The first generation of wind turbines are being retired, and a tremendous number of wind tur-bine blades are coming out of service. Architects and engineers are developing re-use ideas for these blades and are wrestling with their complex geometries and materiality. This paper details a four-phase process for reconstructing the geometry of wind turbine blades, starting from a point-cloud scan and finishing with a digital model that represents the blade and its associated properties. The process builds on earlier work that created an airfoil database to store the nor-malized coordinates of publicly available airfoil profiles. This profile database is traversed to match airfoil shapes to cross-sections found in the point-cloud. Root, transition, and airfoil shapes are matched to cross-sections along the full blade to reconstruct the outer geometry. Based on data from the interior of the blade, the structural spar box is reconstructed. The addi-tion of thickness and material property data allows for calculation of section properties at multi-ple stations along the blade. The resulting 3D geometry and the associated data is used for ar-chitectural design and engineering calculations to develop second-life applications for wind blades. The paper demonstrates the workflow through examples from a GE 37-meter blade and an LM 13.4-meter blade.
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Reconstruction of Wind Turbine Blade Geometry and Internal Structure from Point Cloud Data
This paper presents a method for the digital reconstruction of the geometry of a wind turbine blade from a point-cloud model to polysurface model. The digital reconstruction of the blade geometry is needed to develop computer models that can be used by architects and engineers to design and analyze blade parts for reuse and recycling of decommissioned wind turbine blades. Initial studies of wind-blade geometry led to the creation of an airfoil database that stores the normalized coordinates of publicly-available airfoil profiles. A workflow was developed in which these airfoil profiles are best-fitted to targeted cross-sections of point-cloud representations of a blade. The method for best-fitting airfoil curves is optimized by minimizing the distance between points sampled on the curve and point-cloud cross section. To demonstrate the workflow, a digitally-created point-cloud model of a 100 m blade developed by Sandia National Laboratory was used to test the reconstruction routine.
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- Award ID(s):
- 1701413
- PAR ID:
- 10147569
- Date Published:
- Journal Name:
- Proceedings of the 2019 ASCE International Conference on Computing in Civil Engineering (i3CE2019)
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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