World's Best Scientists 2026 revealed!
Richard D. Sandberg

Richard D. Sandberg

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
7464
World Ranking
6163
National Ranking
326

Richard D. Sandberg 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 Richard D. Sandberg 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: 418 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Richard D. Sandberg 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 Richard D. Sandberg 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: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

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

Overview

Richard D. Sandberg is affiliated with the University of Melbourne in Australia and has contributed extensively to the field of engineering, with a particular focus on computational mechanics and aerospace engineering. Their research spans multiple subfields including mechanical engineering, statistical and nonlinear physics, and environmental engineering.

The primary topics covered in their research include:

  • Fluid Dynamics and Turbulent Flows
  • Heat Transfer Mechanisms
  • Turbomachinery Performance and Optimization
  • Aerodynamics and Acoustics in Jet Flows
  • Model Reduction and Neural Networks
  • Wind and Air Flow Studies
  • Computational Fluid Dynamics and Aerodynamics

Their publication record includes papers in leading journals and venues such as the Journal of Turbomachinery, International Journal of Heat and Fluid Flow, Journal of Fluid Mechanics, arXiv (Cornell University), and Journal of Sound and Vibration. They have published 22 papers in the Journal of Turbomachinery alone, reflecting a significant engagement with this area.

Recent notable papers authored or co-authored by Richard D. Sandberg include:

  • Fluid Dynamics of Axial Turbomachinery: Blade- and Stage-Level Simulations and Models, 2021, Annual Review of Fluid Mechanics
  • RANS turbulence model development using CFD-driven machine learning, 2020, Journal of Computational Physics
  • Studying turbulent flows with physics-informed neural networks and sparse data, 2023, International Journal of Heat and Fluid Flow
  • Multi-objective CFD-driven development of coupled turbulence closure models, 2021, Journal of Computational Physics
  • Application of Gene Expression Programming to a-posteriori LES modeling of a Taylor Green Vortex, 2020, Journal of Computational Physics

Frequent collaborators in their research include Yaomin Zhao, Andrew Ooi, Melissa Kožul, Koichi Tanimoto, and Chitrarth Lav. Collaboration counts are highest with Yaomin Zhao and Andrew Ooi, each with 18 joint publications.

Best Publications

  • Direct numerical simulations of forced and unforced separation bubbles on an airfoil at incidence

    L. E. Jones;R. D. Sandberg;N. D. Sandham

  • A novel evolutionary algorithm applied to algebraic modifications of the RANS stress-strain relationship

    Jack Weatheritt;Richard Sandberg

  • RANS turbulence model development using CFD-driven machine learning

    Yaomin Zhao;Harshal D. Akolekar;Jack Weatheritt;Vittorio Michelassi

  • Stability and receptivity characteristics of a laminar separation bubble on an aerofoil

    L. E. Jones;R. D. Sandberg;N. D. Sandham

  • Acoustic and hydrodynamic analysis of the flow around an aerofoil with trailing-edge serrations

    L. E. Jones;R. D. Sandberg

  • The development of algebraic stress models using a novel evolutionary algorithm

    J. Weatheritt;R.D. Sandberg

  • Nonreflecting Zonal Characteristic Boundary Condition for Direct Numerical Simulation of Aerodynamic Sound

    Richard D. Sandberg;Neil D. Sandham

  • Temperature and pressure dependence of resonance in multi-layer microcantilevers

    Rasmus Kousholt Sandberg;Winnie Edith Svendsen;Kristian Mølhave;Anja Boisen

  • Effect of gold coating on the Q-factor of a resonant cantilever

    Rasmus Kousholt Sandberg;Kristian Mølhave;Anja Boisen;Winnie Edith Svendsen

  • Compressible Direct Numerical Simulation of Low-Pressure Turbines—Part II: Effect of Inflow Disturbances

    Vittorio Michelassi;Li-Wei Chen;Richard Pichler;Richard D. Sandberg

  • Direct Numerical Simulations of a High-Pressure Turbine Vane

    Andrew P S Wheeler;Richard D. Sandberg;Neil Sandham;Richard Pichler

  • Compressible direct numerical simulation of low-pressure turbines: part I - methodology

    Richard D. Sandberg;Vittorio Michelassi;Richard Pichler;Liwei Chen

  • Direct numerical simulation of turbulent flow past a trailing edge and the associated noise generation

    Richard D. Sandberg;Neil D. Sandham

  • Numerical analysis of tonal airfoil self-noise and acoustic feedback-loops

    Lloyd E. Jones;Richard D. Sandberg

  • Direct numerical simulation of the early development of a turbulent mixing layer downstream of a splitter plate

    Neil D. Sandham;Richard D. Sandberg

  • Direct numerical simulations of low Reynolds number flow over airfoils with trailing-edge serrations☆

    R.D. Sandberg;L.E. Jones

  • Fluid Dynamics of Axial Turbomachinery: Blade- and Stage-Level Simulations and Models

    Richard D. Sandberg;Vittorio Michelassi

  • Direct numerical simulations of tonal noise generated by laminar flow past airfoils

    R.D. Sandberg;L.E. Jones;N.D. Sandham;P.F. Joseph

  • Efficient parallel computing with a compact finite difference scheme

    Jae Wook Kim;Richard D. Sandberg

  • A Methodology for Simulating Compressible Turbulent Flows

    Hermann F. Fasel;Dominic A. von Terzi;Richard D. Sandberg

  • Numerical investigation of transitional supersonic axisymmetric wakes

    Richard D. Sandberg;Hermann F. Fasel

  • DNS of compressible pipe flow exiting into a coflow

    Richard D. Sandberg;Neil D. Sandham;Victoria Suponitsky

  • A primer on direct numerical simulation of turbulence - methods, procedures and guidelines

    Gary N. Coleman;Richard D. Sandberg

  • The boundary data immersion method for compressible flows with application to aeroacoustics

    Stefan C. Schlanderer;Gabriel D. Weymouth;Richard D. Sandberg

  • Direct numerical simulations of trailing edge noise generated by boundary-layer instabilities

    R.D. Sandberg;N.D. Sandham;P.F. Joseph

  • Tandem cylinder flow and noise predictions using a hybrid RANS/LES approach

    M. Weinmann;R.D. Sandberg;C. Doolan

Frequent Co-Authors

Neil D. Sandham
Neil D. Sandham University of Southampton
Hermann F. Fasel
Hermann F. Fasel University of Arizona
Andrew Ooi
Andrew Ooi University of Melbourne
Eric Rogers
Eric Rogers University of Southampton
Stéphane Moreau
Stéphane Moreau Université de Sherbrooke
Nicholas Hutchins
Nicholas Hutchins University of Melbourne
Julio Soria
Julio Soria Monash University
Liwei Chen
Liwei Chen Shanghai Jiao Tong University
Phillip Joseph
Phillip Joseph University of Southampton
Kemal Hanjalic
Kemal Hanjalic University of Sarajevo

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

The field of Engineering and Technology is rapidly evolving, with innovative careers now emerging across sectors like financial technology, urban development, and sports management. Many top U.S. universities now offer flexible online programs that accommodate busy schedules and diverse interests.

If you’re passionate about emerging financial systems, consider a blockchain degree. These programs explore cryptocurrencies, blockchain technology, and fintech innovation—key areas shaping global finance and secure transactions.

Sports enthusiasts who want to combine management skills with a love for athletics may benefit from sports management programs online. These degrees blend business principles with sport-specific knowledge to launch careers in sports marketing, operations, and administration.

For those interested in creating smart cities and sustainable spaces, pursuing one of the cheapest online masters in urban planning can open doors to impactful roles in city planning and development.

Looking for fast-track options? There are accredited 6 month masters degree online choices. These accelerated programs help professionals quickly upgrade their skills and advance in booming technology sectors.

Best Scientists Citing Richard D. Sandberg

Trending Scientists

Recently Published Articles