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Mechanical and Aerospace Engineering
Sweden
2026

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
61
Citations
16518
World Ranking
637
National Ranking
3

Philipp Schlatter 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 Philipp Schlatter 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: 540 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Philipp Schlatter 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 Philipp Schlatter 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: 61 D-Index — 82nd percentile

82% 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

  • 2026 - Research.com Mechanical and Aerospace Engineering in Sweden Leader Award

Overview

Philipp Schlatter is affiliated with the University of Erlangen-Nuremberg in Germany. Their research primarily spans the field of Engineering, with significant contributions focused on subfields such as Computational Mechanics, Aerospace Engineering, Environmental Engineering, Statistical and Nonlinear Physics, and Mechanical Engineering.

The scientist's body of work explores several main topics, including:

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

Philipp Schlatter has published extensively, with frequent contributions to venues such as:

  • arXiv (Cornell University)
  • Journal of Fluid Mechanics
  • International Journal of Heat and Fluid Flow
  • Physical Review Fluids
  • Flow Turbulence and Combustion

Recent papers by the scientist include:

  • Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations, 2022, Physics of Fluids
  • Convolutional-network models to predict wall-bounded turbulence from wall quantities, 2021, Journal of Fluid Mechanics
  • Deep reinforcement learning for turbulent drag reduction in channel flows, 2023, The European Physical Journal E
  • Spectral proper orthogonal decomposition and resolvent analysis of near-wall coherent structures in turbulent pipe flows, 2020, Journal of Fluid Mechanics
  • Aerodynamic Effects of Uniform Blowing and Suction on a NACA4412 Airfoil, 2020, Flow Turbulence and Combustion

Collaboration has been an important aspect of Philipp Schlatter's research activities. Frequent coauthors include:

  • Ricardo Vinuesa
  • Saleh Rezaeiravesh
  • Ramis Örlü
  • Adam Peplinski
  • Stefano Markidis

Best Publications

  • Spectral analysis of nonlinear flows

    Clarence Rowley;Igor Mezic;Shervin Bagheri;Philipp Schlatter

  • Spectral analysis of nonlinear flows

    Clarence W. Rowley;Igor Mezić;Shervin Bagheri;Philipp Schlatter

  • Assessment of direct numerical simulation data of turbulent boundary layers

    Philipp Schlatter;Ramis Örlü

  • Transition in boundary layers subject to free-stream turbulence

    Luca Brandt;Philipp Schlatter;Dan S. Henningson

  • Direct Numerical Simulation of Turbulent Pipe Flow at Moderately High Reynolds Numbers

    George K. El Khoury;Philipp Schlatter;Azad Noorani;Paul F. Fischer

  • Steady solutions of the Navier-Stokes equations by selective frequency damping

    Espen Åkervik;Luca Brandt;Dan S. Henningson;Jéro^me Hœpffner

  • Physics-informed neural networks for solving Reynolds-averaged Navier-Stokes equations.

    Hamidreza Eivazi;Mojtaba Tahani;Philipp Schlatter;Ricardo Vinuesa

  • Turbulent boundary layers up to Reθ=2500 studied through simulation and experiment

    P. Schlatter;R. Örlü;Q. Li;G. Brethouwer

  • Turbulent boundary layers at moderate Reynolds numbers: inflow length and tripping effects

    Philipp Schlatter;Ramis Örlü

  • Global stability of a jet in crossflow

    Shervin Bagheri;Philipp Schlatter;Peter J. Schmid;Dan S. Henningson

  • SIMSON : A Pseudo-Spectral Solver for Incompressible Boundary Layer Flows

    Mattias Chevalier;Philipp Schlatter;Anders Lundbladh;Dan S. Henningson

  • Predictions of turbulent shear flows using deep neural networks

    P. A. Srinivasan;P. A. Srinivasan;L. Guastoni;Hossein Azizpour;Hossein Azizpour;Philipp Schlatter

  • Formation of turbulent patterns near the onset of transition in plane Couette flow

    Yohann Duguet;Philipp Schlatter;Dan S. Henningson

  • Simulation and validation of a spatially evolving turbulent boundary layer up to Reθ = 8300

    Georg Eitel-Amor;Ramis Örlü;Philipp Schlatter

  • Wall accumulation and spatial localization in particle-laden wall flows

    G. Sardina;Philipp Schlatter;Luca Brandt;F. Picano

  • On streak breakdown in bypass transition

    Philipp Schlatter;Luca Brandt;H. C. de Lange;Dan S. Henningson

  • Mutual inductance instability of the tip vortices behind a wind turbine

    Sasan Sarmast;Reza Dadfar;Robert Flemming Mikkelsen;Philipp Schlatter

  • LES of transitional flows using the approximate deconvolution model

    Philipp Schlatter;Steffen Stolz;Leonhard Kleiser

  • Simulations of Spatially Evolving Turbulent Boundary Layers up to Reθ = 4300

    Philipp Schlatter;Qiang Li;Geert Brethouwer;Arne V. Johansson

  • History effects and near equilibrium in adverse-pressure-gradient turbulent boundary layers

    Alexandra Bobke;Ricardo Vinuesa;Ramis Örlü;Philipp Schlatter

  • Convolutional-network models to predict wall-bounded turbulence from wall quantities

    Luca Guastoni;Alejandro Güemes;Andrea Ianiro;Stefano Discetti

  • On the fluctuating wall-shear stress in zero pressure-gradient turbulent boundary layer flows

    Ramis Örlü;Philipp Schlatter

  • The global stability of the jet in crossflow

    Shervin Bagheri;Philipp Schlatter;Dan Henningson

Frequent Co-Authors

Dan S. Henningson
Dan S. Henningson Royal Institute of Technology
Ricardo Vinuesa
Ricardo Vinuesa University of Michigan–Ann Arbor
Ramis Örlü
Ramis Örlü OsloMet – Oslo Metropolitan University
Luca Brandt
Luca Brandt Polytechnic University of Turin
Arne V. Johansson
Arne V. Johansson Royal Institute of Technology
Paul Fischer
Paul Fischer University of Illinois at Urbana-Champaign
Bruno Eckhardt
Bruno Eckhardt Philipp University of Marburg
Hassan M. Nagib
Hassan M. Nagib Illinois Institute of Technology
Carlo Massimo Casciola
Carlo Massimo Casciola Sapienza University of Rome

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