Brian C. Vermeire
- Computational Mechanics top 2%
- Computational Fluid Dynamics and Aerodynamics 35
- Fluid Dynamics and Turbulent Flows 26
- Advanced Numerical Methods in Computational Mathematics 15
- Lattice Boltzmann Simulation Studies 5
- Fluid Dynamics and Vibration Analysis 5
- Numerical Analysis top 10%
- Numerical methods for differential equations 9
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- Model Reduction and Neural Networks 9
- Environmental Engineering top 10%
- Aerospace Engineering top 10%
- Aerodynamics and Acoustics in Jet Flows 5
- Co-authors
- Peter VincentFreddie WitherdenSiva NadarajahLeigh OrfEric SavoryPaul G. TuckerJin Seok ParkA. Jameson
- Journals
- Journal of Fluid Mechanics (1 paper)Journal of Computational Physics (13 papers)Computer Methods in Applied Mechanics and Engineering (1 paper)
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Brian C. Vermeire
37 papers receiving 639 citations
Peers
Comparison fields: 5 of 45
- Computational Mechanics 528
- Numerical Analysis 69
- Statistical and Nonlinear Physics 101
- Environmental Engineering 116
- Aerospace Engineering 161
Countries citing papers authored by Brian C. Vermeire
This map shows the geographic impact of Brian C. Vermeire'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 Brian C. Vermeire with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian C. Vermeire more than expected).
Fields of papers citing papers by Brian C. Vermeire
This network shows the impact of papers produced by Brian C. Vermeire. 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 Brian C. Vermeire. The network helps show where Brian C. Vermeire may publish in the future.
Co-authorship network
The 11 scholars most cited alongside Brian C. Vermeire, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 3 | |
| 11 | 2022 | 6 | |
| 12 | 2022 | 2 | |
| 13 | 2021 | 12 | |
| 14 | 2021 | 9 | |
| 15 | 2020 | 10 | |
| 16 | 2020 | 14 | |
| 17 | 2020 | 8 | |
| 18 | 2015 | 0 | |
| 19 | 2013 | 3 | |
| 20 | 2011 | 29 |
About Brian C. Vermeire
Brian C. Vermeire is a scholar working on Computational Mechanics, Numerical Analysis and Statistical and Nonlinear Physics, having authored 45 papers that have together received 664 indexed citations. Recurring topics across this work include Computational Fluid Dynamics and Aerodynamics (35 papers), Fluid Dynamics and Turbulent Flows (26 papers), Advanced Numerical Methods in Computational Mathematics (15 papers), Numerical methods for differential equations (9 papers), Model Reduction and Neural Networks (9 papers), Lattice Boltzmann Simulation Studies (5 papers), Fluid Dynamics and Vibration Analysis (5 papers) and Aerodynamics and Acoustics in Jet Flows (5 papers). The work is most often cited by research in Computational Mechanics (528 citations), Numerical Analysis (69 citations) and Statistical and Nonlinear Physics (101 citations). Brian C. Vermeire has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Peter Vincent, Freddie Witherden, Siva Nadarajah, Leigh Orf, Eric Savory, Paul G. Tucker, Jin Seok Park, A. Jameson, Yoshiaki Abe and Antony Jameson. Their work appears in journals such as Journal of Fluid Mechanics, Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering.
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.