Е. В. Кустова

3.5k total citations
173 papers, 2.6k citations indexed

About

Е. В. Кустова is a scholar working on Applied Mathematics, Computational Mechanics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Е. В. Кустова has authored 173 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 155 papers in Applied Mathematics, 82 papers in Computational Mechanics and 64 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Е. В. Кустова's work include Gas Dynamics and Kinetic Theory (155 papers), Computational Fluid Dynamics and Aerodynamics (49 papers) and Optical properties and cooling technologies in crystalline materials (28 papers). Е. В. Кустова is often cited by papers focused on Gas Dynamics and Kinetic Theory (155 papers), Computational Fluid Dynamics and Aerodynamics (49 papers) and Optical properties and cooling technologies in crystalline materials (28 papers). Е. В. Кустова collaborates with scholars based in Russia, Italy and France. Е. В. Кустова's co-authors include Е. А. Нагнибеда, I. Armenise, A. Chikhaoui, O. Kunova, Georgii Oblapenko, В. А. Истомин, M. Capitelli, Gilberto M. Kremer, A. И. Сайфутдинов and D. Giordano and has published in prestigious journals such as The Journal of Chemical Physics, Journal of Applied Physics and Chemical Physics Letters.

In The Last Decade

Е. В. Кустова

159 papers receiving 2.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Е. В. Кустова Russia 30 2.2k 1.2k 953 765 295 173 2.6k
Marco Panesi United States 30 2.2k 1.0× 1.1k 1.0× 895 0.9× 859 1.1× 518 1.8× 176 2.9k
Thierry Magin Belgium 28 2.0k 0.9× 1.1k 0.9× 577 0.6× 1.0k 1.3× 399 1.4× 188 3.0k
I. Armenise Italy 26 1.2k 0.6× 544 0.5× 706 0.7× 400 0.5× 435 1.5× 54 1.8k
Deborah A. Levin United States 32 2.5k 1.2× 1.9k 1.6× 488 0.5× 1.4k 1.8× 666 2.3× 375 4.0k
Sergey Gimelshein United States 31 2.3k 1.0× 1.5k 1.3× 425 0.4× 1.2k 1.6× 452 1.5× 189 3.1k
Takashi Abe Japan 27 1.2k 0.6× 982 0.9× 521 0.5× 1.3k 1.7× 812 2.8× 286 3.0k
Deepak Bose United States 29 2.6k 1.2× 1.6k 1.4× 385 0.4× 1.7k 2.2× 364 1.2× 86 3.3k
Е. А. Нагнибеда Russia 20 1.1k 0.5× 561 0.5× 447 0.5× 368 0.5× 91 0.3× 62 1.2k
Fabrizio Esposito Italy 25 974 0.4× 336 0.3× 920 1.0× 317 0.4× 558 1.9× 61 1.9k
Vincent Giovangigli∥ France 29 1.1k 0.5× 2.1k 1.8× 245 0.3× 786 1.0× 121 0.4× 104 3.0k

Countries citing papers authored by Е. В. Кустова

Since Specialization
Citations

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

Fields of papers citing papers by Е. В. Кустова

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Е. В. Кустова. 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 Е. В. Кустова. The network helps show where Е. В. Кустова may publish in the future.

Co-authorship network of co-authors of Е. В. Кустова

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

All Works

20 of 20 papers shown
1.
Кустова, Е. В., et al.. (2025). Shock wave structure in binary mixtures of CO2 with noble gases. Physics of Fluids. 37(3).
2.
Kunova, O., et al.. (2024). Effect of exchange reactions and NO vibrational excitation on shock-heated air component flows. Chemical Physics Letters. 847. 141331–141331. 3 indexed citations
3.
Kravchenko, Dmitry V., et al.. (2024). State-to-state oxygen kinetics behind reflected shock waves: Assessment of different approaches. AIP conference proceedings. 3050. 140009–140009. 4 indexed citations
4.
Истомин, В. А., et al.. (2024). Different approaches for simulating heat and radiative fluxes in planetary entry problems. AIP conference proceedings. 3050. 80002–80002.
5.
Кустова, Е. В., et al.. (2023). Modeling of nonequilibrium processes behind a shock wave in a mixture of carbon dioxide and argon. Vestnik of Saint Petersburg University Mathematics Mechanics Astronomy. 10(2). 277–288. 1 indexed citations
6.
Истомин, В. А., et al.. (2023). Scientific school of non-equilibrium aeromechanics in Saint Petersburg State University. Vestnik of Saint Petersburg University Mathematics Mechanics Astronomy. 10 (68)(3). 406–456.
7.
Кустова, Е. В., et al.. (2023). Continuum Models for Bulk Viscosity and Relaxation in Polyatomic Gases. Fluids. 8(2). 48–48. 14 indexed citations
8.
Сайфутдинов, A. И. & Е. В. Кустова. (2023). Simulation of filamentation dynamics of microwave discharge in nitrogen. Plasma Sources Science and Technology. 32(12). 125010–125010. 5 indexed citations
9.
Kunova, O., et al.. (2022). Hybrid approach to accurate modeling of coupled vibrational-chemical kinetics in carbon dioxide. Physics of Fluids. 34(2). 19 indexed citations
10.
Кустова, Е. В., et al.. (2022). Assessment of multi-temperature relaxation models for carbon dioxide vibrational kinetics. Plasma Sources Science and Technology. 31(10). 104002–104002. 4 indexed citations
11.
Кустова, Е. В., et al.. (2022). Boundary conditions for fluid-dynamic parameters of a single-component gas flow with vibrational deactivation on a solid wall. Vestnik of Saint Petersburg University Mathematics Mechanics Astronomy. 9(2). 366–377. 3 indexed citations
12.
Кустова, Е. В., et al.. (2022). Modeling vibrational relaxation rate using machine learning methods. Vestnik of Saint Petersburg University Mathematics Mechanics Astronomy. 9(1). 113–125. 3 indexed citations
13.
Kunova, O., et al.. (2021). Four-temperature kinetic model for CO2 vibrational relaxation. Physics of Fluids. 33(1). 23 indexed citations
14.
Kunova, O., et al.. (2020). Vibrational relaxation of carbon dioxide in state-to-state and multi-temperature approaches. Physical Review Fluids. 5(12). 19 indexed citations
15.
Кустова, Е. В., et al.. (2020). Numerical simulations of shock waves in viscous carbon dioxide flows using finite volume method. Vestnik of Saint Petersburg University Mathematics Mechanics Astronomy. 65(3). 500–510. 3 indexed citations
16.
Кустова, Е. В., et al.. (2018). Rate Coefficients of Exchange Reactions in Air and Carbon Dioxide. 19(3). 1–10. 1 indexed citations
17.
Кустова, Е. В., et al.. (2018). Refinement of state-resolved models for chemical kinetics using the data of trajectory calculations. 19(3). 1–14. 6 indexed citations
18.
Кустова, Е. В., et al.. (2011). Non-Equilibrium Kinetics and Transport Processes in a Hypersonic Flow of CO[sub 2]∕CO∕O[sub 2]∕C∕O Mixture. AIP conference proceedings. 1227–1232. 2 indexed citations
19.
Кустова, Е. В., et al.. (2009). Transport coefficients in nonequilibrium gas-mixture flows with electronic excitation. Physical Review E. 80(4). 46407–46407. 28 indexed citations
20.
Capitelli, M., Gianpiero Colonna, Е. В. Кустова, & Е. А. Нагнибеда. (2002). State-to-state Kinetics and Transport Properties in Supersonic Air Nozzle Flows. ESASP. 487. 137. 2 indexed citations

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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