David Moxey

2.4k total citations · 2 hit papers
44 papers, 1.7k citations indexed

About

David Moxey is a scholar working on Computational Mechanics, Computer Graphics and Computer-Aided Design and Computer Networks and Communications. According to data from OpenAlex, David Moxey has authored 44 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computational Mechanics, 11 papers in Computer Graphics and Computer-Aided Design and 5 papers in Computer Networks and Communications. Recurrent topics in David Moxey's work include Advanced Numerical Methods in Computational Mathematics (22 papers), Computational Fluid Dynamics and Aerodynamics (17 papers) and Computational Geometry and Mesh Generation (9 papers). David Moxey is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (22 papers), Computational Fluid Dynamics and Aerodynamics (17 papers) and Computational Geometry and Mesh Generation (9 papers). David Moxey collaborates with scholars based in United Kingdom, United States and Germany. David Moxey's co-authors include Spencer J. Sherwin, Dwight Barkley, Joaquim Peiró, Kerstin Avila, Björn Hof, Alberto de Lózar, Marc Avila, Gianmarco Mengaldo, D. De Grazia and Chris D. Cantwell and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Computational Physics.

In The Last Decade

David Moxey

41 papers receiving 1.6k citations

Hit Papers

The Onset of Turbulence in Pipe Flow 2011 2026 2016 2021 2011 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Moxey United Kingdom 18 1.4k 242 219 167 165 44 1.7k
Étienne Mémin France 22 643 0.5× 190 0.8× 212 1.0× 211 1.3× 161 1.0× 72 1.5k
Gianmarco Mengaldo United Kingdom 19 960 0.7× 214 0.9× 182 0.8× 73 0.4× 202 1.2× 44 1.4k
Paul Fischer United States 22 1.5k 1.1× 271 1.1× 272 1.2× 139 0.8× 104 0.6× 50 2.0k
William J. Rider United States 26 3.6k 2.6× 548 2.3× 209 1.0× 70 0.4× 94 0.6× 73 4.2k
Jean‐Yves Trépanier Canada 23 1.3k 0.9× 414 1.7× 48 0.2× 109 0.7× 99 0.6× 122 1.8k
Jamaludin Mohd‐Yusof United States 13 1.5k 1.1× 257 1.1× 162 0.7× 36 0.2× 34 0.2× 26 2.0k
Krzysztof Fidkowski United States 21 2.3k 1.7× 260 1.1× 85 0.4× 35 0.2× 564 3.4× 111 2.5k
Omar Ghattas United States 20 461 0.3× 66 0.3× 126 0.6× 35 0.2× 156 0.9× 38 1.5k
Myoungkyu Lee United States 12 1.3k 0.9× 215 0.9× 466 2.1× 269 1.6× 187 1.1× 28 1.7k
Grégoire Winckelmans Belgium 26 2.1k 1.6× 1.0k 4.3× 660 3.0× 88 0.5× 92 0.6× 144 2.5k

Countries citing papers authored by David Moxey

Since Specialization
Citations

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

Fields of papers citing papers by David Moxey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Moxey

This figure shows the co-authorship network connecting the top 25 collaborators of David Moxey. A scholar is included among the top collaborators of David Moxey 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 David Moxey. David Moxey 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.
Peiró, Joaquim, et al.. (2025). High-order curvilinear mesh generation from third-party meshes. Computer-Aided Design. 191. 103962–103962.
2.
Tabor, Gavin, et al.. (2024). Multi-Point Aerodynamic Optimization of a Backward-Curved Impeller Fan. Open Research Exeter (University of Exeter). 1 indexed citations
3.
Sherwin, Spencer J., et al.. (2024). Lower-order Refined Preconditioning for Spectral/hp Element Methods for Complex, 3D Geometries. Research Portal (King's College London). 2 indexed citations
4.
Hunt, A., et al.. (2024). Flight-ready Electrical Capacitance Tomography SMARTTS tank for use with cryogenics. Experimental Thermal and Fluid Science. 154. 111144–111144. 2 indexed citations
5.
Moxey, David, et al.. (2023). Large Eddy Simulation of an Inverted Multi-element Wing in Ground Effect. Flow Turbulence and Combustion. 110(4). 917–944. 3 indexed citations
6.
Narayan, Akil, et al.. (2022). Fast Barycentric-Based Evaluation Over Spectral/hp Elements. Journal of Scientific Computing. 90(2).
7.
Mengaldo, Gianmarco, David Moxey, Michael G. Turner, et al.. (2021). Industry-Relevant Implicit Large-Eddy Simulation of a High-Performance Road Car via Spectral/hp Element Methods. SIAM Review. 63(4). 723–755. 25 indexed citations
8.
Moxey, David, et al.. (2020). Efficient Matrix-Free High-Order Finite Element Evaluation for Simplicial Elements. SIAM Journal on Scientific Computing. 42(3). C97–C123. 16 indexed citations
9.
Moxey, David, Chris D. Cantwell, Yan Bao, et al.. (2019). Nektar++: Enhancing the capability and application of high-fidelity spectral/ h p element methods. Computer Physics Communications. 249. 107110–107110. 96 indexed citations
10.
Moxey, David, et al.. (2019). Towards a performance-portable high-order implicit flow solver. AIAA Scitech 2019 Forum. 1 indexed citations
11.
Turner, Michael G., et al.. (2018). Accelerating high-order mesh optimisation with an architecture-independent programming model. Computer Physics Communications. 229. 36–53. 10 indexed citations
13.
Turner, Michael G., et al.. (2017). A framework for the generation of high-order curvilinear hybrid meshes for CFD simulations. Procedia Engineering. 203. 206–218. 3 indexed citations
15.
Turner, Michael G., Joaquim Peiró, & David Moxey. (2016). A Variational Framework for High-order Mesh Generation. Procedia Engineering. 163. 340–352. 16 indexed citations
16.
Moxey, David, Chris D. Cantwell, Robert M. Kirby, & Spencer J. Sherwin. (2016). Optimising the performance of the spectral/hp element method with collective linear algebra operations. Computer Methods in Applied Mechanics and Engineering. 310. 628–645. 17 indexed citations
17.
Mengaldo, Gianmarco, D. De Grazia, David Moxey, Peter Vincent, & Spencer J. Sherwin. (2015). Dealiasing techniques for high-order spectral element methods on regular and irregular grids. Journal of Computational Physics. 299. 56–81. 76 indexed citations
18.
Grazia, D. De, Gianmarco Mengaldo, David Moxey, Peter Vincent, & Spencer J. Sherwin. (2014). Connections between the discontinuous Galerkin method and high‐order flux reconstruction schemes. International Journal for Numerical Methods in Fluids. 75(12). 860–877. 54 indexed citations
19.
Ferrer, Esteban, David Moxey, Richard Willden, & Spencer J. Sherwin. (2014). Stability of Projection Methods for Incompressible Flows Using High Order Pressure-Velocity Pairs of Same Degree: Continuous and Discontinuous Galerkin Formulations. Communications in Computational Physics. 16(3). 817–840. 38 indexed citations
20.
Avila, Kerstin, David Moxey, Alberto de Lózar, et al.. (2011). The Onset of Turbulence in Pipe Flow. Science. 333(6039). 192–196. 420 indexed citations breakdown →

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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