Jan Mandel

8.9k total citations · 1 hit paper
127 papers, 5.3k citations indexed

About

Jan Mandel is a scholar working on Computational Mechanics, Computational Theory and Mathematics and Global and Planetary Change. According to data from OpenAlex, Jan Mandel has authored 127 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Computational Mechanics, 42 papers in Computational Theory and Mathematics and 39 papers in Global and Planetary Change. Recurrent topics in Jan Mandel's work include Advanced Numerical Methods in Computational Mathematics (59 papers), Fire effects on ecosystems (33 papers) and Meteorological Phenomena and Simulations (30 papers). Jan Mandel is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (59 papers), Fire effects on ecosystems (33 papers) and Meteorological Phenomena and Simulations (30 papers). Jan Mandel collaborates with scholars based in United States, Czechia and France. Jan Mandel's co-authors include Marian Brezina, Charbel Farhat, Petr Vaněk, Jonathan Beezley, Radek Tezaur, Adam K. Kochanski, Clark R. Dohrmann, Steve McCormick, Bedřich Sousedík and Zhiqiang Cai and has published in prestigious journals such as Journal of Computational Physics, Atmospheric Environment and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

Jan Mandel

123 papers receiving 4.7k citations

Hit Papers

Algebraic multigrid by smoothed aggregation for second an... 1996 2026 2006 2016 1996 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
Jan Mandel United States 42 3.2k 1.9k 1.6k 1.2k 921 127 5.3k
Thomas A. Zang United States 27 4.5k 1.4× 907 0.5× 874 0.5× 600 0.5× 316 0.3× 67 8.9k
M. Y. Hussaini United States 18 2.8k 0.9× 607 0.3× 818 0.5× 772 0.6× 183 0.2× 41 6.4k
Anthony T. Patera United States 49 6.2k 1.9× 1.0k 0.5× 1.8k 1.1× 1.1k 0.9× 174 0.2× 153 10.3k
Dongbin Xiu United States 38 2.1k 0.7× 2.4k 1.2× 639 0.4× 783 0.7× 351 0.4× 116 11.6k
Tobin A. Driscoll United States 29 1.9k 0.6× 397 0.2× 772 0.5× 635 0.5× 381 0.4× 78 4.0k
J. Peraire United States 51 7.8k 2.4× 694 0.4× 1.2k 0.8× 1.5k 1.2× 59 0.1× 229 10.4k
Antony Jameson United States 53 11.5k 3.6× 974 0.5× 444 0.3× 416 0.3× 561 0.6× 292 13.5k
Graham F. Carey United States 41 4.2k 1.3× 1.0k 0.5× 1.7k 1.0× 944 0.8× 58 0.1× 298 6.8k
Olivier Pironneau France 36 4.3k 1.3× 1.7k 0.9× 1.1k 0.7× 367 0.3× 103 0.1× 153 6.1k
Julian D. Cole United States 22 2.5k 0.8× 533 0.3× 929 0.6× 467 0.4× 121 0.1× 97 8.0k

Countries citing papers authored by Jan Mandel

Since Specialization
Citations

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

Fields of papers citing papers by Jan Mandel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Mandel

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Mandel. A scholar is included among the top collaborators of Jan Mandel 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 Jan Mandel. Jan Mandel 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
2.
O’Neill, Susan, Rime El Asmar, Yongtao Hu, et al.. (2025). An investigation of corrective approaches for uncertain winds and analysis of impacts on smoke model performance. Agricultural and Forest Meteorology. 376. 110885–110885.
3.
Mallia, Derek V., et al.. (2025). Simulating the impacts of regional wildfire smoke on ozone using a coupled fire-atmosphere-chemistry model. Atmospheric Environment. 360. 121404–121404.
4.
Kochanski, Adam K., et al.. (2023). Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model. Frontiers in Forests and Global Change. 6. 2 indexed citations
5.
Mandel, Jan, et al.. (2021). Machine Learning Estimation of Fire Arrival Time from Level-2 Active Fires Satellite Data. Remote Sensing. 13(11). 2203–2203. 22 indexed citations
6.
Mallia, Derek V., Adam K. Kochanski, Kerry E. Kelly, et al.. (2020). Evaluating Wildfire Smoke Transport Within a Coupled Fire‐Atmosphere Model Using a High‐Density Observation Network for an Episodic Smoke Event Along Utah's Wasatch Front. Journal of Geophysical Research Atmospheres. 125(20). 29 indexed citations
7.
Mallia, Derek V., et al.. (2020). Incorporating a Canopy Parameterization within a Coupled Fire-Atmosphere Model to Improve a Smoke Simulation for a Prescribed Burn. Atmosphere. 11(8). 832–832. 24 indexed citations
9.
Mandel, Jan, et al.. (2016). Hybrid Levenberg–Marquardt and weak-constraint ensemble Kalman smoother method. Nonlinear processes in geophysics. 23(2). 59–73. 14 indexed citations
10.
Cobb, Loren, et al.. (2014). Bayesian tracking of emerging epidemics using ensemble optimal statistical interpolation. Spatial and Spatio-temporal Epidemiology. 10. 39–48. 10 indexed citations
11.
Kochanski, Adam K., Mary Ann Jenkins, S. K. Krueger, et al.. (2010). Evaluation of The Fire Plume Dynamics Simulated by WRF-Fire. AGUFM. 2010. 3 indexed citations
12.
Beezley, Jonathan, Adam K. Kochanski, Volodymyr Y. Kondratenko, Jan Mandel, & Bedřich Sousedík. (2010). Simulation of the Meadow Creek fire using WRF-Fire. AGU Fall Meeting Abstracts. 2010. 5 indexed citations
13.
Mandel, Jan, Jonathan Beezley, Adam K. Kochanski, Volodymyr Y. Kondratenko, & Bedřich Sousedík. (2010). Wildland fire simulation by WRF-Fire. AGU Fall Meeting Abstracts. 2010. 1 indexed citations
14.
Glueck, Deborah H., Jan Mandel, Anis Karimpour‐Fard, Lawrence Hunter, & Keith E. Muller. (2008). Exact Calculations of Average Power for the Benjamini-Hochberg Procedure. The International Journal of Biostatistics. 4(1). Article 11–Article 11. 46 indexed citations
15.
Douglas, Craig C., Richard E. Ewing, Yalchin Efendiev, et al.. (2006). DDDAS approaches to wildland fire modeling and contaminant tracking. Winter Simulation Conference. 2117–2124. 13 indexed citations
16.
Cowsar, Lawrence C., Jan Mandel, & Mary F. Wheeler. (1995). Balancing Domain Decomposition for Mixed Finite Elements. Mathematics of Computation. 64(211). 989–989. 68 indexed citations
17.
Mandel, Jan. (1990). Two‐level domain decomposition preconditioning for the p‐version finite element method in three dimensions. International Journal for Numerical Methods in Engineering. 29(5). 1095–1108. 60 indexed citations
18.
Mandel, Jan, et al.. (1989). Proceedings of the Fourth Copper Mountain Conference on Multigrid Methods. Society for Industrial and Applied Mathematics eBooks. 17 indexed citations
19.
Mandel, Jan. (1989). Two-Level Domain Decomposition Preconditioning For The p-Version Finite Element Method In Three Dimensions. 3 indexed citations
20.
Mandel, Jan, et al.. (1983). A local convergence proof for the iterative aggregation method. Linear Algebra and its Applications. 51. 163–172. 29 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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