Development and Demonstration of an Improved Hybrid Machine Learning Algorithm for Predicting Lagrangian Trajectories in Turbulent Wall-Bounded Flows

Mortimer, L.F. and Fairweather, M. (2024) Development and Demonstration of an Improved Hybrid Machine Learning Algorithm for Predicting Lagrangian Trajectories in Turbulent Wall-Bounded Flows. In: American Institute of Physics Conference Proceedings. International Conference on Applied Physics, Simulation and Computing (APSAC 2024), 20-22 Jun 2024, Rome, Italy. American Institute of Physics

Metadata

Item Type: Proceedings Paper
Authors/Creators:
  • Mortimer, L.F.
  • Fairweather, M.
Copyright, Publisher and Additional Information:

This is an author produced version of a conference paper accepted for publication in Powder Technology, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.
Dates:
  • Published: 20 June 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds)
Funding Information:
Funder
Grant number
EPSRC (Engineering and Physical Sciences Research Council)
EP/S01019X/1
Depositing User: Symplectic Publications
Date Deposited: 07 Jan 2025 14:45
Last Modified: 08 Jan 2025 14:17
Status: Published
Publisher: American Institute of Physics
Open Archives Initiative ID (OAI ID):

Export

Statistics


CORE (COnnecting REpositories)