World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
4831
World Ranking
6344
National Ranking
127

Rolf Dollevoet 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 Rolf Dollevoet sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 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: 117 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: 59 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: 159 publications — 31st percentile

31% of scientists in this discipline score the same or lower.

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

Rolf Dollevoet 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 Rolf Dollevoet sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 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: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 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: 94 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: 24 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

Rolf Dollevoet is affiliated with Delft University of Technology in the Netherlands and specializes in the field of engineering. Their research primarily covers mechanical engineering, mechanics of materials, and civil and structural engineering, with additional work in statistical and nonlinear physics and industrial and manufacturing engineering.

The main topics of Rolf Dollevoet's research include:

  • Railway Engineering and Dynamics
  • Mechanical stress and fatigue analysis
  • Model Reduction and Neural Networks
  • Adhesion, Friction, and Surface Interactions
  • Structural Health Monitoring Techniques
  • Railway Systems and Energy Efficiency
  • Geotechnical Engineering and Underground Structures

Their frequently published research appears in venues such as:

  • arXiv (Cornell University)
  • Mechanical Systems and Signal Processing
  • International Journal of Rail Transportation
  • Tribology International
  • IEEE Transactions on Industrial Informatics

Rolf Dollevoet has contributed to several recent papers including:

  • Physics-Informed Neural Networks for Solving Forward and Inverse Problems in Complex Beam Systems, 2023, IEEE Transactions on Neural Networks and Learning Systems
  • Fast and robust identification of railway track stiffness from simple field measurement, 2020, Mechanical Systems and Signal Processing
  • Mechanism of short pitch rail corrugation: initial excitation and frequency selection for consistent initiation and growth, 2022, International Journal of Rail Transportation
  • Ground vibration induced by high speed trains on an embankment with pile-board foundation: Modelling and validation with in situ tests, 2022, Transportation Geotechnics
  • Artificial intelligence in railway infrastructure: current research, challenges, and future opportunities, 2023, Intelligent Transportation Infrastructure

The scientist has collaborated frequently with colleagues including Alfredo Núñez, Zili Li, Hongrui Wang, and Taniya Kapoor. These collaborations have been significant, with multiple coauthored publications across various research areas.

Best Publications

  • An investigation into the causes of squats—Correlation analysis and numerical modeling

    Zili Li;Xin Zhao;Coenraad Esveld;Rolf Dollevoet

  • Automatic detection of squats in railway infrastructure

    Maria Molodova;Zili Li;Alfredo Núñez;Rolf P. B. J. Dollevoet

  • Axle box acceleration: Measurement and simulation for detection of short track defects

    Marija Molodova;Zili Li;Rolf Dollevoet

  • Squat growth—Some observations and the validation of numerical predictions

    Zili Li;Rolf Dollevoet;Marija Molodova;Xin Zhao

  • A big data analysis approach for rail failure risk assessment

    Ali Jamshidi;Shahrzad Faghih-Roohi;Siamak Hajizadeh;Alfredo Núñez

  • Nationwide Railway Monitoring Using Satellite SAR Interferometry

    Ling Chang;Rolf P. B. J. Dollevoet;Ramon F. Hanssen

  • On the mechanism of squat formation on train rails – Part I: Origination

    Michaël Steenbergen;Rolf Dollevoet

  • Improvements in Axle Box Acceleration Measurements for the Detection of Light Squats in Railway Infrastructure

    Zili Li;Maria Molodova;Alfredo Nunez;Rolf Dollevoet

  • Differential wear and plastic deformation as causes of squat at track local stiffness change combined with other track short defects

    Zili Li;Xin Zhao;Rolf Dollevoet;Marija Molodova

  • Physics-informed neural networks for solving forward and inverse problems in complex beam systems

    Unknown

  • Health condition monitoring of insulated joints based on axle box acceleration measurements

    Maria Molodova;Maider Oregui;Alfredo Núñez;Zili Li

  • Laboratory simulation of martensite formation of white etching layer in rail steel

    Jun Wu;Jun Wu;Roumen H. Petrov;Roumen H. Petrov;Meysam Naeimi;Zili Li

  • An investigation into the modeling of railway fastening

    M. Oregui;Z. Li;R. Dollevoet

  • Thermomechanical analysis of the wheel-rail contact using a coupled modelling procedure

    Meysam Naeimi;Shaoguang Li;Zili Li;Jun Wu;Jun Wu

  • A decision support approach for condition-based maintenance of rails based on big data analysis

    Ali Jamshidi;Siamak Hajizadeh;Zhou Su;Meysam Naeimi

  • Monitoring bolt tightness of rail joints using axle box acceleration measurements

    M. Oregui;S. Li;A. Núñez;Z. Li

  • Facilitating maintenance decisions on the Dutch railways using big data: The ABA case study

    Alfredo Nunez;Jurjen Hendriks;Zili Li;Bart De Schutter

  • Obtaining railpad properties via dynamic mechanical analysis

    M. Oregui;A. de Man;M.F. Woldekidan;Z. Li

  • New insights into the short pitch corrugation development enigma based on 3D-FE dynamic vehicle-track coupled modelling in frictional rolling contact

    Shaoguang Li;Zili Li;Alfredo Núñez;Rolf Dollevoet

  • Identification of characteristic frequencies of damaged railway tracks using field hammer test measurements

    M. Oregui;Z. Li;R. Dollevoet

  • Numerical and experimental study of wheel-rail impact vibration and noise generated at an insulated rail joint

    Zhen Yang;Zhen Yang;Anthonie Boogaard;Rong Chen;Rolf Dollevoet

  • Evaluating Degradation at Railway Crossings Using Axle Box Acceleration Measurements

    Zilong Wei;Alfredo Núñez;Zili Li;Rolf P. B. J. Dollevoet

  • “Brown etching layer”: A possible new insight into the crack initiation of rolling contact fatigue in rail steels?

    Shaoguang Li;Jun Wu;Jun Wu;Roumen H. Petrov;Roumen H. Petrov;Zili Li

  • Validation of a finite element model for axle box acceleration at squats in the high frequency range

    Maria Molodova;Zili Li;Alfredo Núñez;Rolf Dollevoet

Frequent Co-Authors

Zili Li
Zili Li Delft University of Technology
Jilt Sietsma
Jilt Sietsma Delft University of Technology
Roumen Petrov
Roumen Petrov Ghent University
Zhigang Liu
Zhigang Liu Southwest Jiaotong University
Ramon F. Hanssen
Ramon F. Hanssen Delft University of Technology
Valeri Markine
Valeri Markine Delft University of Technology
Bart De Schutter
Bart De Schutter Delft University of Technology
Robert Babuska
Robert Babuska Delft University of Technology
Simone Baldi
Simone Baldi Southeast University
David M. J. Tax
David M. J. Tax Delft University of Technology

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