David Andrš

3.1k total citations · 2 hit papers
33 papers, 1.7k citations indexed

About

David Andrš is a scholar working on Aerospace Engineering, Materials Chemistry and Computational Mechanics. According to data from OpenAlex, David Andrš has authored 33 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Aerospace Engineering, 16 papers in Materials Chemistry and 9 papers in Computational Mechanics. Recurrent topics in David Andrš's work include Nuclear reactor physics and engineering (17 papers), Nuclear Materials and Properties (14 papers) and Nuclear Engineering Thermal-Hydraulics (9 papers). David Andrš is often cited by papers focused on Nuclear reactor physics and engineering (17 papers), Nuclear Materials and Properties (14 papers) and Nuclear Engineering Thermal-Hydraulics (9 papers). David Andrš collaborates with scholars based in United States, Czechia and Germany. David Andrš's co-authors include Derek Gaston, Richard Martineau, Michael Tonks, Cody Permann, John W. Peterson, Andrew E. Slaughter, Paul C. Millett, R.L. Williamson, Paul Talbot and Fande Kong and has published in prestigious journals such as Journal of Computational Physics, Computer Physics Communications and Journal of Nuclear Materials.

In The Last Decade

David Andrš

31 papers receiving 1.6k citations

Hit Papers

MOOSE: Enabling massively parallel m... 2012 2026 2016 2021 2020 2012 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 Andrš United States 17 1.1k 947 355 214 198 33 1.7k
Richard Martineau United States 19 999 0.9× 1.0k 1.1× 262 0.7× 306 1.4× 160 0.8× 64 1.7k
Cody Permann United States 15 858 0.8× 756 0.8× 275 0.8× 144 0.7× 177 0.9× 32 1.3k
Derek Gaston United States 19 1.6k 1.5× 1.4k 1.4× 535 1.5× 342 1.6× 327 1.7× 56 2.6k
Jason Hales United States 22 1.7k 1.6× 1.4k 1.5× 234 0.7× 90 0.4× 126 0.6× 65 1.9k
L. Luzzi Italy 28 2.3k 2.2× 2.4k 2.5× 569 1.6× 331 1.5× 94 0.5× 169 3.4k
Glen Hansen United States 15 397 0.4× 405 0.4× 203 0.6× 257 1.2× 141 0.7× 44 1.1k
Andrew E. Slaughter United States 13 475 0.4× 424 0.4× 191 0.5× 119 0.6× 134 0.7× 31 980
Hamid Aı̈t Abderrahim Belgium 17 590 0.5× 696 0.7× 130 0.4× 89 0.4× 128 0.6× 58 1.1k
Michael Tonks United States 37 3.5k 3.2× 2.0k 2.1× 1.2k 3.5× 230 1.1× 540 2.7× 146 4.1k
Cetin Unal United States 17 630 0.6× 637 0.7× 365 1.0× 397 1.9× 54 0.3× 64 1.3k

Countries citing papers authored by David Andrš

Since Specialization
Citations

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

Fields of papers citing papers by David Andrš

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Andrš

This figure shows the co-authorship network connecting the top 25 collaborators of David Andrš. A scholar is included among the top collaborators of David Andrš 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 Andrš. David Andrš 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.
Hu, Rui, Ling Zou, Guojun Hu, et al.. (2024). SAM: A Modern System Code for Advanced Non-LWR Safety Analysis. Nuclear Technology. 211(9). 1883–1902. 2 indexed citations
2.
Hansel, Joshua, et al.. (2024). The MOOSE Thermal Hydraulics Module. The Journal of Open Source Software. 9(94). 6146–6146. 13 indexed citations
3.
Green, Christopher P., Joshua Hansel, David Andrš, et al.. (2024). The MOOSE fluid properties module. Computer Physics Communications. 307. 109407–109407.
4.
Lindsay, Alexander, Guillaume Giudicelli, Péter German, et al.. (2023). MOOSE Navier–Stokes module. SoftwareX. 23. 101503–101503. 15 indexed citations
6.
Andrš, David, et al.. (2021). Two-zone stratified wetwell model development and implementation for RELAP-7. Annals of Nuclear Energy. 164. 108592–108592. 3 indexed citations
7.
Matthews, Christopher, Vincent Labouré, Mark D. DeHart, et al.. (2021). Coupled Multiphysics Simulations of Heat Pipe Microreactors Using DireWolf. Nuclear Technology. 207(7). 1142–1162. 49 indexed citations
8.
Martineau, Richard, David Andrš, Robert Carlsen, et al.. (2020). Multiphysics for nuclear energy applications using a cohesive computational framework. Nuclear Engineering and Design. 367. 110751–110751. 18 indexed citations
9.
Slaughter, Andrew E., Michael Tonks, Derek Gaston, et al.. (2014). Moose: A Framework to Enable Rapid Advances and Collaboration in Modeling Snow and Avalanches. 644–650.
10.
Šolı́n, Pavel, et al.. (2014). Arbitrary-level hanging nodes for adaptive hp-FEM approximations in 3D. Journal of Computational and Applied Mathematics. 270. 121–133. 17 indexed citations
11.
Andersson, David A., Philippe Garcia, Xiang-Yang Liu, et al.. (2014). Atomistic modeling of intrinsic and radiation-enhanced fission gas (Xe) diffusion in UO2±x: Implications for nuclear fuel performance modeling. Journal of Nuclear Materials. 451(1-3). 225–242. 83 indexed citations
12.
Zhao, Haihua, Ling Zou, Hongbin Zhang, David Andrš, & Richard Martineau. (2014). Developing Fully Coupled Dynamical Reactor Core Isolation System Models in RELAP-7 for Extended Station Black-Out Analysis. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1 indexed citations
13.
Permann, Cody, David Andrš, John W. Peterson, & Derek Gaston. (2013). MASSIVE HYBRID PARALLELISM FOR FULLY IMPLICIT MULTIPHYSICS. University of North Texas Digital Library (University of North Texas). 4 indexed citations
14.
Tonks, Michael, Paul C. Millett, Pankaj Nerikar, et al.. (2013). Multiscale development of a fission gas thermal conductivity model: Coupling atomic, meso and continuum level simulations. Journal of Nuclear Materials. 440(1-3). 193–200. 32 indexed citations
15.
Tonks, Michael, et al.. (2012). A quantitative comparison between and elements for solving the Cahn–Hilliard equation. Journal of Computational Physics. 236. 74–80. 36 indexed citations
16.
Williamson, R.L., Jason Hales, Stephen Novascone, et al.. (2012). Multidimensional multiphysics simulation of nuclear fuel behavior. Journal of Nuclear Materials. 423(1-3). 149–163. 339 indexed citations breakdown →
17.
Tonks, Michael, Derek Gaston, Paul C. Millett, David Andrš, & Paul Talbot. (2011). An object-oriented finite element framework for multiphysics phase field simulations. Computational Materials Science. 51(1). 20–29. 227 indexed citations
18.
Andrš, David, et al.. (2009). On Scientific Data and Image Compression Based on Adaptive Higher-Order FEM. 2 indexed citations
19.
Červený, Jakub, et al.. (2009). Monolithic discretization of linear thermoelasticity problems via adaptive multimesh hp-FEM. Journal of Computational and Applied Mathematics. 234(7). 2350–2357. 30 indexed citations
20.
Šolı́n, Pavel, et al.. (2009). PDE-independent adaptive hp-FEM based on hierarchic extension of finite element spaces. Journal of Computational and Applied Mathematics. 233(12). 3086–3094. 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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