Periodic Reporting for period 3 - PRE-ECO (A new paradigm to re-engineering printed composites)
Reporting period: 2023-02-01 to 2024-07-31
This project is for an exploratory study into a radical new approach to the problem of design, manufacturing and analysis of tow-steered printed composite materials. The program will act as a pre-echo, a precursor, to: 1) implement global/local models for the simulation and analysis of VATs with unprecedented accuracy from fibre-matrix to component scales; 2) develop a (hybrid) metamodeling platform based on machine learning for defect sensitivity and optimization; and 3) set new rules and best-practices to design for manufacturing. A 5-year, highly inter-disciplinary programme is planned, encompassing structural mechanics, numerical calculus, 3D printing and AFP, measurements and testing of advanced composites, data science and artificial intelligence, and constrained optimization problems to finally fill the gap between the design and the digital manufacturing chain of advanced printed materials.
A parallelized in-house hybrid optimization code has been developed, utilizing Genetic Algorithms (GA) and gradient-based methods to solve continuous and discrete problems efficiently. This tool enables using direct and/or surrogate simulations for enhanced computational efficiency. The code has been applied to multi-objective optimisation problems, targeting mass, strain energy, fundamental frequency, and buckling load as objectives. These optimizations integrate the manufacturing signature of the AFP process, explicitly accounting for gaps and overlap through machine simulations. Additionally, this approach is designed for potential applications in real-world structural scenarios, such as wing-box structural optimization, where design rules and various laminated composite patches are incorporated to further reduce structural weight, offering hope for practical and efficient solutions in structural engineering.
An advanced higher-order beam model employing the Node-Dependent Kinematics approach has been developed for the progressive damage analysis of composite structures. This scalable and efficient model reduces computational costs while accurately capturing damage propagation in critical zones.
Other activities include investigating the possibility of reducing the strain/stress concentrations in an open-hole plate using localized 3D printed carbon fiber reinforcements; using non-local elasticity models to conduct crack propagation analysis; solving inverse problems (e.g. detection of damage or printing issues) via algorithms based on artificial intelligence; cooperation with University of Tokyo on space antennas subject to thermal loading and investigate the effect of geometrical parameters, extending the developed methods to thin-ply composites for deployable structures. Moreover, the latest applications also include the development of high-order models for the accurate three-dimensional stress analysis at large strains of hyperelastic anisotropic materials, allowing the study of innovative composite configurations with isotropic silicone matrix of complex composite with immersed and distributed/dispersed fibers, with refined fully nonlinear models.