Data-driven modelling of nonlinear spatio-temporal fluid flows using a deep convolutional generative adversarial network (2020)
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/10.1016/j.cma.2020.113000
Publication URI: http://dx.doi.org/10.1016/j.cma.2020.113000
Type: Journal Article/Review
Parent Publication: Computer Methods in Applied Mechanics and Engineering