardo Ruíz Chavarria · 1×
Citations per year

Countries citing papers authored by Daigen Fukayama

Since Specialization
Citations

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

Fields of papers citing papers by Daigen Fukayama

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daigen Fukayama

This figure shows the co-authorship network connecting the top 25 collaborators of Daigen Fukayama. A scholar is included among the top collaborators of Daigen Fukayama 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 Daigen Fukayama. Daigen Fukayama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
#WorkIndexed citations
1 3
2
Development of Automatic Scaling Software of Ionospheric Parameters
4
3 4
4 328
5 1
6 4
7 119
8 9
9 5
10 33
11 8

About Daigen Fukayama

Daigen Fukayama is a scholar working on Computational Mechanics, Environmental Engineering and Statistical and Nonlinear Physics, having authored 11 papers that have together received 518 indexed citations. Recurring topics across this work include Fluid Dynamics and Turbulent Flows (6 papers), Wind and Air Flow Studies (4 papers) and Neural dynamics and brain function (3 papers). The work is most often cited by research in Computational Mechanics (396 citations), Environmental Engineering (171 citations) and Ocean Engineering (97 citations). Daigen Fukayama has collaborated with scholars based in Japan, Israel and United States. Frequent co-authors include Toshiyuki Gotoh, Tohru Nakano, A. Bershadskii, Kiyoshi Yamamoto, Eliyahu Dremencov, Gal Yadid, Takashi Maruyama, Naoto Kitamura, Klaus Hack and Hiromichi Takebe. Their work appears in journals such as Physical Review Letters, Physics Letters A and Physics of Fluids.

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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