M.D. Mikhailov

79 papers receiving 1.1k citations

Peers

M.D. Mikhailov
Comparison fields: 5 of 81
  • Numerical Analysis 107
  • Computational Mechanics 401
  • Modeling and Simulation 69
  • Mechanical Engineering 441
  • Mathematical Physics 106
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A. D. Solomon United States
V. M. Entov Russia
Carolina P. Naveira‐Cotta Brazil
Jian Su Brazil
A.J. Kassab United States
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Citations per year

Countries citing papers authored by M.D. Mikhailov

Since Specialization
Citations

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

Fields of papers citing papers by M.D. Mikhailov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside M.D. Mikhailov, 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.D. Mikhailov Line = papers co-authored together M.D. Mikhailov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Heat Conduction: Lumped Analysis, Integral Transforms, Symbolic Computation
1997183
2 198394
3 201263
4 197560
5 198649
6 198747
7 197545
8 199337
9 197336
10 199934
11 199429
12 197227
13 198724
14 199323
15 200523
16 200222
17 197422
18 197619
19 199317
20 199717

About M.D. Mikhailov

M.D. Mikhailov is a scholar working on Computational Mechanics, Mechanical Engineering, Mechanics of Materials, Numerical Analysis and Mathematical Physics, having authored 82 papers that have together received 1.1k indexed citations. Recurring topics across this work include Heat Transfer and Optimization (13 papers), Numerical methods in inverse problems (9 papers), Differential Equations and Numerical Methods (7 papers), Fluid Dynamics and Turbulent Flows (6 papers), Numerical methods in engineering (5 papers), Advanced Mathematical Modeling in Engineering (5 papers), Mechanical and Thermal Properties Analysis (5 papers) and Fractional Differential Equations Solutions (5 papers). The work is most often cited by research in Numerical Analysis (107 citations), Computational Mechanics (401 citations), Modeling and Simulation (69 citations), Mechanical Engineering (441 citations) and Mathematical Physics (106 citations). M.D. Mikhailov has collaborated with scholars based in Bulgaria, Brazil and United States. Frequent co-authors include Renato M. Cotta, Müslüm Özişik, Atila P. Silva Freire, N.L. Vulchanov, Sanjeev K. Srivastava, S. Del Giudice, G. Comini, S. Kakaç, Leonardo Santos de Brito Alves and Sanjeev Kumar Pandey. Their work appears in journals such as International Journal of Heat and Mass Transfer, International Communications in Heat and Mass Transfer, Journal of Engineering Physics and Thermophysics, Drying Technology and International Journal of Engineering Science.

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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