Optimization of Digital Image Correlation Techniques for 3D Surfaces in Aeronautics
The project aims to improve the mechanical characterization capabilities used during the mechanical testing of structural aeronautical parts. Specifically, it focuses on developing tools that enable and facilitate the measurement of displacements and deformations on large 3D surfaces using a non-contact measurement method, Digital Image Correlation (DIC). The project will also utilize Finite Element Modeling (FEM) to compare the results obtained with DIC and allow for the early detection of defects or anomalies. Flight tests (in collaboration with ENA and CTA) will be conducted to validate the method.
By enhancing the precision and efficiency of non-contact measurement methods, this project allows for better characterization of deformations and displacements of complex structural parts. The expected impact includes a significant reduction in costs and time associated with physical tests, thanks to better integration of numerical simulations and experimental tests. Additionally, the developed tools will enable real-time monitoring of tests, facilitating early detection of anomalies and optimization of designs. Ultimately, this project will help strengthen the competitiveness of the aerospace industry by offering innovative solutions for the design and validation of aeronautical structures.
This project follows on from a previous project during which an initial method based on DIC was developed and validated through flight tests.
The candidate will benefit from valuable experience in technology transfer between academia and industry, as well as in managing technological research projects. They will develop skills in digital image correlation, experimental methods for the aerospace industry, finite element modeling of aeronautical structures, and post-processing of experimental results. Additionally, they will have the opportunity to collaborate with experts from Bombardier and participate in academic and industrial networks in Montreal.
Required knowledge
The ideal candidate for this PhD or Master project should possess the following skills and knowledge:
Programming Skills: Proficiency in Python and associated libraries such as OpenCV.
Knowledge in Structural Mechanics: Deep understanding of the principles of structural mechanics, particularly in the context of aeronautics. Ability to use finite element software.
Experience in Experimental Methods: Familiarity with experimental testing and measurement techniques, including the preparation and execution of digital image correlation tests.
Data Analysis and Modeling: Skills in analyzing experimental data and finite element modeling to compare experimental results with numerical simulations.
Project Management: Ability to plan and manage complex research projects, including coordination with industrial and academic partners.