Qinglong Tang

2.0k total citations
76 papers, 1.6k citations indexed

About

Qinglong Tang is a scholar working on Fluid Flow and Transfer Processes, Computational Mechanics and Automotive Engineering. According to data from OpenAlex, Qinglong Tang has authored 76 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Fluid Flow and Transfer Processes, 64 papers in Computational Mechanics and 25 papers in Automotive Engineering. Recurrent topics in Qinglong Tang's work include Advanced Combustion Engine Technologies (75 papers), Combustion and flame dynamics (64 papers) and Vehicle emissions and performance (24 papers). Qinglong Tang is often cited by papers focused on Advanced Combustion Engine Technologies (75 papers), Combustion and flame dynamics (64 papers) and Vehicle emissions and performance (24 papers). Qinglong Tang collaborates with scholars based in China, Saudi Arabia and United States. Qinglong Tang's co-authors include Mingfa Yao, Haifeng Liu, Gaetano Magnotti, Hao Shi, James Turner, Kalim Uddeen, Bengt Johansson, Chao Geng, Priybrat Sharma and Emre Cenker and has published in prestigious journals such as Journal of Cleaner Production, Applied Energy and Energy Conversion and Management.

In The Last Decade

Qinglong Tang

73 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Qinglong Tang China 23 1.5k 1.0k 461 404 379 76 1.6k
Jiangping Tian China 25 1.5k 1.0× 989 1.0× 319 0.7× 635 1.6× 411 1.1× 92 1.7k
Emre Cenker Saudi Arabia 24 1.3k 0.9× 1.1k 1.0× 338 0.7× 169 0.4× 518 1.4× 92 1.4k
Zunhua Zhang China 22 913 0.6× 569 0.5× 217 0.5× 553 1.4× 314 0.8× 77 1.3k
Hua Tian China 17 1.0k 0.7× 606 0.6× 282 0.6× 501 1.2× 272 0.7× 87 1.2k
Cinzia Tornatore Italy 23 1.3k 0.9× 818 0.8× 517 1.1× 336 0.8× 197 0.5× 96 1.5k
Cherian A. Idicheria United States 13 1.3k 0.9× 1.1k 1.0× 334 0.7× 203 0.5× 280 0.7× 21 1.4k
Gesheng Li China 22 766 0.5× 458 0.4× 198 0.4× 477 1.2× 275 0.7× 69 1.1k
Yuri M. Wright Switzerland 27 1.8k 1.2× 1.8k 1.7× 312 0.7× 229 0.6× 676 1.8× 105 2.1k
Yanzhao An China 20 955 0.6× 695 0.7× 406 0.9× 244 0.6× 186 0.5× 60 1.0k
Anders Hultqvist Sweden 23 1.9k 1.3× 1.5k 1.4× 809 1.8× 309 0.8× 332 0.9× 46 2.1k

Countries citing papers authored by Qinglong Tang

Since Specialization
Citations

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

Fields of papers citing papers by Qinglong Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qinglong Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Qinglong Tang. A scholar is included among the top collaborators of Qinglong Tang 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 Qinglong Tang. Qinglong Tang 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.
Yang, Rui, Heng Liu, Bin Li, Qinglong Tang, & Mingfa Yao. (2025). Experimental and numerical investigation on the superheated and subcooled ammonia spray characteristics under high injection pressure. Fuel. 387. 134320–134320. 3 indexed citations
2.
Uddeen, Kalim, Qinglong Tang, Hao Shi, & James Turner. (2025). Improving the combustion performance of ammonia in a spark-ignition engine by mixing methane coupled with multiple spark ignition: An optical study. International Journal of Engine Research. 26(10). 1527–1540. 2 indexed citations
3.
4.
Yang, Rui, et al.. (2025). Optical and numerical study on high-pressure liquid ammonia spray atomization and ignition characteristics under different injector nozzle diameters. Energy Conversion and Management. 333. 119781–119781. 2 indexed citations
5.
Yang, Rui, et al.. (2024). Experimental study on the spray characteristics of high-pressure liquid ammonia under different ambient conditions. Journal of the Energy Institute. 117. 101771–101771. 13 indexed citations
6.
Tang, Qinglong, et al.. (2024). The ignition mechanisms and chemical reaction kinetics of nitrogen oxides of ammonia/diesel dual-fuel engine combustion. Applied Thermal Engineering. 262. 125287–125287. 12 indexed citations
7.
Tang, Qinglong, et al.. (2024). Computational study of the impacts of the nozzle configurations on passive pre-chamber engine combustion. Applied Thermal Engineering. 250. 123530–123530. 6 indexed citations
8.
Li, Gang, Qinglong Tang, H.S. Zhen, et al.. (2024). Fundamental insights on turbulence characterization, vortex motion and ignition mechanism of sub/supersonic turbulent jet flames. Applied Thermal Engineering. 248. 123274–123274. 7 indexed citations
9.
Liu, Xinlei, Qinglong Tang, & Hong G. Im. (2024). Enhancing ammonia engine efficiency through pre-chamber combustion and dual-fuel compression ignition techniques. Journal of Cleaner Production. 436. 140622–140622. 43 indexed citations
10.
Sun, Haibo, Gang Li, Jincheng Li, et al.. (2024). Development of an LSTM-CCF-MA Model for Predicting NOx Emission and Exhaust Temperature of a Diesel Engine. International Journal of Automotive Technology. 26(2). 437–450.
11.
Tang, Qinglong, et al.. (2024). Combustion characteristics and flame development of ammonia in an optical spark-ignition engine. Fuel. 375. 132601–132601. 9 indexed citations
12.
Tang, Qinglong, et al.. (2024). Numerical investigation and optimization of the ammonia/diesel dual fuel engine combustion under high ammonia substitution ratio. Journal of the Energy Institute. 117. 101797–101797. 21 indexed citations
13.
14.
15.
Tang, Qinglong, et al.. (2023). Numerical study of the effects of excess air ratio on passive pre-chamber jet performance and ignition mechanism. Applied Thermal Engineering. 234. 121315–121315. 18 indexed citations
16.
Uddeen, Kalim, et al.. (2023). Investigation into Various Strategies to Achieve Stable Ammonia Combustion in a Spark-Ignition Engine. SAE International Journal of Advances and Current Practices in Mobility. 6(4). 2102–2113. 10 indexed citations
17.
Uddeen, Kalim, Qinglong Tang, Hao Shi, & James Turner. (2023). Performance and emission analysis of ammonia-ethanol and ammonia-methane dual-fuel combustion in a spark-ignition engine: An optical study. Fuel. 358. 130296–130296. 41 indexed citations
18.
Shi, Hao, Minh Bau Luong, Qinglong Tang, et al.. (2023). Prediction of knock intensity and validation in an optical SI engine. Combustion and Flame. 254. 112854–112854. 11 indexed citations
19.
Sampath, Ramgopal, Qinglong Tang, Manuel Echeverri Marquez, et al.. (2020). Study on the Pre-Chamber Fueling Ratio Effect on the Main Chamber Combustion Using Simultaneous PLIF and OH* Chemiluminescence Imaging. SAE International Journal of Advances and Current Practices in Mobility. 3(1). 137–149. 20 indexed citations
20.

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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