David D. Wickman

696 total citations
18 papers, 578 citations indexed

About

David D. Wickman is a scholar working on Fluid Flow and Transfer Processes, Computational Mechanics and Biomedical Engineering. According to data from OpenAlex, David D. Wickman has authored 18 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Fluid Flow and Transfer Processes, 12 papers in Computational Mechanics and 11 papers in Biomedical Engineering. Recurrent topics in David D. Wickman's work include Advanced Combustion Engine Technologies (17 papers), Biodiesel Production and Applications (11 papers) and Combustion and flame dynamics (10 papers). David D. Wickman is often cited by papers focused on Advanced Combustion Engine Technologies (17 papers), Biodiesel Production and Applications (11 papers) and Combustion and flame dynamics (10 papers). David D. Wickman collaborates with scholars based in United States, Canada and Germany. David D. Wickman's co-authors include Rolf D. Reitz, P. K. Senecal, Michael Bergin, Andrzej Sobiesiak, Yu Shi, Haiwen Ge, Caroline L. Genzale, Sudhakar Das, Yu Zhang and William De Ojeda and has published in prestigious journals such as Fuel, SAE technical papers on CD-ROM/SAE technical paper series and SAE International Journal of Engines.

In The Last Decade

David D. Wickman

18 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David D. Wickman United States 13 551 300 278 275 82 18 578
Hanho Yun United States 13 592 1.1× 366 1.2× 298 1.1× 232 0.8× 102 1.2× 17 611
Michael Grill Germany 12 408 0.7× 274 0.9× 199 0.7× 95 0.3× 58 0.7× 71 463
Franz Chmela United States 9 428 0.8× 265 0.9× 224 0.8× 154 0.6× 42 0.5× 28 448
Giulio Cazzoli Italy 12 279 0.5× 196 0.7× 116 0.4× 101 0.4× 57 0.7× 39 360
P. Pelloni Italy 15 386 0.7× 278 0.9× 160 0.6× 131 0.5× 38 0.5× 26 517
G. H. Abd Alla Egypt 7 490 0.9× 206 0.7× 275 1.0× 309 1.1× 75 0.9× 12 519
Glenn R. Bower United States 9 477 0.9× 275 0.9× 231 0.8× 269 1.0× 87 1.1× 27 581
Daisuke Kawano Japan 13 349 0.6× 241 0.8× 178 0.6× 236 0.9× 67 0.8× 32 510
Takuji ISHIYAMA Japan 15 633 1.1× 358 1.2× 282 1.0× 306 1.1× 124 1.5× 91 662
Kihyun Kim South Korea 9 355 0.6× 243 0.8× 133 0.5× 182 0.7× 46 0.6× 19 390

Countries citing papers authored by David D. Wickman

Since Specialization
Citations

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

Fields of papers citing papers by David D. Wickman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David D. Wickman. 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 David D. Wickman. The network helps show where David D. Wickman may publish in the future.

Co-authorship network of co-authors of David D. Wickman

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

All Works

18 of 18 papers shown
1.
2.
Wickman, David D. & Sage Kokjohn. (2018). A Computational investigation of the potential for non-sooting fuels to enable ultra-low NOx and CO2 emissions. Fuel. 216. 648–664. 2 indexed citations
3.
Dascanio, John J., et al.. (2017). Development and Student Evaluation of an Anatomically Correct High-Fidelity Calf Leg Model. Journal of Veterinary Medical Education. 45(1). 126–130. 4 indexed citations
4.
Sobiesiak, Andrzej, et al.. (2015). Combustion Simulation of Dual Fuel CNG Engine Using Direct Injection of Natural Gas and Diesel. SAE International Journal of Engines. 8(2). 846–858. 39 indexed citations
5.
Bergin, Michael, David D. Wickman, Christopher J. Rutland, & Rolf D. Reitz. (2015). Multi-Dimensional-Modeling-Based Development of a Novel 2-Zone Combustion Chamber Applied to Reactivity Controlled Compression Ignition Combustion. SAE International Journal of Engines. 8(2). 808–820. 2 indexed citations
6.
Sobiesiak, Andrzej, et al.. (2014). Computational Study of Reactivity Controlled Compression Ignition (RCCI) Combustion in a Heavy-Duty Diesel Engine Using Natural Gas. SAE technical papers on CD-ROM/SAE technical paper series. 1. 36 indexed citations
7.
Zhang, Yu, et al.. (2013). Development of Dual-Fuel Low Temperature Combustion Strategy in a Multi-Cylinder Heavy-Duty Compression Ignition Engine Using Conventional and Alternative Fuels. SAE International Journal of Engines. 6(3). 1481–1489. 46 indexed citations
8.
Zhang, Yu, William De Ojeda, & David D. Wickman. (2012). Computational Study of Combustion Optimization in a Heavy-Duty Diesel Engine Using In-Cylinder Blending of Gasoline and Diesel Fuels. SAE technical papers on CD-ROM/SAE technical paper series. 15 indexed citations
9.
Ge, Haiwen, Yu Shi, Rolf D. Reitz, David D. Wickman, & Werner Willems. (2010). Engine Development Using Multi-dimensional CFD and Computer Optimization. SAE technical papers on CD-ROM/SAE technical paper series. 27 indexed citations
10.
Ge, Haiwen, et al.. (2009). Heavy-Duty Diesel Combustion Optimization Using Multi-Objective Genetic Algorithm and Multi-Dimensional Modeling. SAE technical papers on CD-ROM/SAE technical paper series. 1. 30 indexed citations
11.
Ge, Haiwen, Yu Shi, Rolf D. Reitz, David D. Wickman, & Werner Willems. (2009). Optimization of a HSDI Diesel Engine for Passenger Cars Using a Multi-Objective Genetic Algorithm and Multi-Dimensional Modeling. SAE International Journal of Engines. 2(1). 691–713. 32 indexed citations
12.
Singh, Satbir, et al.. (2007). Development of a Hybrid, Auto-Ignition/Flame-Propagation Model and Validation Against Engine Experiments and Flame Liftoff. SAE technical papers on CD-ROM/SAE technical paper series. 1. 23 indexed citations
13.
Genzale, Caroline L., Rolf D. Reitz, & David D. Wickman. (2007). A Computational Investigation into the Effects of Spray Targeting, Bowl Geometry and Swirl Ratio for Low-Temperature Combustion in a Heavy-Duty Diesel Engine. SAE technical papers on CD-ROM/SAE technical paper series. 1. 45 indexed citations
14.
Wickman, David D., Hanho Yun, & Rolf D. Reitz. (2003). Split-Spray Piston Geometry Optimized for HSDI Diesel Engine Combustion. SAE technical papers on CD-ROM/SAE technical paper series. 1. 36 indexed citations
15.
Wickman, David D., P. K. Senecal, & Rolf D. Reitz. (2001). Diesel Engine Combustion Chamber Geometry Optimization Using Genetic Algorithms and Multi-Dimensional Spray and Combustion Modeling. SAE technical papers on CD-ROM/SAE technical paper series. 1. 142 indexed citations
16.
Wickman, David D., et al.. (2000). Methods and Results from the Development of a 2600 Bar Diesel Fuel Injection System. SAE technical papers on CD-ROM/SAE technical paper series. 28 indexed citations
17.
Wickman, David D., et al.. (1999). The Influence of Boost Pressure on Emissions and Fuel Consumption of a Heavy-Duty Single-Cylinder D.I. Diesel Engine. SAE technical papers on CD-ROM/SAE technical paper series. 1. 60 indexed citations
18.
Beck, N., et al.. (1998). An Evaluation of Common Rail, Hydraulically Intensified Diesel Fuel Injection System Concepts and Rate Shapes. SAE technical papers on CD-ROM/SAE technical paper series. 1. 10 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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