World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
35
Citations
5196
World Ranking
2643
National Ranking
324

Jian-Chun 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 Jian-Chun 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: 204 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

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

Jian-Chun 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 Jian-Chun 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: 35 D-Index — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Best Publications

  • Size-dependent effective elastic constants of solids containing nano-inhomogeneities with interface stress

    H. L. Duan;J. Wang;Z. P. Huang;Bhushan Lal Karihaloo

  • Eshelby formalism for nano-inhomogeneities

    Huiling Duan;J. Wang;Z. P. Huang;Bhushan Lal Karihaloo

  • Reynolds-stress-constrained large-eddy simulation of wall-bounded turbulent flows

    Shiyi Chen;Zhenhua Xia;Suyang Pei;Jianchun Wang

  • A hybrid numerical simulation of isotropic compressible turbulence

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

  • Prediction of the overall moduli of layered silicate-reinforced nanocomposites—part I: basic theory and formulas

    Unknown

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

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

  • Effective conductivities of heterogeneous media containing multiple inclusions with various spatial distributions

    H. L. Duan;H. L. Duan;Bhushan Lal Karihaloo;J. Wang;X. Yi

  • Modeling subgrid-scale forces by spatial artificial neural networks in large eddy simulation of turbulence

    Chenyue Xie;Jianchun Wang;Weinan E

  • Cascade of kinetic energy in three-dimensional compressible turbulence.

    Jianchun Wang;Yantao Yang;Yipeng Shi;Zuoli Xiao

  • Kinetic energy transfer in compressible isotropic turbulence

    Jianchun Wang;Minping Wan;Song Chen;Shiyi Chen

  • Effect of shocklets on the velocity gradients in highly compressible isotropic turbulence

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

  • Artificial neural network-based nonlinear algebraic models for large eddy simulation of turbulence

    Unknown

  • Deconvolutional artificial neural network models for large eddy simulation of turbulence

    Unknown

  • Artificial neural network approach to large-eddy simulation of compressible isotropic turbulence

    Unknown

  • Spectra and statistics in compressible isotropic turbulence

    Unknown

  • Scaling and statistics in three-dimensional compressible turbulence.

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

  • Modeling subgrid-scale force and divergence of heat flux of compressible isotropic turbulence by artificial neural network

    Unknown

  • Fourier neural operator approach to large eddy simulation of three-dimensional turbulence

    Unknown

  • Attention-enhanced neural network models for turbulence simulation

    Unknown

  • Long-term predictions of turbulence by implicit U-Net enhanced Fourier neural operator

    Unknown

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