Perrine Pepiot

1.4k total citations
33 papers, 1.1k citations indexed

About

Perrine Pepiot is a scholar working on Computational Mechanics, Fluid Flow and Transfer Processes and Biomedical Engineering. According to data from OpenAlex, Perrine Pepiot has authored 33 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Computational Mechanics, 19 papers in Fluid Flow and Transfer Processes and 11 papers in Biomedical Engineering. Recurrent topics in Perrine Pepiot's work include Advanced Combustion Engine Technologies (19 papers), Combustion and flame dynamics (17 papers) and Heat transfer and supercritical fluids (14 papers). Perrine Pepiot is often cited by papers focused on Advanced Combustion Engine Technologies (19 papers), Combustion and flame dynamics (17 papers) and Heat transfer and supercritical fluids (14 papers). Perrine Pepiot collaborates with scholars based in United States, France and Germany. Perrine Pepiot's co-authors include Heinz Pitsch, Krithika Narayanaswamy, Olivier Desjardins, Jesse Capecelatro, Éléonore Riber, Bénédicte Cuenot, Mark R. Nimlos, Himanshu Goyal, Stephen B. Pope and Katherine R. Gaston and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Applied Catalysis B: Environmental and Chemical Engineering Journal.

In The Last Decade

Perrine Pepiot

32 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Perrine Pepiot United States 18 711 570 366 173 105 33 1.1k
Suhui Li China 17 431 0.6× 296 0.5× 231 0.6× 168 1.0× 127 1.2× 36 837
C. Allouis Italy 17 402 0.6× 289 0.5× 211 0.6× 119 0.7× 180 1.7× 50 846
Helmut Ciezki Germany 18 901 1.3× 734 1.3× 198 0.5× 752 4.3× 157 1.5× 109 1.6k
R.E. Peck United States 15 611 0.9× 302 0.5× 362 1.0× 195 1.1× 156 1.5× 36 926
Jing Gong China 15 468 0.7× 781 1.4× 453 1.2× 206 1.2× 254 2.4× 33 1.1k
Scott C. Hill United States 11 643 0.9× 398 0.7× 632 1.7× 62 0.4× 271 2.6× 15 1.1k
Sayak Banerjee India 13 428 0.6× 305 0.5× 232 0.6× 123 0.7× 68 0.6× 22 737
M.P. Heap United States 16 382 0.5× 282 0.5× 284 0.8× 142 0.8× 193 1.8× 36 753
Reinhard Seiser United States 21 1.4k 2.0× 1.4k 2.4× 637 1.7× 482 2.8× 272 2.6× 43 2.0k

Countries citing papers authored by Perrine Pepiot

Since Specialization
Citations

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

Fields of papers citing papers by Perrine Pepiot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Perrine Pepiot

This figure shows the co-authorship network connecting the top 25 collaborators of Perrine Pepiot. A scholar is included among the top collaborators of Perrine Pepiot 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 Perrine Pepiot. Perrine Pepiot 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.
Pepiot, Perrine, et al.. (2023). A novel machine learning based lumping approach for the reduction of large kinetic mechanisms for plasma-assisted combustion applications. Combustion and Flame. 260. 113252–113252. 4 indexed citations
2.
Pope, Stephen B., et al.. (2022). A feasibility study on the use of low-dimensional simulations for database generation in adaptive chemistry approaches. Combustion Theory and Modelling. 26(7). 1239–1261. 2 indexed citations
3.
Pepiot, Perrine, et al.. (2022). Efficient treatment of secondary kinetic processes for pre-partitioned adaptive chemistry approaches. Combustion Theory and Modelling. 26(6). 1098–1113. 1 indexed citations
4.
5.
Aubin, Cameron A., Hyeon Seok An, Elizabeth M. Fisher, et al.. (2021). Valveless microliter combustion for densely packed arrays of powerful soft actuators. Proceedings of the National Academy of Sciences. 118(39). 30 indexed citations
6.
Pepiot, Perrine, et al.. (2021). Automated construction of reduced mechanisms and additive reaction modules. Combustion and Flame. 234. 111682–111682. 5 indexed citations
7.
Pope, Stephen B., et al.. (2019). A combined PPAC-RCCE-ISAT methodology for efficient implementation of combustion chemistry. Combustion Theory and Modelling. 23(6). 1021–1053. 7 indexed citations
8.
Goyal, Himanshu & Perrine Pepiot. (2018). On the Validation of a One-Dimensional Biomass Pyrolysis Model Using Uncertainty Quantification. ACS Sustainable Chemistry & Engineering. 6(9). 12153–12165. 10 indexed citations
9.
Goyal, Himanshu, Olivier Desjardins, Perrine Pepiot, & Jesse Capecelatro. (2018). A computational study of the effects of multiphase dynamics in catalytic upgrading of biomass pyrolysis vapor. AIChE Journal. 64(9). 3341–3353. 15 indexed citations
10.
Poinsot, Thierry, Lyle M. Pickett, Perrine Pepiot, et al.. (2018). A conceptual model of the flame stabilization mechanisms for a lifted Diesel-type flame based on direct numerical simulation and experiments. Combustion and Flame. 201. 65–77. 27 indexed citations
11.
Goyal, Himanshu & Perrine Pepiot. (2017). A Compact Kinetic Model for Biomass Pyrolysis at Gasification Conditions. Energy & Fuels. 31(11). 12120–12132. 22 indexed citations
12.
Jaravel, Thomas, Éléonore Riber, Bénédicte Cuenot, & Perrine Pepiot. (2017). Prediction of flame structure and pollutant formation of Sandia flame D using Large Eddy Simulation with direct integration of chemical kinetics. Combustion and Flame. 188. 180–198. 28 indexed citations
13.
Pepiot, Perrine, et al.. (2016). A novel atom tracking algorithm for the analysis of complex chemical kinetic networks. Combustion and Flame. 173. 387–401. 4 indexed citations
14.
15.
Fox, Rodney O., et al.. (2015). Reduced Chemical Kinetics for the Modeling of TiO2 Nanoparticle Synthesis in Flame Reactors. Industrial & Engineering Chemistry Research. 54(20). 5407–5415. 9 indexed citations
16.
Narayanaswamy, Krithika, Perrine Pepiot, & Heinz Pitsch. (2013). A chemical mechanism for low to high temperature oxidation of n-dodecane as a component of transportation fuel surrogates. Combustion and Flame. 161(4). 866–884. 190 indexed citations
17.
Gaston, Katherine R., Mark W. Jarvis, Perrine Pepiot, et al.. (2011). Biomass Pyrolysis and Gasification of Varying Particle Sizes in a Fluidized-Bed Reactor. Energy & Fuels. 25(8). 3747–3757. 76 indexed citations
18.
Capecelatro, Jesse, Perrine Pepiot, & Olivier Desjardins. (2010). Eulerian-Lagrangian Simulations of Three-Dimensional Turbulent Riser Flows. Bulletin of the American Physical Society. 63.
19.
Desjardins, Olivier & Perrine Pepiot. (2009). Analysis of dense particulate flow dynamics using a Euler-Lagrange approach. Bulletin of the American Physical Society. 62. 1 indexed citations
20.
Pepiot, Perrine & Heinz Pitsch. (2005). Systematic Reduction of Large Chemical Mechanisms. 42 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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