Antonios Tempelis, Kristine Munk Jespersen, Leon Mishnaevsky Jr.
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引用次数: 0
Abstract
The state of the surface of the leading edge of wind turbine blades is important for optimal aerodynamic performance. Rain erosion leads to damage and roughness on the leading edge. In this study, we present an approach to predict the level of roughness of the leading edge based on fatigue damage accumulation due to impacts of rain droplets. Impact simulations of droplets on the protective coating layer are coupled with rain erosion test data and fatigue S-N curves. Fatigue damage values are then related to surface roughness levels. An approach to extract S-N curve parameters from a rain erosion test and then make predictions for other coatings based only on the output of impact simulations is presented and tested against test data. Both the end of incubation and coating breakthrough times are predicted with this approach. Stress, strain and energy density values were used as fatigue damage indicators and the respective predictions were compared to each other. It was found that the maximum principal strain gave the best predictions and matched the experimental trends.
期刊介绍:
Typical subjects discussed in International Journal of Fatigue address:
Novel fatigue testing and characterization methods (new kinds of fatigue tests, critical evaluation of existing methods, in situ measurement of fatigue degradation, non-contact field measurements)
Multiaxial fatigue and complex loading effects of materials and structures, exploring state-of-the-art concepts in degradation under cyclic loading
Fatigue in the very high cycle regime, including failure mode transitions from surface to subsurface, effects of surface treatment, processing, and loading conditions
Modeling (including degradation processes and related driving forces, multiscale/multi-resolution methods, computational hierarchical and concurrent methods for coupled component and material responses, novel methods for notch root analysis, fracture mechanics, damage mechanics, crack growth kinetics, life prediction and durability, and prediction of stochastic fatigue behavior reflecting microstructure and service conditions)
Models for early stages of fatigue crack formation and growth that explicitly consider microstructure and relevant materials science aspects
Understanding the influence or manufacturing and processing route on fatigue degradation, and embedding this understanding in more predictive schemes for mitigation and design against fatigue
Prognosis and damage state awareness (including sensors, monitoring, methodology, interactive control, accelerated methods, data interpretation)
Applications of technologies associated with fatigue and their implications for structural integrity and reliability. This includes issues related to design, operation and maintenance, i.e., life cycle engineering
Smart materials and structures that can sense and mitigate fatigue degradation
Fatigue of devices and structures at small scales, including effects of process route and surfaces/interfaces.