Brian Carnes

682 citations
35 papers · 502 · h-index 11

Impact in

Papers in

Brian Carnes

30 papers receiving 495 citations

Peers

Brian Carnes
Comparison fields: 5 of 35
  • Computational Mechanics 168
  • Electrical and Electronic Engineering 232
  • Numerical Analysis 15
  • Applied Mathematics 30
  • Statistics, Probability and Uncertainty 10
Replace Vitaliy Gyrya with:
Vitaliy Gyrya United States
Steven Dargaville United Kingdom
Jan Lienemann Germany
Hui Feng China
Yi-Jung Chen Taiwan
Kim S. Bey United States
Dehui Yang China
S.K. Gangaraj United States
Yudong Zhang China
Chang‐Hsien Tai Taiwan
Brian Carnes relative to Vitaliy Gyrya United States Vitaliy Gyrya's profile →
Citations per field
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Vitaliy Gyrya · 1×
Citations per year

Countries citing papers authored by Brian Carnes

Since Specialization
Citations

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

Fields of papers citing papers by Brian Carnes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015104
2 200669
3 200563
4 200548
5 201337
6 200633
7 202020
8 202018
9 200316
10 202215
11 201212
12 20218
13 20227
14 20075
15 20135
16 20165
17
Thermal contact algorithms in SIERRA mechanics
20084
18 20194
19 20194
20 20194

About Brian Carnes

Brian Carnes is a scholar working on Computational Mechanics, Electrical and Electronic Engineering, Statistics, Probability and Uncertainty, Applied Mathematics and Hardware and Architecture, having authored 35 papers that have together received 502 indexed citations. Recurring topics across this work include Fuel Cells and Related Materials (12 papers), Advanced Numerical Methods in Computational Mathematics (9 papers), Computational Fluid Dynamics and Aerodynamics (8 papers), Probabilistic and Robust Engineering Design (3 papers), Gas Dynamics and Kinetic Theory (3 papers), Parallel Computing and Optimization Techniques (2 papers), Computational Geometry and Mesh Generation (1 paper) and Radiative Heat Transfer Studies (1 paper). The work is most often cited by research in Computational Mechanics (168 citations), Electrical and Electronic Engineering (232 citations), Numerical Analysis (15 citations), Applied Mathematics (30 citations) and Statistics, Probability and Uncertainty (10 citations). Brian Carnes has collaborated with scholars based in United States and Canada. Frequent co-authors include Ned Djilali, Guglielmo Scovazzi, Xianyi Zeng, Simone Rossi, Marc Secanell, Afzal Suleman, Henning Struchtrup, V. Gregory Weirs, Graham F. Carey and Liang Hao. Their work appears in journals such as Electrochimica Acta, Journal of Computational Physics, Journal of Power Sources, Computer Methods in Applied Mechanics and Engineering and International Journal for Numerical Methods in 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.

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