Ben Evans

506 total citations
34 papers, 315 citations indexed

About

Ben Evans is a scholar working on Computational Mechanics, Aerospace Engineering and Applied Mathematics. According to data from OpenAlex, Ben Evans has authored 34 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Mechanics, 8 papers in Aerospace Engineering and 7 papers in Applied Mathematics. Recurrent topics in Ben Evans's work include Computational Fluid Dynamics and Aerodynamics (12 papers), Fluid Dynamics and Turbulent Flows (8 papers) and Gas Dynamics and Kinetic Theory (7 papers). Ben Evans is often cited by papers focused on Computational Fluid Dynamics and Aerodynamics (12 papers), Fluid Dynamics and Turbulent Flows (8 papers) and Gas Dynamics and Kinetic Theory (7 papers). Ben Evans collaborates with scholars based in United Kingdom, United States and New Zealand. Ben Evans's co-authors include Lerrel Pinto, Farzad Mohebbi, O. Hassan, Sean Walton, Timon Rabczuk, Ken Morgan, Dunhui Xiao, Jinlong Fu, Min Wang and Mathieu Sellier and has published in prestigious journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Applied Thermal Engineering.

In The Last Decade

Ben Evans

33 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ben Evans United Kingdom 11 87 72 50 48 41 34 315
А. Е. Бондарев Russia 10 117 1.3× 46 0.6× 22 0.4× 13 0.3× 15 0.4× 68 293
Wayne Johnson United States 9 86 1.0× 318 4.4× 95 1.9× 32 0.7× 27 0.7× 31 429
Brendan Tracey United States 8 313 3.6× 161 2.2× 21 0.4× 46 1.0× 9 0.2× 12 533
Byungjoon Lee South Korea 14 57 0.7× 55 0.8× 29 0.6× 55 1.1× 83 2.0× 62 641
Tilman Neunhoeffer Germany 4 233 2.7× 32 0.4× 16 0.3× 43 0.9× 35 0.9× 5 416
Jiaojiao Chen China 10 42 0.5× 10 0.1× 13 0.3× 33 0.7× 31 0.8× 33 546
Tianhang Xiao China 14 295 3.4× 311 4.3× 36 0.7× 36 0.8× 16 0.4× 57 515
Yoshiaki Abe Japan 13 375 4.3× 304 4.2× 28 0.6× 31 0.6× 25 0.6× 39 538

Countries citing papers authored by Ben Evans

Since Specialization
Citations

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

Fields of papers citing papers by Ben Evans

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ben Evans

This figure shows the co-authorship network connecting the top 25 collaborators of Ben Evans. A scholar is included among the top collaborators of Ben Evans 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 Ben Evans. Ben Evans 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.
Discacciati, Marco, et al.. (2025). PGD-based local surrogate models via overlapping domain decomposition: A computational comparison. Finite Elements in Analysis and Design. 253. 104475–104475.
2.
Evans, Ben, et al.. (2025). Modelling aerodynamic drag of a very low earth orbit 1U CubeSat utilising a Boltzmann-BGK approach. Advances in Space Research. 75(10). 7610–7623. 1 indexed citations
3.
Evans, Ben, et al.. (2024). See to Touch: Learning Tactile Dexterity through Visual Incentives. 13825–13832. 13 indexed citations
4.
Fu, Jinlong, et al.. (2023). Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network. Computer Methods in Applied Mechanics and Engineering. 410. 116049–116049. 8 indexed citations
5.
Walton, Sean, et al.. (2023). Evaluating the effect of a ducted winglet on the induced drag of wind turbine blade using CFD and Trefftz plane analysis. Engineering With Computers. 39(6). 3835–3846. 1 indexed citations
6.
Fu, Jinlong, Min Wang, Bin Chen, et al.. (2023). A data-driven framework for permeability prediction of natural porous rocks via microstructural characterization and pore-scale simulation. Engineering With Computers. 39(6). 3895–3926. 20 indexed citations
7.
Evans, Ben, et al.. (2023). Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation. 5954–5961. 45 indexed citations
8.
Walton, Sean, et al.. (2021). It's the journey not the destination. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 231–232. 2 indexed citations
9.
Mohebbi, Farzad, Ben Evans, & Mathieu Sellier. (2021). On an Exact Step Length in Gradient-Based Aerodynamic Shape Optimization—Part II: Viscous Flows. Fluids. 6(3). 106–106. 4 indexed citations
10.
Mohebbi, Farzad & Ben Evans. (2020). Simultaneous estimation of heat flux and heat transfer coefficient in irregular geometries made of functionally graded materials. International Journal of Thermofluids. 1-2. 100009–100009. 9 indexed citations
11.
Mohebbi, Farzad, Ben Evans, Alexander D. Shaw, & Mathieu Sellier. (2019). An inverse analysis for determination of space-dependent heat flux in heat conduction problems in the presence of variable thermal conductivity. International Journal for Computational Methods in Engineering Science and Mechanics. 20(3). 229–241. 7 indexed citations
12.
Evans, Ben & Sean Walton. (2017). Aerodynamic optimisation of a hypersonic reentry vehicle based on solution of the Boltzmann–BGK equation and evolutionary optimisation. Applied Mathematical Modelling. 52. 215–240. 13 indexed citations
13.
Evans, Ben, et al.. (2017). Discrete boundary smoothing using control node parameterisation for aerodynamic shape optimisation. Applied Mathematical Modelling. 48. 113–133. 1 indexed citations
14.
Evans, Ben, et al.. (2015). A novel implementation of computational aerodynamic shape optimisation using Modified Cuckoo Search. Applied Mathematical Modelling. 40(7-8). 4543–4559. 17 indexed citations
15.
Evans, Ben, et al.. (2015). Computational aerodynamic optimisation of vertical axis wind turbine blades. Applied Mathematical Modelling. 40(2). 1038–1051. 21 indexed citations
16.
Hassan, O., et al.. (2014). Spray drag effect of fluidized sand for a supersonic vehicle. BIRD (Basque Center for Applied Mathematics). 2(3). 169–177. 2 indexed citations
17.
Lavery, Nicholas, et al.. (2014). Investigating the thermal profile of a marine vessel engine room through simulation with field measurements. Applied Thermal Engineering. 73(1). 1360–1370. 15 indexed citations
18.
Evans, Ben, et al.. (2012). Design optimisation using computational fluid dynamics applied to a land–based supersonic vehicle, the BLOODHOUND SSC. Structural and Multidisciplinary Optimization. 47(2). 301–316. 8 indexed citations
19.
Evans, Ben, Ken Morgan, & O. Hassan. (2010). A discontinuous finite element solution of the Boltzmann kinetic equation in collisionless and BGK forms for macroscopic gas flows. Applied Mathematical Modelling. 35(3). 996–1015. 15 indexed citations
20.
Evans, Ben, et al.. (2010). Computational fluid dynamics applied to the aerodynamic design of a land‐based supersonic vehicle. Numerical Methods for Partial Differential Equations. 27(1). 141–159. 13 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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