Dataset for Fail-Safe Topology Optimization using Artificial Neural Networks

This repository contains the training dataset created within the research project "Structural Optimization for Fail-Safe Designs by Machine Learning". The objective of the project is to investigate machine learning approaches for fail-safe topology optimization. In particular, a conditional generative adversarial network (cGAN) was trained to map topology-optimized non-fail-safe structures obtained from standard compliance minimization to corresponding fail-safe designs.