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David R.S. Verelst

About David R.S. Verelst

David R.S. Verelst, With an exceptional h-index of 14 and a recent h-index of 12 (since 2020), a distinguished researcher at Danmarks Tekniske Universitet, specializes in the field of Wind Turbine Engineering, Aeroelasticity, Rotor Blades.

His recent articles reflect a diverse array of research interests and contributions to the field:

Dynamic Modelling and Response of a Power Cable connected to a Floating Wind Turbine

HAWC2 v13. 1 and HAWCStab2 v2. 16 Comparison

Veer and shear in the tropical cyclone lower boundary-layer

Extreme coherent gusts with direction change–probabilistic model, yaw control, and wind turbine loads

Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parameterization in WRF

Swept Blade Dynamic Investigations for a 100 kW Small Wind Turbine

Using transfer learning to build physics-informed machine learning models for improved wind farm monitoring

Blade research and demonstration platform

David R.S. Verelst Information

University

Position

Scientist, DTU Wind Energy

Citations(all)

618

Citations(since 2020)

482

Cited By

271

hIndex(all)

14

hIndex(since 2020)

12

i10Index(all)

20

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

David R.S. Verelst Skills & Research Interests

Wind Turbine Engineering

Aeroelasticity

Rotor Blades

Top articles of David R.S. Verelst

Dynamic Modelling and Response of a Power Cable connected to a Floating Wind Turbine

Wind Energy Science Discussions

2024/4/29

HAWC2 v13. 1 and HAWCStab2 v2. 16 Comparison

2024

Georg Pirrung
Georg Pirrung

H-Index: 11

Riccardo Riva
Riccardo Riva

H-Index: 3

Veer and shear in the tropical cyclone lower boundary-layer

EGU General Assembly Conference Abstracts

2023/5

Xiaoli Guo Larsén
Xiaoli Guo Larsén

H-Index: 18

Extreme coherent gusts with direction change–probabilistic model, yaw control, and wind turbine loads

Wind Energy Science

2023/2/21

Tropical cyclone low-level wind speed, shear, and veer: sensitivity to the boundary layer parameterization in WRF

Wind Energy Science Discussions

2023/7/7

Xiaoli Guo Larsén
Xiaoli Guo Larsén

H-Index: 18

Swept Blade Dynamic Investigations for a 100 kW Small Wind Turbine

Energies

2022/4/20

Taeseong Kim
Taeseong Kim

H-Index: 15

Using transfer learning to build physics-informed machine learning models for improved wind farm monitoring

Energies

2022/1/13

Blade research and demonstration platform

Journal of Physics: Conference Series

2020/9/1

Frederik Zahle
Frederik Zahle

H-Index: 22

A surrogate model approach for associating wind farm load variations with turbine failures

Wind Energy Science Discussions

2020/5/11

The effects of blade structural model fidelity on wind turbine load analysis and computation time

Wind Energy Science

2020/4/20

Re-design of an upwind rotor for a downwind configuration: design changes and cost evaluation

Conceptual Research of a Multi Megawatt Downwind Turbine

2019/12

See List of Professors in David R.S. Verelst University(Danmarks Tekniske Universitet)