Go to https://blastnet.github.io/ to access and download this reacting and non-reacting flow physics simulations. The Bearable Large Accessible Scientific Training Network-of-Datasets (BLASTNet) is composed of: Direct involvement from the scientific community. Public Machine Learning (ML) repositories such as Kaggle. Lossy compression techniques for managing >100 GB data. An easily-accessible webpage (https://blastnet.github.io/).

{"references": ["Wai Tong Chung, Ki Sung Jung, Jacqueline H. Chen, Matthias Ihme (2022), BLASTNet: A call for community-involved big data in combustion machine learning, Applications in Energy and Combustion Science 12 pp. 100087.", "Wai Tong Chung, Ki Sung Jung, Jacqueline H. Chen, Matthias Ihme (2022), The Bearable Lightness of Big Data: Towards Massive Public Datasets in Scientific Machine Learning, arXiv 2207.12546"]}

URL: https://blastnet.github.io/