|
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/37235
|
Title: | Composite SVR based modellingof an Industrial Furnace |
Authors: | Santos, Daniel Rato, Luís Gonçalves, Teresa Barão, Miguel Costa, Sérgio Malico, Isabel Canhoto, Paulo |
Issue Date: | 3-Oct-2019 |
Publisher: | Lucian Blaga University Press |
Citation: | Santos, D., Rato, L., Gonçalves, T., Barão, M., Costa, S., Malico, I., Canhoto, P. (2020). Composite SVR based modelling of an industrial furnace. 6th International Conference on Modeling and Development of Intelligent Systems, MDIS 2019, p. 36, 3-5 de Outubro de 2019, Sibiu, Romania |
Abstract: | Industrial furnaces consume a large amount of energy and their operating points have a major influence on the quality of the final product. Designing a tool that analyzes the combustion process, fluid mechanics and heat transfer and assists the work done during energy audits is then of the most importance. This work proposes a hybrid model for such a tool, having as it base two white-box models, namely a detailed Computational Fluid Dynamics (CFD) model and a simplified Reduced-Order model (RO), and a black- box model developed using Machine Learning (ML) techniques. The preliminary results presented in the paper show that this composite model is able to improve the accuracy of the RO model without having the high computational load of the CFD model. |
URI: | http://hdl.handle.net/10174/37235 |
Type: | lecture |
Appears in Collections: | ICT - Comunicações - Em Congressos Científicos Internacionais
|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
|