Temperature effects on the static, dynamic and fatigue behaviour of composite materials used in wind turbine blades
Bibliographic record
Abstract
Many Canadian regions have strong winds that are interesting for wind energy production. However, these same regions are often quite remote and the Canadian climate is atypical for the wind energy industry. The high level of uncertainty about the turbines durability and the profitability of wind plants under such environments thus hinders the development of wind energy projects in Canada. Among the many uncertainties related to Canadian operating conditions, one specific concern is about the durability of wind turbine blades in Northern climates. \n \nThe goal of this thesis is thus to clarify the effects of temperature and strain rate on the strength, stiffness and fatigue performance of composite materials as used in the wind energy sector. It thus focuses on glass fibre reinforced composites, which is the mainstream material for wind turbine blades. Wind turbine blades are basically beam exposed to a combination of axial, bending (in and out of the rotor plane) and torsional loads. In order to resist these loads, laminates used in the different parts of the blade are mostly made of a combination of longitudinal and ±45◦ plies. In order to improve the basic understanding of the mechanics of failure, two simple laminate configurations are studied, namely: \n \n• The unidirectional laminate loaded in the fibre direction, which is the main load bearing component of the blade structure. \n \n• The [±45]s bias-ply laminate, which provides shear stiffness to the blades structure. \n \nThe temperatures considered are limited to those that could realistically be encountered in Canada’s climate, namely an extreme wintertime low of -40℃ to a summertime high of 60℃, which is deemed representative of a part exposed to direct sunlight in the summer. Similarly, fatigue frequencies are limited to a maximum of 24 Hz. \n \nIt was found that the static strength and stiffness of both laminate configurations were strongly affected by both low and high temperatures. A significant increase of both properties was measured at low temperature, while high temperature strongly degraded them. However, while the high temperature fatigue durability followed the same trend as the static strength, the low temperature fatigue performance was only slightly affected, and even less so for unidirectional laminates. Both a vertical shift and a change in slope of the S–N curve with temperature was observed. At low temperature, this change of slope favours the fatigue strength under a high fatigue load, but reduces expected lives at lower load levels. This finding may be particularly significant in the context of wind turbine blade durability since they generally need to operate at low fatigue stresses, but over very long periods. Frequency effects were mostly not significant within the range explored. Nevertheless, experiments suggest that higher frequencies may have a slightly deleterious effect. \n \nAn approach to predict the effect of temperature on the probabilistic S–N curve of fibre dominated composites with minimal experimental requirements is also proposed. This method is based on a cyclic strength degradation model, for which the parameters change with temperature is correlated with temperature effect on static strength. Since the latter is also an input for the cyclic strength degradation model, a function describing its temperature dependence is also suggested. The predictions obtained by the model are very good for both strength and fatigue life. \n \nFinally, models are developed for describing the static strength as well as the storage and loss modulus as a function of temperature across multiple transitions. The latter model also has provision for evaluating frequency effects on the storage modulus and glass transition temperature. These models provide a very good description of the dynamic response of polymers and composites on which they were validated (epoxies and epoxy based composites). Moreover, they provide a unambiguous definition of the glass transition temperature and allows for the evaluation of temperature and frequency effects on both the storage modulus without using the time-temperature superposition principle. Results show that if the time-temperature shift factors are calculated from the model, they are continuous across the glass transition. This suggests that the commonly expected discontinuity in this region may actually only be a side effect of neglecting the glass transition frequency dependence in conventional time-temperature superposition approaches.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".