Brian Carnes

600 total citations
25 papers, 423 citations indexed

About

Brian Carnes is a scholar working on Computational Mechanics, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment. According to data from OpenAlex, Brian Carnes has authored 25 papers receiving a total of 423 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computational Mechanics, 10 papers in Electrical and Electronic Engineering and 6 papers in Renewable Energy, Sustainability and the Environment. Recurrent topics in Brian Carnes's work include Fuel Cells and Related Materials (9 papers), Computational Fluid Dynamics and Aerodynamics (7 papers) and Advanced Numerical Methods in Computational Mathematics (6 papers). Brian Carnes is often cited by papers focused on Fuel Cells and Related Materials (9 papers), Computational Fluid Dynamics and Aerodynamics (7 papers) and Advanced Numerical Methods in Computational Mathematics (6 papers). Brian Carnes collaborates with scholars based in United States and Canada. Brian Carnes's co-authors include Ned Djilali, Guglielmo Scovazzi, Simone Rossi, Xianyi Zeng, Marc Secanell, Afzal Suleman, Henning Struchtrup, Graham F. Carey, V. Gregory Weirs and Dusan Spernjak and has published in prestigious journals such as Journal of The Electrochemical Society, Journal of Power Sources and Electrochimica Acta.

In The Last Decade

Brian Carnes

21 papers receiving 411 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Brian Carnes United States 10 241 192 141 79 70 25 423
Farzad Mohebbi New Zealand 10 100 0.4× 20 0.1× 101 0.7× 74 0.9× 27 0.4× 23 414
L. T. Yeh United States 7 66 0.3× 43 0.2× 88 0.6× 74 0.9× 70 1.0× 23 410
Yuchao Hua China 9 50 0.2× 33 0.2× 47 0.3× 59 0.7× 48 0.7× 22 420
Yuhe Shang China 10 111 0.5× 45 0.2× 183 1.3× 19 0.2× 89 1.3× 22 429
Jaakko Larjola Finland 11 159 0.7× 101 0.5× 169 1.2× 9 0.1× 75 1.1× 35 910
XueTao Cheng China 24 50 0.2× 135 0.7× 80 0.6× 84 1.1× 186 2.7× 64 1.7k
Rory A. Roberts United States 12 150 0.6× 47 0.2× 40 0.3× 227 2.9× 48 0.7× 67 515
Karl Yngve Lervåg Norway 9 89 0.4× 77 0.4× 85 0.6× 11 0.1× 116 1.7× 12 306
Mohammed Alaoui Morocco 11 41 0.2× 57 0.3× 188 1.3× 22 0.3× 158 2.3× 45 394
O. Joneydi Shariatzadeh Iran 9 54 0.2× 76 0.4× 68 0.5× 89 1.1× 160 2.3× 9 551

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-authorship network of co-authors of Brian Carnes

This figure shows the co-authorship network connecting the top 25 collaborators of Brian Carnes. A scholar is included among the top collaborators of Brian Carnes 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 Brian Carnes. Brian Carnes 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.
Lee, Kookjin, et al.. (2022). Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models. Computer Methods in Applied Mechanics and Engineering. 401. 115396–115396. 15 indexed citations
2.
Ray, Jaideep, Sarah L. Kieweg, Brian Carnes, et al.. (2020). Estimation of Inflow Uncertainties in Laminar Hypersonic Double-Cone Experiments. AIAA Journal. 58(10). 4461–4474. 19 indexed citations
3.
Carnes, Brian, V. Gregory Weirs, & Thomas M. Smith. (2019). Code verification and numerical error estimation for use in model validation of laminar, hypersonic double-cone flows. AIAA Scitech 2019 Forum. 3 indexed citations
4.
Kieweg, Sarah L., Jaideep Ray, V. Gregory Weirs, et al.. (2019). Validation Assessment of Hypersonic Double-Cone Flow Simulations using Uncertainty Quantification, Sensitivity Analysis, and Validation Metrics. AIAA Scitech 2019 Forum. 3 indexed citations
5.
Kieweg, Sarah L., Jaideep Ray, V. Gregory Weirs, et al.. (2019). Correction: Validation Assessment of Hypersonic Double-Cone Flow Simulations using Uncertainty Quantification, Sensitivity Analysis, and Validation Metrics. AIAA Scitech 2019 Forum. 1 indexed citations
6.
Ray, Jaideep, Sarah L. Kieweg, Brian Carnes, et al.. (2019). Estimation of inflow uncertainties in laminar hypersonic double-cone experiments. AIAA Scitech 2019 Forum. 4 indexed citations
7.
Carnes, Brian, et al.. (2016). Mesh Scaling for Affordable Solution Verification. Procedia Engineering. 163. 46–58. 3 indexed citations
8.
Carnes, Brian, et al.. (2016). Introduction: The 2014 Sandia Verification and Validation Challenge Workshop. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1(1). 5 indexed citations
9.
Scovazzi, Guglielmo, Brian Carnes, Xianyi Zeng, & Simone Rossi. (2015). A simple, stable, and accurate linear tetrahedral finite element for transient, nearly, and fully incompressible solid dynamics: a dynamic variational multiscale approach. International Journal for Numerical Methods in Engineering. 106(10). 799–839. 93 indexed citations
10.
Scovazzi, Guglielmo & Brian Carnes. (2012). Weak boundary conditions for wave propagation problems in confined domains: Formulation and implementation using a variational multiscale method. Computer Methods in Applied Mechanics and Engineering. 221-222. 117–131. 12 indexed citations
11.
Carnes, Brian, et al.. (2012). Simulation and validation of liquid water transport in fuel cells from neutron imaging experiments.. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
13.
Carnes, Brian, Ken S. Chen, Dusan Spernjak, & Gang Luo. (2011). Validation of PEMFC Computer Models Using Segmented Current and Temperature Data. ECS Transactions. 41(1). 287–292.
14.
Chen, Ken S., Brian Carnes, Liang Hao, et al.. (2011). Toward the Development and Validation of a Comprehensive PEM Fuel Cell Model. 757–765.
15.
Chen, Ken S., Brian Carnes, Fangming Jiang, Gang Luo, & Chao‐Yang Wang. (2010). Toward Developing a Computational Capability for PEM Fuel Cell Design and Optimization. 445–454.
16.
Carnes, Brian & Graham F. Carey. (2007). Local boundary value problems for the error in FE approximation of non‐linear diffusion systems. International Journal for Numerical Methods in Engineering. 73(5). 665–684. 5 indexed citations
17.
Carnes, Brian & Ned Djilali. (2006). Analysis of coupled proton and water transport in a PEM fuel cell using the binary friction membrane model. Electrochimica Acta. 52(3). 1038–1052. 32 indexed citations
18.
Carnes, Brian, et al.. (2005). Transport Phenomena in Polymer Electrolyte Membranes. Journal of The Electrochemical Society. 152(9). A1815–A1815. 45 indexed citations
19.
Carnes, Brian & Ned Djilali. (2005). Systematic parameter estimation for PEM fuel cell models. Journal of Power Sources. 144(1). 83–93. 58 indexed citations
20.
Carey, Graham F., Michael L. Anderson, Brian Carnes, & Benjamin Kirk. (2003). Some aspects of adaptive grid technology related to boundary and interior layers. Journal of Computational and Applied Mathematics. 166(1). 55–86. 16 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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