A.G. Buchan

443 total citations
30 papers, 316 citations indexed

About

A.G. Buchan is a scholar working on Aerospace Engineering, Computational Mechanics and Statistical and Nonlinear Physics. According to data from OpenAlex, A.G. Buchan has authored 30 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Aerospace Engineering, 13 papers in Computational Mechanics and 8 papers in Statistical and Nonlinear Physics. Recurrent topics in A.G. Buchan's work include Nuclear reactor physics and engineering (13 papers), Advanced Numerical Methods in Computational Mathematics (10 papers) and Model Reduction and Neural Networks (8 papers). A.G. Buchan is often cited by papers focused on Nuclear reactor physics and engineering (13 papers), Advanced Numerical Methods in Computational Mathematics (10 papers) and Model Reduction and Neural Networks (8 papers). A.G. Buchan collaborates with scholars based in United Kingdom, United States and Canada. A.G. Buchan's co-authors include Christopher C. Pain, Liang Yang, Kirk D. Atkinson, R.P. Smedley‐Stevenson, Steven Dargaville, A.J.H. Goddard, M.D. Eaton, David J. Brenner, David Welch and Paul N. Smith and has published in prestigious journals such as Scientific Reports, Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

A.G. Buchan

29 papers receiving 308 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A.G. Buchan United Kingdom 12 118 94 82 53 42 30 316
Jacques Peter France 10 331 2.8× 146 1.6× 32 0.4× 61 1.2× 15 0.4× 35 518
Todd S. Palmer United States 11 64 0.5× 143 1.5× 9 0.1× 22 0.4× 5 0.1× 67 324
Hadrien Calmet Spain 12 147 1.2× 63 0.7× 269 3.3× 12 0.2× 18 0.4× 26 591
Alexander Grahn Germany 13 78 0.7× 210 2.2× 67 0.8× 15 0.3× 5 0.1× 38 549
J.-F. Gerbeau France 4 524 4.4× 67 0.7× 49 0.6× 33 0.6× 4 764
Kevin W. Cassel United States 12 265 2.2× 76 0.8× 73 0.9× 48 0.9× 39 472
Jens-Dominik Müeller United Kingdom 10 183 1.6× 47 0.5× 48 0.6× 20 0.4× 3 0.1× 29 291
Tatjana Jevremović United States 14 151 1.3× 274 2.9× 148 1.8× 7 0.1× 3 0.1× 86 705
Beatriz Eguzkitza Spain 11 90 0.8× 36 0.4× 84 1.0× 6 0.1× 4 0.1× 20 305

Countries citing papers authored by A.G. Buchan

Since Specialization
Citations

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

Fields of papers citing papers by A.G. Buchan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A.G. Buchan. 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 A.G. Buchan. The network helps show where A.G. Buchan may publish in the future.

Co-authorship network of co-authors of A.G. Buchan

This figure shows the co-authorship network connecting the top 25 collaborators of A.G. Buchan. A scholar is included among the top collaborators of A.G. Buchan 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 A.G. Buchan. A.G. Buchan 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.
Xiao, Dunhui, et al.. (2025). A parametric non-linear non-intrusive reduce-order model using deep transfer learning. Computer Methods in Applied Mechanics and Engineering. 438. 117807–117807. 1 indexed citations
2.
Buchan, A.G., et al.. (2022). An adaptive reduced order model for the angular discretization of the Boltzmann transport equation using independent basis sets over a partitioning of the space‐angle domain. International Journal for Numerical Methods in Engineering. 123(16). 3781–3799. 4 indexed citations
3.
Piggott, Matthew D., et al.. (2022). Development of a gamma ray dose rate calculation and mapping tool for Lagrangian marine nuclear emergency response models. Marine Pollution Bulletin. 181. 113895–113895. 1 indexed citations
4.
Buchan, A.G., Liang Yang, David Welch, David J. Brenner, & Kirk D. Atkinson. (2021). Improved estimates of 222 nm far-UVC susceptibility for aerosolized human coronavirus via a validated high-fidelity coupled radiation-CFD code. Scientific Reports. 11(1). 19930–19930. 19 indexed citations
5.
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Dargaville, Steven, A.G. Buchan, R.P. Smedley‐Stevenson, Paul N. Smith, & Christopher C. Pain. (2021). A comparison of element agglomeration algorithms for unstructured geometric multigrid. Journal of Computational and Applied Mathematics. 390. 113379–113379. 4 indexed citations
7.
Buchan, A.G., et al.. (2020). A discontinuous and adaptive reduced order model for the angular discretization of the Boltzmann transport equation. International Journal for Numerical Methods in Engineering. 121(24). 5647–5666. 14 indexed citations
8.
Buchan, A.G., Liang Yang, & Kirk D. Atkinson. (2020). Predicting airborne coronavirus inactivation by far-UVC in populated rooms using a high-fidelity coupled radiation-CFD model. Scientific Reports. 10(1). 19659–19659. 51 indexed citations
9.
Buchan, A.G., Steven Dargaville, & Christopher C. Pain. (2019). A combined immersed body and adaptive mesh method for simulating neutron transport within complex structures. Annals of Nuclear Energy. 134. 88–100. 3 indexed citations
10.
Dargaville, Steven, A.G. Buchan, R.P. Smedley‐Stevenson, Paul N. Smith, & Christopher C. Pain. (2019). Scalable angular adaptivity for Boltzmann transport. Journal of Computational Physics. 406. 109124–109124. 11 indexed citations
11.
Dargaville, Steven, A.G. Buchan, R.P. Smedley‐Stevenson, Paul N. Smith, & Christopher C. Pain. (2019). Angular adaptivity with spherical harmonics for Boltzmann transport. Journal of Computational Physics. 397. 108846–108846. 11 indexed citations
12.
Dargaville, Steven, et al.. (2017). A goal-based angular adaptivity method for thermal radiation modelling in non grey media. Journal of Quantitative Spectroscopy and Radiative Transfer. 200. 215–224. 12 indexed citations
13.
Buchan, A.G., et al.. (2014). An immersed body method for coupled neutron transport and thermal hydraulic simulations of PWR assemblies. Annals of Nuclear Energy. 68. 124–135. 6 indexed citations
14.
Smedley‐Stevenson, R.P., et al.. (2014). Adjoint eigenvalue correction for elliptic and hyperbolic neutron transport problems. Progress in Nuclear Energy. 76. 1–16. 3 indexed citations
15.
Buchan, A.G., et al.. (2013). Goal based mesh adaptivity for fixed source radiation transport calculations. Annals of Nuclear Energy. 55. 169–183. 12 indexed citations
16.
Buchan, A.G., Christopher C. Pain, Jefferson Gomes, et al.. (2012). Simulated spatially dependent transient kinetics analysis of the Oak Ridge Y12 plant criticality excursion. Progress in Nuclear Energy. 63. 12–21. 2 indexed citations
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Nicol, Kathleen, et al.. (2010). Synchronous Presentation of Hashimoto Thyroiditis and Papillary Thyroid Carcinoma in a 7-Year-Old Girl. Journal of Ultrasound in Medicine. 29(6). 1007–1010. 1 indexed citations
20.
Buchan, A.G., Christopher C. Pain, M.D. Eaton, R.P. Smedley‐Stevenson, & A.J.H. Goddard. (2005). Linear and quadratic octahedral wavelets on the sphere for angular discretisations of the Boltzmann transport equation. Annals of Nuclear Energy. 32(11). 1224–1273. 48 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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