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Kim Branner

Technical University of Denmark

Denmark

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Research Interests

Structural Engineering

100%

Solid Mechanics

100%

Wind Engineering

70%

Turbine Technology

50%

Applied Mechanics

50%

Fatigue Analysis

40%

Damage Detection

40%

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Articles15

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

Article Link

Year:

2024

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

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Year:

2024

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

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Year:

2024

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

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Year:

2024

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

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Year:

2023

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

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Year:

2023

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

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Year:

2022

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

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Year:

2022

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

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Year:

2022

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

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Year:

2022

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

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Year:

2021

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

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Year:

2021

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

Article Link

Year:

2021

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

Article Link

Year:

2021

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

Article Link

Year:

2021

Collaborators15

Henrik Madsen

Technical University of Denmark

DENMARK

Süleyman Cem Yeniceli

Technical University of Denmark

DENMARK

Philipp Ulrich Haselbach

Technical University of Denmark

DENMARK

Hans-Henrik Benzon

Technical University of Denmark

DENMARK

Heloisa Guedes Mendonça

Technical University of Denmark

DENMARK

Malcolm McGugan

Technical University of Denmark

DENMARK

Oscar Gerardo Castro Ardila

Technical University of Denmark

DENMARK

Lars Pilgaard Mikkelsen

Associate Professor

Technical University of Denmark

DENMARK

Seyed Sina Samareh-Mousavi

Technical University of Denmark

DENMARK

Federico Belloni

Technical University of Denmark

DENMARK

Peter Berring

Technical University of Denmark

DENMARK

Xiao Chen

Technical University of Denmark

DENMARK

Steffen Rasmussen

Technical University of Denmark

DENMARK

Sergei Semenov

Technical University of Denmark

DENMARK

Kenneth Thomsen

Technical University of Denmark

DENMARK

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