Kim Branner

Technical University of Denmark

Denmark

Research Interests

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Articles (15)

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Year:

2021

Collaborators (15)

Henrik Madsen

Technical University of Denmark

DENMARK

View details

Süleyman Cem Yeniceli

Technical University of Denmark

DENMARK

View details

Philipp Ulrich Haselbach

Technical University of Denmark

DENMARK

View details

Hans-Henrik Benzon

Technical University of Denmark

DENMARK

View details

Heloisa Guedes Mendonça

Technical University of Denmark

DENMARK

View details

Malcolm McGugan

Technical University of Denmark

DENMARK

View details

Oscar Gerardo Castro Ardila

Technical University of Denmark

DENMARK

View details

Lars Pilgaard Mikkelsen

Associate Professor

Technical University of Denmark

DENMARK

View details

Seyed Sina Samareh-Mousavi

Technical University of Denmark

DENMARK

View details

Federico Belloni

Technical University of Denmark

DENMARK

View details

Peter Berring

Technical University of Denmark

DENMARK

View details

Xiao Chen

Technical University of Denmark

DENMARK

View details

Steffen Rasmussen

Technical University of Denmark

DENMARK

View details

Sergei Semenov

Technical University of Denmark

DENMARK

View details

Kenneth Thomsen

Technical University of Denmark

DENMARK

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Kim Branner

Research Interests

Contact this professor

Articles (15)

Artificial intelligence-based blade identification in operational wind turbines through similarity analysis aided drone inspection

Analysis of damage localization based on acoustic emission data from test of wind turbine blades

Monitoring fatigue delamination growth in a wind turbine blade using passive thermography and acoustic emission

How to design and execute multiaxial fatigue tests for wind turbine blades without sensitive design data?

A full-scale wind turbine blade monitoring campaign: detection of damage initiation and progression using medium-frequency active vibrations

Feasibility study on a full-scale wind turbine blade monitoring campaign: Comparing performance and robustness of features extracted from medium-frequency active vibrations

Structural health monitoring of 52-meter wind turbine blade: Detection of damage propagation during fatigue testing

Experimental demonstration of strain-based damage method for optimized fatigue testing of wind turbine blades

An Operational Image-Based Digital Twin for Large-Scale Structures

Methodology to predict stiffness knock-down in laminates for wind turbine blades with artificial wrinkles

Fatigue testing of a 14.3 m composite blade embedded with artificial defects – damage growth and structural health monitoring

Bending-moment-based approach to match damage-equivalent strains in fatigue testing

Corrigendum to “Effect of tunneling cracks on structural property degradation of wind turbine blades” [Compos. Struct. 268 (2021) 113914]

Effect of tunneling cracks on structural property degradation of wind turbine blades

AQUADA: Automated quantification of damages in composite wind turbine blades for LCOE reduction

Collaborators (15)

Henrik Madsen

Süleyman Cem Yeniceli

Philipp Ulrich Haselbach

Hans-Henrik Benzon

Heloisa Guedes Mendonça

Malcolm McGugan

Oscar Gerardo Castro Ardila

Lars Pilgaard Mikkelsen

Seyed Sina Samareh-Mousavi

Federico Belloni

Peter Berring

Xiao Chen

Steffen Rasmussen

Sergei Semenov

Kenneth Thomsen

Make your next move.