Artificial Intelligence to Optimize Melting Processes: An Approach Combining Data Acquisition and Modeling View Full Text


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Chapter Info

DATE

2019-02-16

AUTHORS

Amin Rostamian , Stéphane Lesquereux , Marc Bertherat , Michel Rappaz

ABSTRACT

Melting and Recycling of Al alloys involve large amounts of Energy and CO2 release. In order to minimize Energy consumption and Environment impact, a novel approach has been developed and tested for this industrial sector, but it can be extended to other processes and materials. The approach is based on on-line Data acquisition and efficient numerical Modeling of heat exchanges within a MeltingFurnace. The fast and efficient Numerical Model, which includes the physical mechanisms of Combustion, Radiation, Conduction and Convection, has a few adjustable parameters which are calibrated on-line by a few Data acquisition values. A friendly user-interface allows Furnace operators to monitor the Melting process and optimize mass loading, door opening, heating sequences, etc. The main features of this tool are presented. More... »

PAGES

1159-1164

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-05864-7_142

DOI

http://dx.doi.org/10.1007/978-3-030-05864-7_142

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112157468


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