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Adhesive curing cycle time optimization in wind turbine blade manufacturing

Author

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  • Lux, Philipp
  • Cassano, Alessandro G.
  • Johnson, Stephen B.
  • Maiaru, Marianna
  • Stapleton, Scott E.

Abstract

The curing of adhesives in wind turbine blades is a cost and time-intensive manufacturing step. Bondlines are critical to the structural integrity of the blade, but substantial variation in bondline thickness can result in different thermal histories and even degradation of the adhesive due to its exothermic reaction. Models to predict the thermal behavior of adhesive bondlines during the curing step, taking manufacturing conditions and variation in thickness into account, are needed to minimize cure times while avoiding excess temperature. In this study, a finite element model capable of tracing the thermal and conversion histories of the adhesive was developed. Standard heat transfer equations were coupled with cure kinetics in the model through user subroutines, and the cure kinetics were characterized and validated experimentally. A 2D cross-section model of a wind turbine blade was created to simulate the adhesive curing cycle in a manufacturing setting. This model was used to highlight critical aspects of the curing cycle and test methods to shorten the cycle time while maintaining the integrity of the bond. Several improvement methods and their potential cycle time savings were investigated, such as implementing individual heating and cooling zones for each adhesive area and additional spar cap heating/cooling.

Suggested Citation

  • Lux, Philipp & Cassano, Alessandro G. & Johnson, Stephen B. & Maiaru, Marianna & Stapleton, Scott E., 2020. "Adhesive curing cycle time optimization in wind turbine blade manufacturing," Renewable Energy, Elsevier, vol. 162(C), pages 397-410.
    • Handle: RePEc:eee:renene:v:162:y:2020:i:c:p:397-410
    DOI: 10.1016/j.renene.2020.08.043
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    References listed on IDEAS

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    1. Ji, Y.M. & Han, K.S., 2014. "Fracture mechanics approach for failure of adhesive joints in wind turbine blades," Renewable Energy, Elsevier, vol. 65(C), pages 23-28.
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    Cited by:

    1. Sun, Shilin & Wang, Tianyang & Yang, Hongxing & Chu, Fulei, 2022. "Damage identification of wind turbine blades using an adaptive method for compressive beamforming based on the generalized minimax-concave penalty function," Renewable Energy, Elsevier, vol. 181(C), pages 59-70.

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