Scholarlink

Abstract <p>The transformation of a standard conventional bolt to a standard sensory bolt represent challenges because of the conflict between sensory and mechanical functions such as size of the hole, which must be large enough to integrate sensors and electronics, yet small enough to maintain the load bearing capacity and structural integrity. This work introduces a weighted average load-carrying-capacity parameter for bolts used in wind turbines. This parameter, determined through FE simulation, is based on three key factors: maximum stress, maximum plastic strain, and dissipated plastic energy. To reduce the time and computational demands of FE simulation-based optimisation, a predictive metamodel using the Kriging approach was developed. This model provides insights into the degradation of the bolts’ load-bearing capacity. Through optimization, it was found that the height of the lower hole, where the sensor is integrated, could be flexibly chosen provided that its radius was below some threshold value and the use of electronics of standard size already reduced the load capacity of the sensory bolt by 65%. Finally, a short FEM based modal analysis was done to characterize the sensory bolt’s eigen frequency, shedding light on the interplay between the mass loss and the boundary stiffness of the preloaded bolt.</p> Graphical abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

FEM and metamodeling-aided analysis of load-bearing capacity and Eigen frequency of large bolts with holes for sensor integration

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月17日

查看全文
  • Pravishan Bhandari,
  • Alexander Graf,
  • Yakun Xu,
  • Till Clausmeyer

摘要

Abstract

The transformation of a standard conventional bolt to a standard sensory bolt represent challenges because of the conflict between sensory and mechanical functions such as size of the hole, which must be large enough to integrate sensors and electronics, yet small enough to maintain the load bearing capacity and structural integrity. This work introduces a weighted average load-carrying-capacity parameter for bolts used in wind turbines. This parameter, determined through FE simulation, is based on three key factors: maximum stress, maximum plastic strain, and dissipated plastic energy. To reduce the time and computational demands of FE simulation-based optimisation, a predictive metamodel using the Kriging approach was developed. This model provides insights into the degradation of the bolts’ load-bearing capacity. Through optimization, it was found that the height of the lower hole, where the sensor is integrated, could be flexibly chosen provided that its radius was below some threshold value and the use of electronics of standard size already reduced the load capacity of the sensory bolt by 65%. Finally, a short FEM based modal analysis was done to characterize the sensory bolt’s eigen frequency, shedding light on the interplay between the mass loss and the boundary stiffness of the preloaded bolt.

Graphical abstract