Tobias Leicht

629 citations
19 papers · 369 indexed · h-index 10
Topics
Computational Fluid Dynamics and Aerodynamics (16 papers)Advanced Numerical Methods in Computational Mathematics (15 papers)Model Reduction and Neural Networks (6 papers)
Partner nations
GermanyItaly

In The Last Decade

Tobias Leicht

18 papers receiving 347 citations

Peers

Tobias Leicht
Comparison fields: 5 of 37
  • Computational Mechanics 349
  • Statistical and Nonlinear Physics 61
  • Applied Mathematics 40
  • Mechanics of Materials 33
  • Aerospace Engineering 33
Replace Marco Ceze with:
Marco Ceze United States
Aravind Balan Germany
Laslo T. Diosady United States
Niklas Fehn Germany
Dmitry S. Kamenetskiy United States
S.P. Spekreijse Netherlands
M.‐G. Vallet Canada
Masayoshi Senga United States
Z. J. Wang United States
Gilbert Rogé France
Tobias Leicht relative to Marco Ceze United States Marco Ceze's profile →
Citations per field
00.5×1.5×
Marco Ceze · 1×
Citations per year

Countries citing papers authored by Tobias Leicht

Since Specialization
Citations

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

Fields of papers citing papers by Tobias Leicht

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tobias Leicht

This figure shows the co-authorship network connecting the top 25 collaborators of Tobias Leicht. A scholar is included among the top collaborators of Tobias Leicht 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 Tobias Leicht. Tobias Leicht is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 7
2 4
3
DLR-Project Digital-X: Next generation CFD solver 'Flucs'
5
4 3
5 9
6 17
7 18
8 1
9 5
10
Higher order and adaptive DG methods for compressible flows
9
11 12
12 3
13 66
14 18
15 49
16 83
17 51
18
Anisotropic Mesh Refinement for Discontinuous Galerkin Methods in Aerodynamic Flow Simulations
1
19 8

About Tobias Leicht

Tobias Leicht is a scholar working on Computational Mechanics, Statistical and Nonlinear Physics and Numerical Analysis, having authored 19 papers that have together received 369 indexed citations. Recurring topics across this work include Computational Fluid Dynamics and Aerodynamics (16 papers), Advanced Numerical Methods in Computational Mathematics (15 papers) and Model Reduction and Neural Networks (6 papers). The work is most often cited by research in Computational Mechanics (349 citations), Computer Graphics and Computer-Aided Design (31 citations) and Statistical and Nonlinear Physics (61 citations). Tobias Leicht has collaborated with scholars based in Germany and Italy. Frequent co-authors include Ralf Hartmann, Časlav Ilić, Markus Widhalm, Joël Brézillon, Oskar Haidn, Jörg Riccius, Andreas Krumbein, Ralf Heinrich, Lorenzo Botti and Jens Jägersküpper. Their work appears in journals such as Journal of Computational Physics, International Journal for Numerical Methods in Fluids and Aerospace Science and Technology.

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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