NON DESTRUCTIVE TESTING (NDT) FOR AEROSPACE COMPOSITE MATERIALS

Abstract

Ensuring the structural integrity of aircraft is critical for safety and operational efficiency in aviation. Non-destructive testing (NDT) of aircraft structures, especially those incorporating a mix of metals and composites, presents challenges in achieving high-resolution imaging, rapid testing, and comprehensive defect detection. Current methods often lack a holistic solution for assessing complex internal structures effectively. The aim of this thesis is to enhance aircraft safety through advanced NDT methods and computational simulations. The objective is to present a comprehensive approach by integrating advanced computational electromagnetics simulations using CST software with Python-based post-processing techniques. This integration aims to address the challenges associated with achieving high-resolution imaging, rapid testing, and comprehensive defect detection in complex internal structures of aircraft. The thesis encompasses several key components. Firstly, the design and setup of the CST simulations are detailed, focusing on modelling complex aircraft structures to simulate electromagnetic interactions within them. The results of these CST simulations provide valuable insights into the behaviour of aircraft structures under electromagnetic conditions. Post-processing techniques using Python are employed to enhance the analysis of CST simulation results. This includes defect identification and representation, where Python scripts are utilized to identify and visualize defects within aircraft structures based on simulation data. Furthermore, dimensionality reduction techniques are applied to identify and locate defects effectively. By employing methods such as Principal Component Analysis (PCA), the complex dataset resulting from simulations is condensed into key components, aiding in the localization of defects within the aircraft structure. The thesis also delves into the computation of dielectric properties in two dimensions (2D) using the Distorted Born Iterative Method (DBIM). This method facilitates the estimation of dielectric properties, providing critical information for NDT applications. Lastly, the thesis explores the three-dimensional (3D) change in permittivity distribution using the Conjugate Gradient Subspace Iteration (CSI) algorithm. This algorithm allows for a detailed analysis of how the permittivity of aircraft materials changes spatially, aiding in the detection and characterization of defects. By integrating these advanced computational simulations and post-processing techniques, this thesis contributes to advancing NDT methods for aircraft structures. The proposed approach promises to enhance safety and efficiency in aviation by providing more accurate and comprehensive defect detection capabilities for complex internal aircraft structures.