Addressing the challenge of roll loss and strip deformation arising from the lack of precise prediction of the roll temperature field in hot tandem rolling mills, this study employs numerical analysis via the finite difference method. Based on the roll temperature field and hot roll crown model, an intelligent support cooling control system for the roll cooling water of hot rolls is established. This system comprehensively considers the direct impact of specific parameters on the roll temperature field in the intricate context of cooling water dynamics. The study focuses on the cyclic superposition effect of rolling coil quantities on the roll temperature field and the resulting hot roll shape, and theoretical calculations along with simulation analyses were conducted using finite element software. Through the integration of field-measured values, the study achieves accurate predictions of the temperature field and hot roll profile for both work rolls and backup rolls.

The roll quenching process can be approximated as a high-pressure jet impinging on a high-temperature moving steel plate. The process can greatly improve the strength and overall mechanical properties of the steel plate. However, the cooling uniformity and other factors lead to the problem of poor plate shape after quenching. It is found that in the roll quenching process, the roller conveyor speed has a large influence on the temperature field and stress field. This paper establishes a roll quenching mechanism model, iterates the convective heat transfer coefficient on the steel plate surface through the inverse heat transfer method, and performs a numerical simulation. Through the numerical simulation of the roll quenching process in the high-pressure zone of the steel plate, the temperature and equivalent force change rule of the transient of each position of the steel plate in the thick direction are obtained. It is found that the plate does not reach its maximum value when it is in the quenching zone, but there is some hysteresis that becomes more pronounced as it gets closer to the core. These findings are valuable for regulating the roll-hardening process and maintaining optimal strip surface quality in industrial production environments.

Roll wear significantly affects production efficiency and product quality in hot-rolled strip steel manufacturing by reducing roll lifespan and impeding the control of strip shape. This study addresses these challenges through a comprehensive analysis of the roll wear mechanism and the integration of an elastic deformation model. We propose an optimized wear prediction model for work and backup rolls in a hot continuous rolling finishing mill, dynamically accounting for variations in strip specifications and cumulative wear effects. A three-dimensional elastic–plastic thermo-mechanical coupled finite element model was established using MARC 2020 software, with experimental calibration of wear coefficients under specific production conditions. The developed dynamic simulation software achieved high-precision wear prediction, validated by field measurements. The optimized model reduced prediction deviations for work and backup rolls to 0.012 and 0.004, respectively, improving accuracy by 5.3% and 3.25% for uniform and mixed strip specifications. This research provides a robust theoretical framework and practical tool for precision roll wear management in industrial hot rolling processes.

This study aims to enhance the efficiency of pickling processes by investigating the impact of strip speed and acid flow rate on the turbulence of the acid solution within the pickling tank. The research quantitatively evaluates the flow field state and distribution of acid temperature within the pickling tank. Through finite element simulation, factors such as jet velocity, strip motion velocity, and acid temperature are considered to determine the turbulence intensity, turbulent kinetic energy, convective heat transfer coefficient, and average temperature of the near-wall layer of the strip surface under the oblique jet. This analysis considers the effects of these parameters on the flow field within the pickling tank. Furthermore, simulations are conducted to assess the turbulence intensity of the acid solution under various conditions. The study reveals that the intake flow rate has a substantial influence on turbulence and temperature rise at the strip exit and inlet, albeit less so, within the acid tank itself. However, an increase in strip speed notably impacts the turbulence within the center of the acid tank. These findings are invaluable for regulating the pickling process and maintaining optimal strip surface quality in industrial production settings.