Thermal-hydraulic characteristics and optimization of coiled-tube resistance furnace based on response surface method and multi-objective genetic algorithms

The electrification transformation of the petrochemical industry is imminent, driven by the imperative to reduce carbon emissions. This paper presents a coiled-tube resistance furnace and investigates the flow and heat transfer performance of heavy residual oil within the tube through numerical simulation methods. The furnace’s coiled-tube structure was optimized using a multi-objective genetic algorithm (MOGA) combined with a genetic aggregation response surface model, with inlet velocity, coil diameter, pitch, and tube diameter as design variables. The numerical model was experimentally validated and demonstrated the reliability of the simulation approach. Sensitivity analysis identified inlet velocity and coil diameter as the most influential parameters. Consequently, the optimal structural parameters were determined as a coil diameter of 200 mm, a pitch of 60 mm, and a tube diameter of 30 mm. Compared to the original structure, the optimized design led to a 63.7% increase in the average heat transfer coefficient and a 44.6% reduction in the average pressure drop. Additionally, a new correlation formula was developed by incorporating the Dean number, coil curvature, and dimensionless pitch as correction factors. The formula shows excellent fitting accuracy and robustness, providing a theoretical basis for the design of coiled tube resistance furnaces.