Heat transfer modeling and waste heat management in the furnaces of secondary aluminum production
Aluminum recycling significantly contributes to supplying the growing demand for aluminum alloys within the framework of a circular economy. Recycling leads to reducing the negative economic and environmental impact of primary aluminum production. Enhancing energy efficiency to reduce carbon footprint in secondary aluminum production is a necessity for meeting the environmental regulations. This project is conducted during an internship at EPFL, and in collaboration with an industrial company. In the current study, several potential solutions are proposed and analyzed to improve energy efficiency in both remelting and rolling plants of secondary aluminum production. To characterize the thermal performance of the furnaces and evaluate the proposed strategies for waste heat management, a heat transfer model is developed using the finite difference method and machine learning approaches. Four regression models are trained and checked for predicting the heat transfer coefficient in preheater and ACL furnaces. These operational models calculate temperature profile of the aluminum inside the furnaces, as well as the fuel consumptions, and allows achieving an energy analysis for non-predefined operating conditions. A low computational time makes the model suitable for the optimization and real-time controlling applications. The energy efficiency scenarios for the remelting plant are defined based on the integrated waste heat from the melter and holder stack into the preheater furnace to heat up the charge. Results demonstrate that waste heat recovery can reduce fuel consumption of the preheater furnace up to 80.4% less than energy consumption of the preheater furnace in the business-as-usual case. Potential solutions for improvement of the energy performance in rolling plant are proposed on the furnace of annealing continuous line (ACL). ACL furnace is critical for achieving the desired material properties in the production of high-quality aluminum products. The proposed strategies include the modulation of the furnace temperature profiles and the energy integration via the partial recirculation of the zonal exhaust gases. The results show that the advanced energy integration approach significantly reduces fuel consumption by up to 20.7%. In total, the proposed energy efficiency measures reduce fuel consumption by 2.7 and 5.5 m3NG/tonAl in remelting and rolling plants, respectively.
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