Numéro |
Matériaux & Techniques
Volume 104, Numéro 1, 2016
Social Value of Materials SAM-9
|
|
---|---|---|
Numéro d'article | 104 | |
Nombre de pages | 9 | |
Section | Modélisation et simulation : procédés d’élaboration et de traitement / Modelling and simulation : materials processing | |
DOI | https://doi.org/10.1051/mattech/2016004 | |
Publié en ligne | 16 mars 2016 |
Process modelling and simulation of electric arc furnace steelmaking to allow prognostic evaluations of process environmental and energy impacts
1
Scuola Superiore Sant’Anna, TeCIP Institute -
PERCRO, Via Alamanni 13B, 56010
Ghezzano, San Giuliano Terme, Pisa, Italy
i.matino@sssup.it
2
RIVA ACCIAIO S.p.A Caronno Works, Via Bergamo 1484, 21042 Caronno Pertusella,
Varese,
Italy
Received: 21 September 2015
Accepted: 27 January 2016
Several studies have been carried out in order to evaluate optimal process management practices and to assess specific aspects related to the environmental impacts (e.g. CO2 emission) of steelmaking facilities. On the other hand, limited efforts have been spent so far to jointly evaluate the enhancement of process performances, resource management and the overall environmental and energy impact. This paper describes a simulation tool, which is a part of the integrated framework that is under development within the research project entitled “EIRES – Environmental Impact Evaluation and Effective Management of Resources in the EAF Steelmaking”. The modelling approach and validation for one steel grade is described to represent the electric steelmaking route through Aspen Plus®. Results show a global error on energy consumption of about 0.4%, negligible differences in steel composition and temperature. The model application for the evaluation of environmental impact of the process is depicted. The model computes energy consumptions and emissions that can be used to evaluate KPIs to allow evaluation of plant environmental impact during scenario analyses. Thus it can be a powerful instrument for plant manager in feasibility studies in order to enhance process sustainability.
Key words: Electric steelmaking / sustainability / resource efficiency / process modelling / Aspen Plus® simulation
© EDP Sciences, 2016
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