M. Padula

25 papers receiving 264 citations

Peers

M. Padula
Comparison fields: 5 of 25
  • Applied Mathematics 241
  • Mathematical Physics 104
  • Computational Theory and Mathematics 98
  • Computational Mechanics 119
  • Control and Systems Engineering 98
Replace Takeyuki Nagasawa with:
Takeyuki Nagasawa Japan
Matthias Kotschote Germany
Jörg Wolf South Korea
Mikhail V. Korobkov Russia
Bum Ja Jin South Korea
Francesca Crispo Italy
Ondřej Kreml Czechia
Xiaoding Shi China
Philip Isett United States
Naoto Tanaka Japan
M. Padula relative to Takeyuki Nagasawa Japan Takeyuki Nagasawa's profile →
Citations per field
00.5×4.5×
Takeyuki Nagasawa · 1×
Citations per year

Countries citing papers authored by M. Padula

Since Specialization
Citations

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

Fields of papers citing papers by M. Padula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside M. Padula, 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 M. Padula Line = papers co-authored together M. Padula links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199946
2 199536
3 199026
4 199322
5 201122
6 200817
7 201017
8 200017
9 200217
10 199613
11 200110
12 199710
13 19914
14 19894
15
EXISTENCE OF STEADY INCOMPRESSIBLE FLOWS PAST AN OBSTACLE(Mathematical Analysis of Phenomena in Fluid and Plasma Dynamics)
19913
16 19973
17 20033
18 19953
19 20043
20 19963

About M. Padula

M. Padula is a scholar working on Applied Mathematics, Control and Systems Engineering, Computational Mechanics, Computational Theory and Mathematics and Mathematical Physics, having authored 26 papers that have together received 293 indexed citations. Recurring topics across this work include Navier-Stokes equation solutions (16 papers), Stability and Controllability of Differential Equations (11 papers), Advanced Mathematical Modeling in Engineering (7 papers), Fluid Dynamics and Turbulent Flows (6 papers), Computational Fluid Dynamics and Aerodynamics (5 papers), Advanced Mathematical Physics Problems (4 papers), Advanced Numerical Methods in Computational Mathematics (2 papers) and Geomagnetism and Paleomagnetism Studies (2 papers). The work is most often cited by research in Applied Mathematics (241 citations), Mathematical Physics (104 citations), Computational Theory and Mathematics (98 citations), Computational Mechanics (119 citations) and Control and Systems Engineering (98 citations). M. Padula has collaborated with scholars based in Italy, France and Germany. Frequent co-authors include V. A. Solonnikov, Paolo Maremonti, Antonín Novotný, Giovanni P. Galdi, Κ. R. Rajagopal, П. И. Плотников, Milan Pokorný, Konstantin Pileckas, Markus Bause and Michael Růžička. Their work appears in journals such as Journal of Mathematical Fluid Mechanics, Differential and Integral Equations, Applied Physics Letters, Pacific Journal of Mathematics and Siberian Mathematical Journal.

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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