Wai Tong Chung, Matthias Ihme, Ki Sung Jung, Jacqueline H. Chen, Jack Guo, Davy Brouzet, Mohsen Talei, Bin Jiang, Bruno Savard
, Alexei Y. Poludnenko, Bassem Akoush, Pushan Sharma, Alex Tamkin, Qing Wang, Shantanu Shahane, Chen Yifan, Victor Coulon, Corentin J. Lapeyre
Ensemble de données (2024)
Libre accès au texte intégral chez l'éditeur officielRésumé
Mission
BLASTNet 2.1 was developed to provide the researchers in reacting and non-reacting flow physics communities with high-fidelity simulation datasets in a convenient format for ML applications. With ~5 TB, 765 full-domain samples, and 36 configurations, BLASTNet can effectively address these gaps and aid in fostering open/fair ML development within reacting and non-reacting flow physics communities.
Application
This data is useful for fluid flows in a wide range of ML applications tied to automotive, propulsion, energy, and the environment. Specifically, scientific engineering tasks related to these domains may include turbulent closure modeling, spatio-temporal modeling, and inverse modeling.
Statistiques
Dimensions
