World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
55
Citations
10858
World Ranking
907
National Ranking
112

Lian-Ping Wang publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Lian-Ping Wang sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 265 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Lian-Ping Wang D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Lian-Ping Wang sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 55 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Research.com Recognitions

  • 2016 - Fellow of the American Society of Mechanical Engineers

Overview

Lian-Ping Wang is affiliated with the Southern University of Science and Technology in China. Their research spans numerous areas within engineering, with a significant focus on computational mechanics, ocean engineering, biomedical engineering, electrical and electronic engineering, and applied mathematics. The scientist's work primarily addresses topics related to fluid dynamics and turbulence, particle dynamics in fluid flows, and lattice Boltzmann simulation studies.

The main topics covered in their research include:

  • Lattice Boltzmann Simulation Studies
  • Fluid Dynamics and Turbulent Flows
  • Particle Dynamics in Fluid Flows
  • Aerosol Filtration and Electrostatic Precipitation
  • Gas Dynamics and Kinetic Theory
  • Fluid Dynamics and Vibration Analysis
  • Fluid Dynamics and Heat Transfer

Frequent coauthors collaborating with Lian-Ping Wang have included Cheng Peng, Zhaoli Guo, Tao Chen, Shiyi Chen, and Hua Zhang.

The scientist's recent published papers encompass a range of topics and publication venues. Selected works include:

  • "Estimation of the dissipation rate of turbulent kinetic energy: A review," 2020, Chemical Engineering Science
  • "A magnetic field coupling fractional step lattice Boltzmann model for the complex interfacial behavior in magnetic multiphase flows," 2022, Applied Mathematical Modelling
  • "A Comprehensive Review on Multi-Dimensional Heat Conduction of Multi-Layer and Composite Structures: Analytical Solutions," 2021, Journal of Thermal Science
  • "Is Hadley Cell Expanding?", 2021, Atmosphere
  • "Effect of self-assembly on fluorescence in magnetic multiphase flows and its application on the novel detection for COVID-19," 2021, Physics of Fluids

Lian-Ping Wang's research outputs have appeared repeatedly in several publication venues, notably:

  • Physics of Fluids
  • SSRN Electronic Journal
  • arXiv (Cornell University)
  • Journal of Fluid Mechanics
  • International Journal of Multiphase Flow

Their main field of study is engineering, supported by extensive contributions in subfields such as computational mechanics and ocean engineering. The volume of publications in these areas reflects a sustained research focus and contribution over time.

Among awards, Lian-Ping Wang was recognized as a Fellow of the American Society of Mechanical Engineers in 2016, indicating a professional standing within the mechanical engineering community.

Best Publications

  • Settling velocity and concentration distribution of heavy particles in homogeneous isotropic turbulence

    Lian-Ping Wang;Martin R. Maxey

  • Growth of Cloud Droplets in a Turbulent Environment

    Wojciech W. Grabowski;Lian Ping Wang

  • Statistical mechanical description and modelling of turbulent collision of inertial particles

    Lian-Ping Wang;Anthony S. Wexler;Yong Zhou

  • Droplet growth in warm turbulent clouds

    B. J. Devenish;P. Bartello;J.-L. Brenguier;L. R. Collins

  • Examination of hypotheses in the Kolmogorov refined turbulence theory through high-resolution simulations. Part 1. Velocity field

    Lian-Ping Wang;Shiyi Chen;James G. Brasseur;John C. Wyngaard

  • Dispersion of heavy particles by turbulent motion

    Lian-Ping Wang;Davd E. Stock

  • Effects of Turbulence on the Geometric Collision Rate of Sedimenting Droplets. Part 1. Results From Direct Numerical Simulation

    Orlando Ayala;Bogdan Rosa;Lian-Ping Wang;Wojciech W Grabowski

  • Retention and Transport of Silica Nanoparticles in Saturated Porous Media: Effect of Concentration and Particle Size

    Chao Wang;Aparna Devi Bobba;Ramesh Attinti;Chongyang Shen

  • Simulations of dispersed turbulent multiphase flow

    M.R. Maxey;B.K. Patel;E.J. Chang;L.-P. Wang

  • Modelling turbulent collision of bidisperse inertial particles

    Yong Zhou;Anthony S. Wexler;Lian-Ping Wang

  • On the collision rate of small particles in isotropic turbulence. II. Finite inertia case

    Lian Ping Wang;Anthony S. Wexler;Yong Zhou

  • Effects of turbulence on the geometric collision rate of sedimenting droplets. Part 2. Theory and parameterization

    Orlando Ayala;Bogdan Rosa;Lian-Ping Wang

  • A hybrid numerical simulation of isotropic compressible turbulence

    J. Wang;L. P. Wang;Z. Xiao;Y. Shi

  • Theoretical Formulation of Collision Rate and Collision Efficiency of Hydrodynamically Interacting Cloud Droplets in Turbulent Atmosphere

    Lian-Ping Wang;Orlando Ayala;Scott E. Kasprzak;Wojciech W. Grabowski

  • Lattice Boltzmann simulation of turbulent flow laden with finite-size particles

    Hui Gao;Hui Li;Lian-Ping Wang

  • Effect of compressibility on the small-scale structures in isotropic turbulence

    Jianchun Wang;Yipeng Shi;Lian-Ping Wang;Zuoli Xiao

  • Estimation of the dissipation rate of turbulent kinetic energy: A review

    Guichao Wang;Fan Yang;Ke Wu;Yongfeng Ma

  • STATISTICAL MECHANICAL DESCRIPTIONS OF TURBULENT COAGULATION

    Lian Ping Wang;Anthony S. Wexler;Yong Zhou

  • Growth of Cloud Droplets by Turbulent Collision–Coalescence

    Yan Xue;Lian-Ping Wang;Wojciech W. Grabowski

  • Turbulent collision efficiency of heavy particles relevant to cloud droplets

    Lian-Ping Wang;Orlando Ayala;Bogdan Rosa;Wojciech W Grabowski

  • Effects of subgrid-scale modeling on time correlations in large eddy simulation

    Guo-Wei He;R. Rubinstein;Lian-Ping Wang

  • Statistical Mechanical Description and Modeling of Turbulent Collision of Inertial Particles

    Yong Zhou;Anthony Wexler;Lian-Ping Wang

Frequent Co-Authors

Wojciech W. Grabowski
Wojciech W. Grabowski National Center for Atmospheric Research
Shiyi Chen
Shiyi Chen Southern University of Science and Technology
Zhaoli Guo
Zhaoli Guo Huazhong University of Science and Technology
Martin R. Maxey
Martin R. Maxey Brown University
Minping Wan
Minping Wan Southern University of Science and Technology
Anthony S. Wexler
Anthony S. Wexler University of California, Davis
Lance R. Collins
Lance R. Collins Cornell University
Li-Shi Luo
Li-Shi Luo Old Dominion University
Chandra Kambhamettu
Chandra Kambhamettu University of Delaware
Bingqing Wei
Bingqing Wei University of Delaware

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