A grey-box Neural Network Composite Model for an Industrial Heating Furnace

Abstract

Industrial furnaces consume large amounts of energy and their operating points have a major influence on the quality of the final product. Design- ing a tool that analyzes the combustion process, fluid mechanics and heat transfer and assists the energy audit work is then of the most importance. This work proposes a hybrid composite model for such a tool, having, as its base, two white-box models, namely a detailed Computational Fluid Dynamics (CFD) model and a simplified Reduced-Order (RO) model, plus a black-box model developed using Artificial Neural Networks. The preliminary results presented in this 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.