Field-driven multi-variable framework for tailoring of additively manufactured lattice-infilled wing structures

Lightweight components are in high demand in aerospace due to their environmental and economic benefits. Reducing aircraft weight can significantly lower carbon emissions and environmental impact. Advances in additive manufacturing have enabled the production of intricate lattice structures, opening new possibilities for aerospace applications. Lattice-infilled structures are a research hotspot for weight reduction without compromising structural integrity. Selecting lattice parameters such as unit cell type, size, and thickness is challenging with manual methods. Therefore, this study developed a comprehensive lattice design framework using the commercial modeling tool nTop and performed a numerical analysis of lattice-infilled UAV wings in ANSYS workbench. Unit cell type, size, and thickness variations were analyzed based on applied loading conditions through iterative simulations with Python coding. Five-unit cells (BCC, FCC, Kelvin, Fluorite, and Octet) were used in a UAV wing example, arranged in different configurations from uniform distribution to gradient lattice structures tailored by design data fields. Iterative simulations identified the optimal unit cell type, size, and thickness under level flight loading conditions. The results showed significant weight reduction with enhanced stiffness and stress distribution compared to conventional wing structures. Among the five-unit cells, the Octet performed best, and configuration 4 excelled in performance due to its lightweight and improved properties. This study provides an automatic lattice selection process with variable parameters for lightweight lattice-infilled design, guiding design engineers in selecting appropriate unit cells and parameters for specific requirements.