PREDICTION OF PREHEAT REFRACTORY TEMPERATURE PROFILE OF A LADLE FURNACE

• Main Authors: SINGH, UMESH, BASAVARSU, PURUSHOTTHAM GAUTHAM
• Format: Patent
• Language: English; French; German
• Published: 15.03.2023
• Subjects: BLASTING; CALCULATING; CASTING; CASTING OF METALS; CASTING OF OTHER SUBSTANCES BY THE SAME PROCESSES OR DEVICES; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS,IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KINDOF FURNACE; ELECTRIC DIGITAL DATA PROCESSING; FURNACES; FURNACES, KILNS, OVENS, OR RETORTS IN GENERAL; HEATING; KILNS; LIGHTING; MECHANICAL ENGINEERING; OPEN SINTERING OR LIKE APPARATUS; OVENS; PERFORMING OPERATIONS; PHYSICS; POWDER METALLURGY; RETORTS; TRANSPORTING; WEAPONS

The present disclosure addresses the technical problem of prediction of a preheat refractory temperature profile of a ladle furnace. Operational temperature of the ladle furnace, stability of sensors and placement make sensors not feasible. Computational Fluid Dynamics (CFD) simulations require large computation time and cannot be used for runtime applications in plants. The method and system of the present disclosure uses CFD modeling to carry out parametric study to generate data which is further processed to train an Artificial Neural Network (ANN) model that serves as a prediction model for predicting the preheat refractory temperature profile for at least a portion of the side refractory and at least a portion of the bottom refractory layer separately for which a new set of input data is obtained. The trained prediction model of the present disclosure provides a quick runtime prediction in plants.