Chunkan Yu

626 total citations
42 papers, 397 citations indexed

About

Chunkan Yu is a scholar working on Fluid Flow and Transfer Processes, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Chunkan Yu has authored 42 papers receiving a total of 397 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Fluid Flow and Transfer Processes, 35 papers in Computational Mechanics and 14 papers in Aerospace Engineering. Recurrent topics in Chunkan Yu's work include Advanced Combustion Engine Technologies (36 papers), Combustion and flame dynamics (35 papers) and Combustion and Detonation Processes (12 papers). Chunkan Yu is often cited by papers focused on Advanced Combustion Engine Technologies (36 papers), Combustion and flame dynamics (35 papers) and Combustion and Detonation Processes (12 papers). Chunkan Yu collaborates with scholars based in Germany, China and United Kingdom. Chunkan Yu's co-authors include Ulrich Maas, Agustín Valera-Medina, Syed Mashruk, Sven Eckart, Hua Xiao, V. Bykov, Hartmut Krause, Michael Pfitzner, Robert Schießl and Mohammad Alnajideen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physical Chemistry Chemical Physics and International Journal of Hydrogen Energy.

In The Last Decade

Chunkan Yu

39 papers receiving 382 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chunkan Yu Germany 11 307 280 104 103 66 42 397
N. Slavinskaya Germany 7 394 1.3× 336 1.2× 105 1.0× 78 0.8× 68 1.0× 35 478
Marco Osvaldo Vigueras-Zúñiga Mexico 8 181 0.6× 182 0.7× 127 1.2× 63 0.6× 44 0.7× 17 361
Yong Fan Japan 10 205 0.7× 280 1.0× 57 0.5× 117 1.1× 30 0.5× 36 388
Ponnuthurai Gokulakrishnan United States 14 375 1.2× 422 1.5× 79 0.8× 160 1.6× 18 0.3× 38 518
Sven Eckart Germany 15 472 1.5× 396 1.4× 184 1.8× 210 2.0× 61 0.9× 42 631
Scott A. Steinmetz United States 10 263 0.9× 230 0.8× 101 1.0× 38 0.4× 82 1.2× 22 393
Shuai Huang China 13 283 0.9× 163 0.6× 144 1.4× 116 1.1× 34 0.5× 40 435
Shini Lai China 6 239 0.8× 158 0.6× 190 1.8× 65 0.6× 54 0.8× 7 349
Yoshihiro Nagai Japan 2 281 0.9× 234 0.8× 173 1.7× 86 0.8× 72 1.1× 3 375
Bernard Labégorre France 12 144 0.5× 233 0.8× 58 0.6× 85 0.8× 23 0.3× 14 354

Countries citing papers authored by Chunkan Yu

Since Specialization
Citations

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

Fields of papers citing papers by Chunkan Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunkan Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Chunkan Yu. A scholar is included among the top collaborators of Chunkan Yu 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 Chunkan Yu. Chunkan Yu 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
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2.
Chi, Cheng, Chunkan Yu, Bénédicte Cuenot, Ulrich Maas, & Dominique Thévenin. (2024). Effect of differential diffusion on head-on quenching of premixed NH3/H2/air flames within turbulent boundary layers. Proceedings of the Combustion Institute. 40(1-4). 105276–105276. 2 indexed citations
3.
Alnajideen, Mohammad, Hao Shi, William F. Northrop, et al.. (2024). Ammonia combustion and emissions in practical applications: a review. SHILAP Revista de lepidopterología. 3(1). 38 indexed citations
4.
Mashruk, Syed, Hao Shi, B. Aravind, et al.. (2024). Perspectives on NOX Emissions and Impacts from Ammonia Combustion Processes. Energy & Fuels. 38(20). 19253–19292. 36 indexed citations
5.
Yu, Chunkan & Agustín Valera-Medina. (2024). A Comprehensive Numerical Study on the Inhibition Effect of Ammonia on Various (Un)strained Premixed Stoichiometric Hydrogen/Air Flame Systems. Energy & Fuels. 39(1). 981–991. 1 indexed citations
6.
Yu, Chunkan, Sven Eckart, D. Markus, et al.. (2023). Investigation of spark ignition processes of laminar strained premixed stoichiometric NH3-H2-air flames. Journal of Loss Prevention in the Process Industries. 83. 105043–105043. 12 indexed citations
7.
8.
Yu, Chunkan & V. Bykov. (2023). GQL-RedChem: A MatLAB-based tool for the model reduction for chemical kinetics based on the Global Quasi-linearization (GQL) approach. Software Impacts. 17. 100555–100555. 1 indexed citations
9.
Wang, Qian, et al.. (2023). Numerical Study on the Combustion Properties of Ammonia/DME and Ammonia/DMM Mixtures. Energies. 16(19). 6929–6929. 14 indexed citations
10.
Yu, Chunkan, Liming Cai, Cheng Chi, et al.. (2023). Numerical Investigation on the Head-on Quenching (HoQ) of Laminar Premixed Lean to Stoichiometric Ammonia–Hydrogen-Air Flames. Flow Turbulence and Combustion. 111(4). 1301–1322. 7 indexed citations
11.
Yu, Chunkan, et al.. (2023). Influence of the chemical kinetics on the prediction of turbulent non-premixed jet CH$$_4$$ flames. Journal of the Brazilian Society of Mechanical Sciences and Engineering. 45(10). 2 indexed citations
12.
Yu, Chunkan, Liming Cai, & Jy Chen. (2023). Stochastic Modeling of Partially Stirred Reactor (PaSR) for the Investigation of the Turbulence-Chemistry Interaction for the Ammonia-Air Combustion. Flow Turbulence and Combustion. 112(2). 509–536. 3 indexed citations
13.
Yu, Chunkan, et al.. (2022). Reaction-Diffusion Manifolds including differential diffusion applied to methane/air combustion in strong extinction regimes. Combustion Theory and Modelling. 26(3). 451–481. 1 indexed citations
14.
Yu, Chunkan, et al.. (2022). The hierarchy of low-dimensional manifolds in the context of multiple mapping conditioning mixing model. Proceedings of the Combustion Institute. 39(2). 2299–2308. 4 indexed citations
15.
16.
Yu, Chunkan, et al.. (2020). Coupling of mixing models with manifold based simplified chemistry in PDF modeling of turbulent reacting flows. Proceedings of the Combustion Institute. 38(2). 2645–2653. 10 indexed citations
17.
Yu, Chunkan, et al.. (2020). Validation of an Eulerian Stochastic Fields Solver Coupled with Reaction–Diffusion Manifolds on LES of Methane/Air Non-premixed Flames. Flow Turbulence and Combustion. 107(2). 441–477. 8 indexed citations
18.
Yu, Chunkan, et al.. (2018). Quasi‐Spectral Method for the Solution of the Master Equation for Unimolecular Reaction Systems. International Journal of Chemical Kinetics. 50(5). 357–369. 3 indexed citations
19.
Yu, Chunkan, V. Bykov, & Ulrich Maas. (2018). Coupling of simplified chemistry with mixing processes in PDF simulations of turbulent flames. Proceedings of the Combustion Institute. 37(2). 2183–2190. 15 indexed citations
20.
Yu, Chunkan, V. Bykov, & Ulrich Maas. (2018). Global quasi-linearization (GQL)versusQSSA for a hydrogen–air auto-ignition problem. Physical Chemistry Chemical Physics. 20(16). 10770–10779. 5 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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