D J Nicklin

496 citations
8 papers · 383 · h-index 5

Impact in

    • Reservoir Engineering and Simulation Methods
    • Granular flow and fluidized beds
    • Cyclone Separators and Fluid Dynamics
    • Fluid Dynamics and Heat Transfer

Papers in

    • Fluid Dynamics and Heat Transfer 2
    • Granular flow and fluidized beds 2
    • Fluid Dynamics and Thin Films 1
    • Mineral Processing and Grinding 2
    • Iron and Steelmaking Processes 1
    • Hydraulic and Pneumatic Systems 1

D J Nicklin

7 papers receiving 366 citations

Peers

D J Nicklin
Comparison fields: 5 of 42
  • Ocean Engineering 125
  • Computational Mechanics 149
  • Biomedical Engineering 278
  • Water Science and Technology 85
  • Mechanical Engineering 153
Replace E. S. Gaddis with:
E. S. Gaddis Germany
E. J. Greskovich United States
J. Reese United States
D. Kunii Japan
F.A. Zenz United States
Xukun Luo United States
Craig A. McKnight Canada
Sujatha Degaleesan United States
Manish R. Bhole India
Jingdai Wang China
D J Nicklin relative to E. S. Gaddis Germany E. S. Gaddis's profile →
Citations per field
00.5×2.7×
E. S. Gaddis · 1×
Citations per year

Countries citing papers authored by D J Nicklin

Since Specialization
Citations

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

Fields of papers citing papers by D J Nicklin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 5 scholars most cited alongside D J Nicklin, 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 D J Nicklin Line = papers co-authored together D J Nicklin links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 1962258
2
The Air-Lift Pump : Theory and Optimization
196353
3 197227
4 197420
5 198620
6 19934
7 19761
8
THE OPTIMUM USE OF A BARREL OF OIL
19810

About D J Nicklin

D J Nicklin is a scholar working on Computational Mechanics, Mechanical Engineering, Control and Systems Engineering, Mechanics of Materials and Ocean Engineering, having authored 8 papers that have together received 383 indexed citations. Recurring topics across this work include Fluid Dynamics and Heat Transfer (2 papers), Granular flow and fluidized beds (2 papers), Mineral Processing and Grinding (2 papers), Iron and Steelmaking Processes (1 paper), Energy, Environment, and Transportation Policies (1 paper), Fluid Dynamics and Thin Films (1 paper), Advanced Control Systems Optimization (1 paper) and Hydraulic and Pneumatic Systems (1 paper). The work is most often cited by research in Ocean Engineering (125 citations), Computational Mechanics (149 citations), Biomedical Engineering (278 citations), Water Science and Technology (85 citations) and Mechanical Engineering (153 citations). D J Nicklin has collaborated with scholars based in Australia and United Kingdom. Frequent co-authors include L. S. Leung, Peter C. Brooks, Victor Rudolph, Yinghe He and P. F. Greenfield. Their work appears in journals such as Chemical Engineering Science, The Canadian Journal of Chemical Engineering, Powder Technology, Fuel and Industrial & Engineering Chemistry Fundamentals.

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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