PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 14, 2026Macromolecular Symposia0 citationsOpen Access

Research Testing of Structural Assembly to Wind Turbine Blade Direct Reuse

View Full Paper
CBClaudiu BisuDADorel AnaniaAPAndra Pena

Key Points

  • This research aims to explore the recycling of fiberglass wind turbine blades into functional items, like furniture, focusing on structural assembly.
  • Developed an experimental protocol to measure cutting parameters during drilling.
  • Studied the mechanical characteristics of assembly elements.
  • Analyzed the behavior of the blade material using robotic technology.
  • Identified specific cutting pressure coefficients during drilling processes.
  • Evaluated the insert/part interaction necessary for effective assembly.

Abstract

ABSTRACT The global production of wind energy has increased significantly, representing a basic component in the energy industry, and the blade materials need an intelligent recycling with sustainable transformation. The blades manufactured using fiberglass are found in many applications, considering their superior properties. For this purpose, the transformation of blades after the end of their working life into furniture represents a sustainable solution in the current context of renewable recycling and reducing pollution. The research presents two directions in this phase: first is the study of the drilling blade workpiece behaviour using a robot, and the second axis is focused on assembly solutions. An experimental protocol was built to determine the cutting parameters during drilling as well as the mechanical characteristics resulting from the assembly elements. The results allowed the analysis of the specific pressure coefficient during drilling as well as the insert/part interaction for the assembly process.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bisu et al. (2026) studied this question.

synapsesocial.com/papers/6a05684ea550a87e60a20c5bhttps://doi.org/10.1002/masy.70385
Ask AI
Helpful
Bookmark
Share
View Full Paper