Scholarlink

<p>This work examines the sensitivity of Lock-In Thermography (LIT) for subsurface defect detection using an advanced Finite Element Model based on the Carrera Unified Formulation (CUF). The model significantly reduces computing costs while accurately simulating heat transfer in composite laminates with simulated defects using a 2D in-plane mesh with a through-thickness approximation. This computation method has a significant advantage over traditional numerical approaches because it enables defect position variation without requiring mesh modifications. As expected, simulation results show that larger defects are simpler to detect, but deeper defects require optimal excitation frequencies to enhance detection. To verify the sensitivity of the adopted model to defect size and depth, statistical analysis was performed changing the excitation frequency. Furthermore, the developed numerical model is a robust tool for predicting thermographic responses under varying conditions. It enables the refinement of inspection parameters for both industrial applications and academic research, reducing experimental costs and enhancing the understanding of Lock-In Thermography (LIT) methodologies.</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

A Novel Approach to Subsurface Defect Analysis with Lock-In Thermography Using Unified Formulation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月19日

查看全文
  • Sidra Riaz,
  • Davide Palumbo,
  • Umberto Galietti,
  • Maria Cinefra

摘要

This work examines the sensitivity of Lock-In Thermography (LIT) for subsurface defect detection using an advanced Finite Element Model based on the Carrera Unified Formulation (CUF). The model significantly reduces computing costs while accurately simulating heat transfer in composite laminates with simulated defects using a 2D in-plane mesh with a through-thickness approximation. This computation method has a significant advantage over traditional numerical approaches because it enables defect position variation without requiring mesh modifications. As expected, simulation results show that larger defects are simpler to detect, but deeper defects require optimal excitation frequencies to enhance detection. To verify the sensitivity of the adopted model to defect size and depth, statistical analysis was performed changing the excitation frequency. Furthermore, the developed numerical model is a robust tool for predicting thermographic responses under varying conditions. It enables the refinement of inspection parameters for both industrial applications and academic research, reducing experimental costs and enhancing the understanding of Lock-In Thermography (LIT) methodologies.