Wind turbine blades continue to grow in length to capture ever more energy. To maintain the economics of this scaling, designers must drive towards minimizing the blade mass while retaining the same reliability in performance. This requires ever more detailed understanding of the response of composite materials under various loading conditions, including damage initiation and progression. Composite materials possess unique damage mechanisms due to their constituent materials and these require further study. Montana State University researchers have begun to investigate damage mechanisms and progression using Acoustic Emission (AE) measurement techniques on common wind industry material systems. The aim is to provide new understanding and design guidance to the industry leading to more cost effective designs and a lower cost of energy.
Composite coupons were manufactured into four layups from four different fabrics in an epoxy matrix, the table below. Acoustic emission sensors were applied in a linear locating arrangement to capture elastic waves emanating from damage mechanisms during a tensile test. Data critical to this study extracted from the elastic waveforms include peak frequency and absolute energy. A static loading scenario was used to characterize the materials and their damage progression, while a load-unload-reload (LUR) scenario was used to correlate absolute energy between cyclic and monotonic tests.
Test matrix showing layups from four different fabrics.
Results of the material characterization found that a greater range of frequencies, and thus damage mechanisms, were observed for increasingly complex fabric architectures. The observed frequency and energy data provided valuable information on the interaction of the various constituent materials. Total accumulated energy emerged as a consistent metric of equal value between static and LUR tests, thus showing promise of being an indicator of coupon damage state.
Strains to damage initiation and changes in damage state were identified in each of the fabric types through the use of peak frequency and absolute energy data. The correlations between peak frequency and four primary composite damage micro-mechanisms determined by other researchers were in agreement with the characterizations performed for this research. Significant activity was observed outside of the frequency range of the expected mode of failure and complex fabrics emitted more events of these other damage types. This data provides invaluable insight into the micro-mechanical damage processes that occur throughout the progression of a test and affect the strength and damage tolerance of the various fabrics. Interphase failures exhibited noticeable shifts in peak frequency between fabrics.
This material characterization will aid in analysis of future coupon work with these materials and will help to identify damage mechanisms for complex sub-structures. Because the peak frequency is a direct representation of the damage type, various modes and critical modes of damage can be identified in situations where it is impossible to visually observe the damage.
The characterizations and progression of damage identified for these materials will also aid validation of damage initiation and progressive damage modeling. These ideal material characterizations can also be compared to defective materials to further quantify the effect of defects. This ability will increase the information gathered per test, thus reducing iterations, test time and cost.
In the interest of developing an AE test metric that could potentially lead to failure criterions, state variables and lifetime estimates, the accumulated absolute energy was found to be a promising candidate. The absolute energy accumulated was consistent not only between tests of the same layup and material, but was also consistent between monotonic and multi-cycle loading regimes.This indicates that for a particular material system, the total accumulated energy may be considered to be a constant value. This constant could be applied as a criterion such that specified levels of accumulated energy can trigger actions such as removing sensors or manually checking the condition of the test article.
Though the rate of accumulation is far from linear, the changes in accumulation rate do indicate various stages of damage progression. An effective method of monitoring the damage state of the test article can be applied when knowledge of the rate of accumulation and values of total accumulation are taken into account.
Through the process of developing the above results and conclusions, Montana State University Composites Research Group has begun to include this new powerful technique into its composites materials characterization testing repertoire. Future work is planned to exploit this data for composite structures and the fundamental data to support damage initiation and progression modeling efforts.
The Montana State University Composite Technologies Research Group website can be accessed here.
Sandia National Labs
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