Lattice Structure

Lattice structures, encompassing regular and irregular arrangements of interconnected elements, are being extensively studied to understand and predict their mechanical and physical properties. Current research focuses on developing data-driven models, such as graph neural networks and variational autoencoders, to efficiently simulate and optimize these structures, particularly for additive manufacturing applications and the design of architected materials. This work is driven by the need to accurately predict material behavior under various conditions, leading to improved design and performance in diverse fields, including aerospace and bioengineering. The development of accurate and efficient predictive models is crucial for accelerating the design process and enabling the creation of novel materials with tailored properties.