Andreas G. Class

1.0k citations
72 papers · 751 · h-index 17

Impact in

Papers in

Andreas G. Class

65 papers receiving 714 citations

Peers

Andreas G. Class
Comparison fields: 5 of 60
  • Computational Mechanics 471
  • Fluid Flow and Transfer Processes 92
  • Aerospace Engineering 347
  • Numerical Analysis 38
  • Safety, Risk, Reliability and Quality 47
Replace Igor Goldfarb with:
Igor Goldfarb Israel
Leonardo Santos de Brito Alves Brazil
V. Bykov Germany
Xin Xue China
Michael L. Frankel United States
N.S. Mera United Kingdom
Xiao-Yen Wang United States
F. A. Williams United States
Luca Massa United States
П. А. Крутицкий Russia
Andreas G. Class relative to Igor Goldfarb Israel Igor Goldfarb's profile →
Citations per field
00.5×5.6×
Igor Goldfarb · 1×
Citations per year

Countries citing papers authored by Andreas G. Class

Since Specialization
Citations

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

Fields of papers citing papers by Andreas G. Class

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Andreas G. Class, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Andreas G. Class Line = papers co-authored together Andreas G. Class links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200877
2 199563
3 201144
4 201442
5 200841
6 200339
7 200634
8 200333
9 201433
10 200830
11 201227
12 201323
13 200818
14 201118
15 201317
16 200116
17 199516
18 201016
19 200610
20 201810

About Andreas G. Class

Andreas G. Class is a scholar working on Aerospace Engineering, Computational Mechanics, Materials Chemistry, Biomedical Engineering and Statistics, Probability and Uncertainty, having authored 72 papers that have together received 751 indexed citations. Recurring topics across this work include Nuclear reactor physics and engineering (26 papers), Nuclear Engineering Thermal-Hydraulics (21 papers), Nuclear Materials and Properties (13 papers), Heat transfer and supercritical fluids (11 papers), Combustion and flame dynamics (11 papers), Probabilistic and Robust Engineering Design (10 papers), Model Reduction and Neural Networks (6 papers) and Nuclear Physics and Applications (6 papers). The work is most often cited by research in Computational Mechanics (471 citations), Fluid Flow and Transfer Processes (92 citations), Aerospace Engineering (347 citations), Numerical Analysis (38 citations) and Safety, Risk, Reliability and Quality (47 citations). Andreas G. Class has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include B. J. Matkowsky, Thomas S. Schulenberg, A. Bayliss, A. Y. Klimenko, R.T. Lahey, Thomas Gomez, F. Roelofs, Eckart Laurien, L. Krebs and Elisabeth Schröder. Their work appears in journals such as Nuclear Engineering and Design, Journal of Nuclear Materials, Progress in Nuclear Energy, Annals of Nuclear Energy and Journal of Computational Physics.

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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