World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
43
Citations
7182
World Ranking
1721
National Ranking
59

Norbert Huber 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 Norbert Huber 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: 158 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Norbert Huber 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 Norbert Huber 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: 43 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Norbert Huber is affiliated with Hamburg University of Technology in Germany. Their research focuses primarily on materials science and engineering, with a significant emphasis on materials chemistry and mechanical engineering subfields.

Their scholarly work covers multiple specialized areas, including:

  • Nanoporous metals and alloys
  • Anodic oxide films and nanostructures
  • Electrocatalysts for energy conversion
  • Surface treatment and residual stress
  • Metal forming simulation techniques
  • Nuclear materials and radiation effects
  • Welding techniques and residual stresses

Norbert Huber has published extensively, contributing to various academic journals and venues. Their frequent publication outlets include:

  • MRS Advances
  • Materials
  • Journal of materials research/Pratt's guide to venture capital sources
  • Computational Materials Science
  • Fatigue & Fracture of Engineering Materials & Structures

Representative recent papers authored or coauthored by Norbert Huber include:

  • "A Review of Non-Destructive Testing (NDT) Techniques for Defect Detection: Application to Fusion Welding and Future Wire Arc Additive Manufacturing Processes," 2022, Materials
  • "A Review of Experimentally Informed Micromechanical Modeling of Nanoporous Metals: From Structural Descriptors to Predictive Structure-Property Relationships," 2020, Materials
  • "Hybrid Modelling by Machine Learning Corrections of Analytical Model Predictions towards High-Fidelity Simulation Solutions," 2021, Materials
  • "Editorial: Machine Learning and Data Mining in Materials Science," 2020, Frontiers in Materials
  • "Prediction of elastic-plastic deformation of nanoporous metals by FEM beam modeling: A bottom-up approach from ligaments to real microstructures," 2020, Materials Science and Engineering A

The researcher collaborates regularly with several frequent coauthors, among them:

  • Claudia Richert
  • Meenakshi Dutt
  • Marian Kennedy
  • Praveen Kumar
  • John S. McCloy

Their contributions integrate advanced experimental, computational, and machine learning approaches to explore and model the behavior and properties of materials at microstructural and nanoscale levels.

Best Publications

  • Experimental analysis and modelling of particle-wall collisions

    M Sommerfeld;N Huber

  • A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics

    Frederic E. Bock;Roland C. Aydin;Christian J. Cyron;Christian J. Cyron;Norbert Huber;Norbert Huber

  • On the feasibility of friction spot joining in magnesium/fiber-reinforced polymer composite hybrid structures

    S.T. Amancio-Filho;C. Bueno;J.F. dos Santos;N. Huber

  • Modelling and numerical calculation of dilute-phase pneumatic conveying in pipe systems

    N. Huber;M. Sommerfeld

  • Finite deformation viscoelasticity laws

    N. Huber;C. Tsakmakis

  • Finite element based simulation of dry sliding wear

    V Hegadekatte;N Huber;O Kraft

  • The influence of refill FSSW parameters on the microstructure and shear strength of 5042 aluminium welds

    M.D. Tier;T.S. Rosendo;J.F. dos Santos;N. Huber

  • On the effect of a general residual stress state on indentation and hardness testing

    N. Huber;J. Heerens

  • Determination of constitutive properties fromspherical indentation data using neural networks. Part i:the case of pure kinematic hardening in plasticity laws

    N. Huber;Ch. Tsakmakis

  • Scaling laws of nanoporous metals under uniaxial compression

    Norbert Huber;R. N. Viswanath;Nadiia Mameka;Jürgen Markmann

  • Determination of constitutive properties fromspherical indentation data using neural networks. Part ii:plasticity with nonlinear isotropic and kinematichardening

    N. Huber;Ch. Tsakmakis

  • Effects of tool rotational and welding speed on microstructure and mechanical properties of bobbin-tool friction-stir welded Mg AZ31

    W.Y. Li;T. Fu;L. Hütsch;J. Hilgert

  • Characterization of the cross-sectional particle concentration distribution in pneumatic conveying systems

    N. Huber;M. Sommerfeld

  • Identification of elastic-plastic material parameters from pyramidal indentation of thin films

    N. Huber;W. D. Nix;H. Gao

  • A predictive modeling scheme for wear in tribometers

    V. Hegadekatte;S. Kurzenhäuser;N. Huber;O. Kraft

  • Asymmetric mechanical properties and tensile behaviour prediction of aluminium alloy 5083 friction stir welding joints

    D. Rao;K. Huber;J. Heerens;J.F. dos Santos

  • Neutrons and Synchrotron Radiation in Engineering Materials Science

    Peter Staron;Torben Fischer;Thomas Lippmann;Andreas Stark

  • Thermal models for bobbin tool friction stir welding

    J. Hilgert;H.N.B. Schmidt;J.F. dos Santos;N. Huber

  • Spherical indentation into elastoplastic materials: Indentation-response based definitions of the representative strain

    Yanping Cao;Xiuqing Qian;Xiuqing Qian;Norbert Huber

  • A neural network tool for identifying the material parameters of a finite deformation viscoplasticity model with static recovery

    N. Huber;Ch. Tsakmakis

Frequent Co-Authors

Oliver Kraft
Oliver Kraft Karlsruhe Institute of Technology
Norbert Schell
Norbert Schell Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research
Gerold A. Schneider
Gerold A. Schneider Hamburg University of Technology
Karl Ulrich Kainer
Karl Ulrich Kainer Hamburg University of Technology
Surya R. Kalidindi
Surya R. Kalidindi Georgia Institute of Technology
Helmut Clemens
Helmut Clemens University of Leoben
Michael V. Swain
Michael V. Swain University of Sydney
Volker Abetz
Volker Abetz Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research
Jörg Weissmüller
Jörg Weissmüller Hamburg University of Technology
Thomas Klassen
Thomas Klassen Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research

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