LLNL researchers unleash machine learning in designing advanced lattice structures

Characterized by their intricate patterns and hierarchical designs, lattice structures hold immense potential for revolutionizing industries ranging from aerospace to biomedical engineering, due to their versatility and customizability. However, the complexity of these structures and the vast design space they encompass have posed significant hurdles for engineers and scientists, and traditional methods of design exploration and optimization often fall short when faced with the sheer magnitude of possibilities within the lattice-design landscape. LLNL scientists and engineers are looking to address these longstanding challenges by incorporating machine learning (ML) and artificial intelligence to accelerate design of lattice structures with properties like low weight and high strength, that can be optimized with unprecedented speed and efficiency. In a recent study published by Scientific Reports, LLNL researchers fused ML-based approaches with traditional computational techniques in hopes of ushering in a new era in lattice design. By harnessing the power of ML algorithms, researchers are unlocking the ability to predict mechanical performance, optimize design variables and speed up the computational design process for lattices that possess millions of potential design options. Read more at LLNL News.