Topology Optimization

Topology optimization is a computational method for designing structures by optimally distributing material within a given design space to maximize performance under specified constraints. Current research emphasizes integrating machine learning, particularly neural networks (including convolutional, recurrent, and implicit field architectures), and Gaussian processes to accelerate the optimization process and handle complex nonlinearities, often replacing or augmenting traditional finite element analysis. This approach is significantly impacting various fields, enabling efficient design of structures with enhanced performance and manufacturability in applications ranging from aerospace engineering and additive manufacturing to soft robotics and power grid management.