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Grant Award View - GA71894-V3
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design
GA ID:
GA71894-V3
Agency:
Australian Research Council
Approval Date:
21-Feb-2020
Variation Publish Date:
19-Oct-2021
Variation Date:
12-Oct-2021
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jul-2021 to 30-Jun-2024
Value (AUD):
$545,000.00
(GST inclusive where applicable)
Varies:
GA71894
- Deep Learning Augmented Intelligent Grinding Mill Simulation and Design
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Linkage
Grant Program:
Linkage Projects
Grant Activity:
Deep Learning Augmented Intelligent Grinding Mill Simulation and Design
Purpose:
Comminution is a key operation in mineral processing that utilises grinding mills to reduce the size of ore for further mineral enrichment processing. The aim of this project is to provide a step change improvement in the operational efficiency and service life of grinding mills through the development of advanced numerical models to simulate the grinding mill process. The outcome will be a hierarchical deep learning program to select optimal model parameters from which computational algorithms will optimise grinding mill geometries. This research project will deliver substantial improvements to equipment used to process our most valuable exports and result in immediate industry impact.
GO ID:
GO Title:
Linkage Projects for funding applied for in 2019
Internal Reference ID:
LP19 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The University of Newcastle
Recipient ABN:
15 736 576 735
Grant Recipient Location
Suburb:
CALLAGHAN
Town/City:
CALLAGHAN
Postcode:
2308
State/Territory:
NSW
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
NSW
Postcode:
2308
Country:
AUSTRALIA