Extending the Capabilities of Data-Driven Reduced-Order Models to Make Predictions for Unseen Scenarios: Applied to Flow Around Buildings (2022)
Attributed to:
PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems (PREMIERE)
funded by
EPSRC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.3389/fphy.2022.910381
Publication URI: http://dx.doi.org/10.3389/fphy.2022.910381
Type: Journal Article/Review
Parent Publication: Frontiers in Physics