D. Pelletier

1.6k citations
84 papers · 1.3k · h-index 21

Impact in

Papers in

D. Pelletier

82 papers receiving 1.3k citations

Peers

D. Pelletier
Comparison fields: 5 of 71
  • Computational Mechanics 1.0k
  • Statistics, Probability and Uncertainty 214
  • Statistical and Nonlinear Physics 185
  • Environmental Engineering 187
  • Numerical Analysis 61
Replace Dominique Pelletier with:
Dominique Pelletier Canada
Jean‐Sébastien Schotté France
Philippe Geuzaine United States
Srinivasan Arunajatesan United States
Paul G. A. Cizmas United States
Stéphane Étienne Canada
Esteban Ferrer Spain
Marius Paraschivoiu Canada
Luís Eça Portugal
M. Hoekstra Netherlands
D. Pelletier relative to Dominique Pelletier Canada Dominique Pelletier's profile →
Citations per field
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Dominique Pelletier · 1×
Citations per year

Countries citing papers authored by D. Pelletier

Since Specialization
Citations

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

Fields of papers citing papers by D. Pelletier

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside D. Pelletier, 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 D. Pelletier Line = papers co-authored together D. Pelletier links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201196
2 200964
3 200763
4 200862
5 200857
6 199751
7 200644
8 199943
9 200539
10 200737
11 200034
12 199933
13 199831
14 201028
15 199827
16 200523
17 200123
18 201022
19 200421
20 199621

About D. Pelletier

D. Pelletier is a scholar working on Computational Mechanics, Electrical and Electronic Engineering, Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Mechanics of Materials, having authored 84 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Fluid Dynamics and Aerodynamics (53 papers), Advanced Numerical Methods in Computational Mathematics (42 papers), Fluid Dynamics and Turbulent Flows (29 papers), Probabilistic and Robust Engineering Design (12 papers), Model Reduction and Neural Networks (10 papers), Wind and Air Flow Studies (8 papers), Silicon and Solar Cell Technologies (8 papers) and Fluid Dynamics and Vibration Analysis (8 papers). The work is most often cited by research in Computational Mechanics (1.0k citations), Statistics, Probability and Uncertainty (214 citations), Statistical and Nonlinear Physics (185 citations), Environmental Engineering (187 citations) and Numerical Analysis (61 citations). D. Pelletier has collaborated with scholars based in Canada, United States and France. Frequent co-authors include F. Ilinca, Jeff Borggaard, A. Garon, A. Hay, Stéphane Étienne, É. Turgeon, M. Hoekstra, Luís Eça, J.‐F. Hétu and Imran Akhtar. Their work appears in journals such as International Journal for Numerical Methods in Fluids, International journal of computational fluid dynamics, AIAA Journal, Journal of Computational Physics and Journal of Crystal Growth.

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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