Autor(es): Santos, Daniel ; Rato, Luís ; Gonçalves, Teresa ; Barão, Miguel ; Costa, Sérgio ; Malico, Isabel ; Canhoto, Paulo
Data: 2024
Identificador Persistente: http://hdl.handle.net/10174/37235
Origem: Repositório Científico da Universidade de Évora
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.
