Recent developments in the protection of wind turbine blades against leading edge erosion: Materials solutions and predictive modelling

Mishnaevsky, Leon; Tempelis, Antonios; Kuthe, Nikesh; Mahajan, Puneet

doi:10.1016/j.renene.2023.118966

Cited by 16 publications

(3 citation statements)

References 32 publications

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“…In order to simulate the effect of moisture on the leading edge protection degradation, a computational model for moisture diffusion in the multilayered coating system was developed in [12] [13].…”

Section: Humidity Effect and Coating Debondingmentioning

confidence: 99%

“…Even initially, the blade surface is not ideally plane, while most of the computational models of the droplet impact still assume the plane surface [4] [5]. Figure 4a shows 3D reconstruction of small region of rough blade surface, obtained using the photogrammetry approach from [12]. The digitized rough surface model was introduced into finite element model of liquid impact.…”

Section: Roughness Formation and Effect Of Roughnessmentioning

confidence: 99%

See 1 more Smart Citation

Complex damage mechanisms and roughness evolution of wind turbine blade surface: Multiphysics and stochastic effect modelling

Mishnaevsky,

Kuthe,

Tempelis

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Leading edge erosion of wind turbine blades is the most often observed damage mechanism of wind turbines. The surface erosion of blades is influenced by many multiphysics and stochastic factors including humidity and related degradation processes, rough uneven surface and roughness development, random defects in the materials. In this paper, the effects of these factors and possibilities of their computational modelling and prediction are discussed. Competing damage mechanisms in erosion, including debonding and impact damage, as well moisture ingress and weathering are investigated. A predictive model for roughness evolution of leading edge due to the surface damage is presented.

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Section: Humidity Effect and Coating Debondingmentioning

confidence: 99%

Section: Roughness Formation and Effect Of Roughnessmentioning

confidence: 99%

Complex damage mechanisms and roughness evolution of wind turbine blade surface: Multiphysics and stochastic effect modelling

Mishnaevsky,

Kuthe,

Tempelis

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…Marzbali et al [38] published a review of the mechanics of liquid impingement erosion and liquid solid impact. Mishnaevsky et al [39] presented current advances in material solutions and predictive modelling for wind turbine blade rain erosion protection. They discovered that the coating damage mechanism is affected by the coating material characteristics, debonding, weathering, and humidity.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Offshore Wind Turbine Blades Coating Thickness Effect on Leading Edge Protection System Subject to Rain Erosion

Ansari,

Sánchez,

Mishnaevsky

et al. 2024

Preprint

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Infrared Thermography of Turbulence Patterns of Operational Wind Turbine Rotor Blades Supported With High‐Resolution Photography: KI‐VISIR Dataset

Chaudhuri,

Stamm,

Lapšanská

et al. 2024

Wind Energy

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With increasing wind energy capacity and installation of wind turbines, new inspection techniques are being explored to examine wind turbine rotor blades, especially during operation. A common result of surface damage phenomena (such as leading edge erosion) is the premature transition of laminar to turbulent flow on the surface of rotor blades. In the KI‐VISIR (Künstliche Intelligenz Visuell und Infrarot Thermografie—Artificial Intelligence‐Visual and Infrared Thermography) project, infrared thermography is used as an inspection tool to capture so‐called thermal turbulence patterns (TTPs) that result from such surface contamination or damage. To complement the thermographic inspections, high‐resolution photography is performed to visualise, in detail, the sites where these turbulence patterns initiate. A convolutional neural network (CNN) was developed and used to detect and localise turbulence patterns. A unique dataset combining the thermograms and visual images of operational wind turbine rotor blades has been provided, along with the simplified annotations for the turbulence patterns. Additional tools are available to allow users to use the data requiring only basic Python programming skills.

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Recent developments in the protection of wind turbine blades against leading edge erosion: Materials solutions and predictive modelling

Cited by 16 publications

References 32 publications

Complex damage mechanisms and roughness evolution of wind turbine blade surface: Multiphysics and stochastic effect modelling

Complex damage mechanisms and roughness evolution of wind turbine blade surface: Multiphysics and stochastic effect modelling

Evaluation of Offshore Wind Turbine Blades Coating Thickness Effect on Leading Edge Protection System Subject to Rain Erosion

Infrared Thermography of Turbulence Patterns of Operational Wind Turbine Rotor Blades Supported With High‐Resolution Photography: KI‐VISIR Dataset

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