World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
54
Citations
9765
World Ranking
3246
National Ranking
960

Paul Fleming publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Paul Fleming sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 155 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Paul Fleming D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Paul Fleming sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 54 D-Index — 68th percentile

68% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Paul Fleming is affiliated with the National Renewable Energy Laboratory in the United States. Their research primarily focuses on wind energy, specifically in areas related to wind turbine control systems and aerodynamics.

The main fields of study in their work include:

  • Engineering
  • Environmental Science

Within these fields, Paul Fleming's work specializes in subfields such as:

  • Aerospace Engineering
  • Environmental Engineering
  • Electrical and Electronic Engineering
  • Computational Mechanics
  • Artificial Intelligence

The primary topics covered in their research publications consist of:

  • Wind Energy Research and Development
  • Wind and Air Flow Studies
  • Wind Turbine Control Systems
  • Aerodynamics and Fluid Dynamics Research
  • Fluid Dynamics and Vibration Analysis
  • Energy Load and Power Forecasting
  • Solar Radiation and Photovoltaics

Paul Fleming has coauthored extensively with several researchers, including:

  • Eric Simley
  • Jennifer King
  • Christopher J. Bay
  • Rafael Mudafort
  • Luis A. Martínez-Tossas

Their recent scholarly articles include:

  • "Wind farm flow control: prospects and challenges" (2022, Wind energy science)
  • "Control-oriented model for secondary effects of wake steering" (2021, Wind energy science)
  • "Continued results from a field campaign of wake steering applied at a commercial wind farm - Part 2" (2020, Wind energy science)
  • "Design and analysis of a wake steering controller with wind direction variability" (2020, Wind energy science)
  • "Results from a wake-steering experiment at a commercial wind plant: investigating the wind speed dependence of wake-steering performance" (2021, Wind energy science)

They have contributed to different publication venues, with the most frequent being:

  • Wind energy science
  • Journal of Physics Conference Series
  • Journal of Renewable and Sustainable Energy
  • Energies
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)

Paul Fleming has also published a book titled Exemplarity and Mediocrity (2020) under Stanford University Press eBooks.

Best Publications

  • Wind plant power optimization through yaw control using a parametric model for wake effects—a CFD simulation study

    P. M. O. Gebraad;F. W. Teeuwisse;J. W. van Wingerden;Paul A. Fleming

  • Evaluating techniques for redirecting turbine wakes using SOWFA

    Paul A. Fleming;Pieter M.O. Gebraad;Sang Lee;Jan-Willem van Wingerden

  • Simulation comparison of wake mitigation control strategies for a two-turbine case

    Paul Fleming;Pieter M.O. Gebraad;Sang Lee;Jan-Willem van Wingerden

  • A tutorial of wind turbine control for supporting grid frequency through active power control

    Jacob Aho;Andrew Buckspan;Jason Laks;Paul Fleming

  • Field test of wake steering at an offshore wind farm

    Paul Fleming;Jennifer Annoni;Jigar J. Shah;Linpeng Wang

  • Maximization of the annual energy production of wind power plants by optimization of layout and yaw‐based wake control

    Pieter Gebraad;Jared J. Thomas;Andrew Ning;Paul Fleming

  • Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1

    Paul Fleming;Jennifer King;Katherine Dykes;Eric Simley

  • Wind plant system engineering through optimization of layout and yaw control

    Paul A. Fleming;Andrew Ning;Pieter M. O. Gebraad;Katherine Dykes

  • Wind farm flow control: prospects and challenges

    Unknown

  • Analysis of axial‐induction‐based wind plant control using an engineering and a high‐order wind plant model

    Jennifer Annoni;Pieter M. O. Gebraad;Andrew K. Scholbrock;Paul A. Fleming

  • A tutorial on control-oriented modeling and control of wind farms

    S. Boersma;B.M. Doekemeijer;P.M.O. Gebraad;P.A. Fleming

  • Use of SCADA Data for Failure Detection in Wind Turbines

    Kyusung Kim;Girija Parthasarathy;Onder Uluyol;Wendy Foslien

  • The aerodynamics of the curled wake: a simplified model in view of flow control

    Luis A. Martínez-Tossas;Jennifer Annoni;Paul A. Fleming;Matthew J. Churchfield

  • Active Power Controls from Wind Power: Bridging the Gaps

    E. Ela;V. Gevorgian;P. Fleming;Y. C. Zhang

  • Using machine learning to predict wind turbine power output

    a Clifton;L Kilcher;Julie K Lundquist;Julie K Lundquist;P Fleming

  • Analysis of control-oriented wake modeling tools using lidar field results

    Jennifer Annoni;Paul Fleming;Andrew Scholbrock;Jason Roadman

  • Assessment of wind turbine component loads under yaw-offset conditions

    Rick Damiani;Scott Dana;Jennifer Annoni;Paul Fleming

  • A data-driven model for wind plant power optimization by yaw control

    P. M. O. Gebraad;F. W. Teeuwisse;J. W. van Wingerden;P. A. Fleming

  • A simulation study demonstrating the importance of large-scale trailing vortices in wake steering

    Paul Fleming;Jennifer Annoni;Matthew Churchfield;Luis A. Martinez-Tossas

  • Field-test results using a nacelle-mounted lidar for improving wind turbine power capture by reducing yaw misalignment

    P A Fleming;A K Scholbrock;A Jehu;S Davoust

  • Control-oriented model for secondary effects of wake steering

    Jennifer King;Paul Fleming;Ryan King;Luis A. Martínez-Tossas

  • Validation of Individual Pitch Control by Field Tests on Two- and Three-Bladed Wind Turbines

    E. A. Bossanyi;P. A. Fleming;A. D. Wright

  • High-fidelity simulation comparison of wake mitigation control strategies for a two-turbine case

    P. Fleming;P. Gebraad;S. Lee;K. Johnson

Frequent Co-Authors

Lucy Y. Pao
Lucy Y. Pao University of Colorado Boulder
Patrick Moriarty
Patrick Moriarty National Renewable Energy Laboratory
David Schlipf
David Schlipf Flensburg University of Applied Sciences
Jan-Willem van Wingerden
Jan-Willem van Wingerden Delft University of Technology
Matthew J. Churchfield
Matthew J. Churchfield National Renewable Energy Laboratory
Julie K. Lundquist
Julie K. Lundquist University of Colorado Boulder
Andrew Ning
Andrew Ning Brigham Young University
Carlo L. Bottasso
Carlo L. Bottasso Technical University of Munich
Fernando Porté-Agel
Fernando Porté-Agel École Polytechnique Fédérale de Lausanne
Philippe R. Spalart
Philippe R. Spalart Boeing (United States)

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