📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

Experimentally trained hybrid machine learning algorithm for predicting turbulent particle-laden flows in pipes (2023)

First Author: Yang Z

Attributed to: A HOLISTIC FRAMEWORK FOR HYBRID MODELLING OF SOLID-LIQUID FLOWS funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1063/5.0172609

Publication URI: http://dx.doi.org/10.1063/5.0172609

Type: Journal Article/Review

Parent Publication: Physics of Fluids

Issue: 11