Advanced numerical modeling and validation of dynamic thermal behavior in layered composites for active thermography test

Non-Destructive Evaluation (NDE) techniques, such as thermography, have become essential for detecting and characterizing defects in composite materials, especially in aerospace and other high-performance applications. While traditional numerical approaches, including those implemented in software like ANSYS and COMSOL, have provided valuable insights into thermal behavior, they face limitations in computational efficiency and accuracy when applied to anisotropic, layered composites. This research introduces advanced numerical modeling methodologies based on the Carrera Unified Formulation (CUF) and the Sublaminate Generalized Unified Formulation (SGUF). For the first time, CUF and SGUF are implemented for transient thermal analysis using active thermography, specifically in Thermography. These formulations enable efficient and accurate simulations of dynamic thermal behavior, capturing interlaminar interactions and thermal gradients that are critical for defect detection. The study begins with a comprehensive review of traditional thermographic techniques and their numerical counterparts. Numerical approaches commonly implemented in finite element tools like Finite difference models (FDM), ANSYS and COMSOL are critically analyzed, revealing significant gaps in computational efficiency and their inability to fully capture interlaminar thermal interactions and anisotropic material behaviors. To address these challenges, CUF and SGUF-based models are developed, offering a more streamlined and accurate framework for transient thermal analysis. These models are further applied in various parametric studies, including lay-up sequence analysis, material anisotropy, and thermal gradient effects, to comprehensively evaluate their performance. Validation of the developed models is conducted through comparisons with experimental data and traditional numerical benchmarks, demonstrating their accuracy and robustness. Key findings demonstrate that CUF and SGUF enhance computational efficiency and accuracy in predicting thermal responses, such as temperature distribution and heat flux, making them effective for thermal analysis of composite materials. Their efficiency enables the application to real defect scenarios, such as simulating air-filled gaps in T-joint structures for debonding analysis. Moreover, the versatility of these advanced formulations enables their application to complex geometries and real-world scenarios, providing critical insights into defect detection and thermal behavior in layered composites.