Application of Cooling Water in Controlled Runout Table Cooling on Hot Strip Mill

The controlled runout table cooling is essential in determining the final mechanical properties and flatness of steel strip. The heat of a hot steel strip is mainly extracted by cooling water during runout. In order to study the heat transfer by water jet impingement boiling during runout, a pilot facility was constructed at the University of British Columbia. On this pilotfacility, the water jet impingement tests were carried out under various cooling conditions to investigate the effect of processing parameters, such as cooling water temperature, water jet impingement velocity, initial strip temperature, water flow rate, water nozzle diameter and array of water nozzles, on the heat transfer of heated strip. The results obtained contribute to the optimization of cooling water during runout.     

Numerical determination of heat transfer coefficient for boiling phenomenon at runout table of hot strip mill

Abstract

The heat transfer coefficient during film boiling at the runout table of the hot strip mill is usually determined by experimental methods. Described in the present paper is a finite difference based model for analysis of the thermal behaviour of the strip during cooling at the runout table of the hot strip mill at Tata Steel, India. The model, developed for the prediction of strip temperature, is used to determine the heat transfer coefficient at the water/strip interface while water cooling occurs. A simple form of polynomial as a function of the strip surface temperature is proposed to describe the heat transfer coefficient at the water/strip interface. Good correlation has been found between model predicted temperatures considering the polynomial type heat transfer coefficient and the actual coiling temperature.     

Thermal behaviour of a moving steel strip cooled by an array of planar water jets

A mathematical model has been developed to predict the temperature distribution in a moving strip of steel cooled by an array of planar water jets. Experimentally determined nucleate boiling and analytically obtained single-phase convection and film boiling heat transfer coefficients are used as convective boundary conditions, and thermophysical property variations of the steel with temperature are considered in the analysis. The model equation for the strip temperature distribution is solved numerically, and the model is validated by comparing predicted coiling temperatures with measurements obtained on the runout table of a steel mill.     

Experimental study of boiling heat transfer during subcooled water jet impingement on flat steel surface

Abstract

The growth in demand for high quality metal alloys has placed considerable emphasis on the type of cooling methods used in manufacturing processes, in particular, the production of highly tailored steel through controlled cooling on the runout table. The present study focuses on the heat transfer (cooling of hot rolled steel strips) on a runout table. The purpose of the study was to develop an efficient experimental method and collect temperature data under conditions similar to those that occur during industrial runout table conditions in a steelmill. Surface and internal temperatures were measured during transient cooling of a flat, upward facing fixed steel plate cooled by a highly subcooled single, circular, free surface jet of water. Measurements were made at stagnation and several streamwise distances from the stagnation point. A numerical, finite difference model was applied to calculate the surface heat flux using measured temperatures. The effect of water flowrate and subcooling on the overall heat transfer with emphasis on the maximum heat flux is discussed.     

Self-Learning and Its Application to Laminar Cooling Model of Hot Rolled Strip

The mathematical model for online controlling hot rolled steel cooling on run-out table （ROT for abbreviation） was analyzed, and water cooling is found to be the main cooling mode for hot rolled steel. The calculation of the drop in strip temperature by both water cooling and air cooling is summed up to obtain the change of heat transfer coefficient. It is found that the learning coefficient of heat transfer coefficient is the kernel coefficient of coiler temperature control （CTC） model tuning. To decrease the deviation between the calculated steel temperature and the measured one at coiler entrance, a laminar cooling control self-learning strategy is used. Using the data acquired in the field, the results of the self-learning model used in the field were analyzed. The analyzed results show that the self-learning function is effective.     

Modelling of microstructural evolution during accelerated cooling of hot strip on the runout table

Microstructural evolution in the hot strip after finishing and subsequent accelerated cooling on the runout table has been modelled in order to assess their suitability for further processing. Transient heat transfer and kinetics of phase change comprising austenite to ferrite plus pearlite have been coupled to ascertain temperature profile, taking into accout the heat generated during phase change. Johnson-Mehl-Avrami relation together with Scheil's rule of additivity have been invoked. Several process parameters such as, coefficient of heat transfer, temperature at the exit of finishing stand, thickness and the speed of strip have been varied to determine their influence on the extent of phases engendered on the runout table. It has been demonstrated that greater spreadout in cooling arrangement with relatively lower heat transfer coefficient ensures homogeneity in microstructure. Cooling from comparatively higher finishing temperatures may result in greater microstructural uniformity. Two grades of steel – namely 0.05C-0.23Mn-0.015Si and 0.08C-0.37Mn-0.06Si – were chosen to carry out plant trials to validate the model. Special features of the microstructure have been brought out and the mechanical properties have been correlated.     

厚规格热轧带钢高精度卷取温度控制模型

卷取温度是影响带钢组织性能的重要工艺参数.在生产实践中,如何提高厚规格带钢卷取温度的控制精度是一个难点.针对厚规格带钢在层流冷却过程中的工况特点,提出了温度场计算模型和对流换热系数模型的改进方法,并开发了一种全新的基于相似策略的自适应模型,以改善卷取温度前馈控制效果.经现场应用证明,本文提出的方案能有效提高厚规格带钢的卷取温度控制精度,其中厚度大于12 mm的带钢平均命中率可达到94.9%.      

Modelling and control of coiling entry temperature using interval type-2 fuzzy logic systems

Abstract

The set-up of the cooling water applied to the strip as it traverses the runout table in order to achieve the coiler entry temperature was made by an intelligent model implemented using interval type-2 fuzzy logic systems. The model uses as inputs the targets for coiling entry temperature, strip thickness, finish mill exit temperature and finishing mill exit speed. The experiments of this application were carried out for three different types of coil in a real hot strip mill. The results proved the feasibility of the system developed for coiler entry temperature prediction. Comparison with the online type-1 fuzzy logic based model shows that the proposed interval type-2 fuzzy logic system improves performance in coiler entry temperature prediction under the tested condition.     

Cooling of a moving steel strip by an array of round jets

Starting from slabs of known dimensions and chemical composition in a hot strip mill, homogeneous strips of predetermined geometry and mechanical properties may be produced. While the geometry and the surface quality are influenced by the deformation process, mechanical properties depend on the cooling process applied immediately after the last stand. Accelerated cooling of steel strips is one of the best ways to achieve both high cooling efficiency and desirable product qualities. A mathematical model is developed to predict the thermal behaviour of steel strips cooled by an array of round jets. Parameters such as the arrangement of the cooling line, nozzle diameter, jet velocity and temperature, and the strip chemical composition (thermophysical properties), thickness and velocity are considered. The governing equation was solved numerically, and the boundary conditions were imposed in different cooling regimes along the cooling line in the form of experimentally and analytically obtained heat transfer coefficients. The mathematical model was validated by comparing predictions for an industrial cooling line with measured starting and coiling temperatures.     

Prediction of Microstructure and Mechanical Properties of Hot Rolled Steel Strip: Part I ‐ Description of Models

A metallurgical through‐process model is presented which describes the microstructural evolution and predicts the final mechanical properties of low carbon steel during hot strip rolling. Process models concern the thermal and deformation phenomena, which take into account the strain, strain rate and temperature distribution along the length of the strip. And the metallurgical models cover five modules, which are (i) austenitization of cast slab in reheating furnace, (ii) recrystallization of austenite in hot rolling, (iii) phase transformation of austenite‐ferrite in laminar cooling on the run‐out‐table, (iv) grain growth after coiling, and (v) final structure‐mechanical properties of products. Temperature is the main parameter and has dominant influence on the microstrutural evolution and the mechanical properties. The related temperature variation in hot strip rolling concerns air cooling, scaling, water cooling, heat transmission by roll contact, heat generation by deformation and friction. These complex factors are incorporated into the thermal models to simulate the temperature distribution along the length of the strip from the reheating furnace exit to the down‐coiler. A self‐learning algorithm is employed to improve the calculation accuracy and the computational temperatures are compared with the measured ones at typical locations. In the structure‐property relationships, two key process parameters (e.g., finishing exit temperature (FT7) and coiling temperature (CT)) are introduced in the model to consider the influence of morphology of microstructure on mechanical properties.     

珠江钢厂CSP热连轧层流冷却热过程模拟研究

分析了带钢层流冷却的传热过程，将相变潜热引入到层流冷却热过程数学模型，用过程模拟的方法研究了珠江钢厂CSP热连轧层流冷却系统。讨论了喷水方式、喷嘴位置、板速和板厚对带钢温度场分布的影响。结果表明建立的模型对于珠钢CSP热连轧层流冷却系统有较好的适应性，能够对实际生产起到较好的指导性作用。     

A parametric study of the accelerated cooling of steel strip

To gain insight into the effects of various parameters controlling the thermal behaviour of a quenched steel strip during the process of accelerated cooling by an array of planar water jets, a parametric study has been performed using a previously developed and validated mathematical model. The behaviour of the strip was characterized by its coiling temperature, top and bottom surface temperature variations and heat extraction in the jet impingement region, top surface heat extraction in the film boiling region, and top and bottom surface thermal penetration depths. Parametric variations included cooling system design conditions, such as the top and bottom nozzle widths, and operating conditions such as the top nozzle discharge velocity, the cooling water temperature, and the ratio of volumetric water flow rates applied at the top and bottom surfaces. The effects of steel strip parameters such as strip thickness and strip velocity were also considered.     

Modelling the Temperature Distribution along the Length of Strip during Hot Rolling Process

Hot strip rolling process includes four main stages, which are reheating process, roughing and finishing process, laminar‐cooling process, and coiling process respectively. Temperature is the most sensitive parameter and has direct effect on the microstructural evolution and further the mechanical properties, and the accurate control of temperature guarantees the quality of products and homogeneity of properties along the strip length. However, for the conventional hot strip rolling process, thermal history along the strip length is very complex, the related temperature variation concerns air cooling, water cooling, heat transmission by roll contact, heat generation by deformation and friction. Based on the actual hot strip mill, the thermal models are established in this paper to simulate the temperature distribution along the whole strip length from the reheating furnace exit to the down coiler. Different interface heat transmission coefficients are selected for the scale breaking and spray water‐cooling process, and a self‐learning algorithm is thus employed to improve the calculation accuracy. This model is characterized as simple and fast, and convenient for on‐line/off‐line prediction of temperature. Finally the simulated results are verified by the on‐line temperature detection at typical points such as roughing exit (RT2), finishing exit (FT7) and coiling position (CT).     

小方坯结晶器水温水速对传热过程影响

通过建立结晶器内钢液和水的二维对流-传热耦合模型过程,研究了小方坯结晶器冷却水入口温度和流速对铜管温度和结晶器内平均热流的影响.该模型使用Fluent进行求解,模拟了钢液和冷却水的流动和传热,凝固坯壳的生长,以及热量以辐射和导热两种通过保护渣和气隙.通过将坯壳厚度和铜管温度与其他研究的结果进行对比来验证模型准确性.研究结果表明,结晶器冷却水的温度显著影响铜管的冷面温度,水温超过313 K会导致铜管冷面最高温度超过水的沸点.水流速升高0.49 m·s-1能够消除水温升高4 K带来的不利影响.      

机架间冷却数学模型计算带钢温度分布

为提高带钢终轧温度的控制精度 ,对精轧过程中导致带钢温度变化的热交换过程进行了分析 ,以此作为机架间冷却控制的传热模型和自学习模型的理论依据 ,给出了带钢厂热轧机组机架间冷却在线控制的传热和自学习模型的算法 ,通过程序开发对精轧机组内带钢的温度分布进行了离线模拟 ,终轧温度计算值与实际生产数据符合较好 ,并对所用数学模型的实际计算结果进行了分析     

层流冷却过程中带钢温度场数值模拟

分析了带钢层流冷却过程中的传热，并利用有限元法对层流冷却过程中带钢温度场进行了模拟计算。结果表明：随着轧件厚度的减薄，在带钢厚度方向上的温差逐渐减小；冷却速度不同时，带钢表面温度和中心温度的变化趋势以及波动幅度相应发生变化。在进行模型计算时，应合理考虑带钢厚度及内部热传导的影响。这对提高数学模型的精度，控制卷取温度，提高产品质量以及指导生产具有重要意义。     

钢板轧后冷却过程的数值模拟及变形分析

 针对钢板冷却发生翘曲变形的问题，利用热弹塑性有限元法对中厚板冷却过程的温度场及应力应变场进行数值模拟。采用分步循环加载的方法精确模拟不同换热边界条件，温度场模拟结果与实测值吻合较好。将热分析得到的温度场作为载荷进行钢板冷却过程应力应变的模拟，模拟结果表明塑性应变差出现在水冷的开始阶段。因此为了获得平直的板形，必须调整上下集管水量比，尽量减小水冷开始时上下表面的应力和塑性应变差。     

热轧带钢层流冷却温度控制模型的应用分析

 工业大学金属材料与加工重点实验室, 安徽 马鞍山 243002) 摘要：在带钢热轧后的冷却过程中，热轧带钢卷取温度的数学模型是至关重要的。介绍了某热轧带钢厂的卷取温度控制数学模型，针对传统的热轧带钢层流冷却卷曲温度控制中数学模型的固有缺陷，分别采用了差分方程和有限元数值模拟的方法，建立带钢厚度方向上的温度场。对测得的数据进行了分析，结果表明：在考虑带钢与介质的热交换的同时再考虑带钢内部的热传导大大提高模型的预报精度，为定量地描述计算值与实测值之间的偏差提供了依据。     

Ultra Fast Cooling of a Hot Steel Plate by Using High Mass Flux Air Atomized Spray

In the current research, the ultra fast cooling (UFC) of a hot stationary AISI‐304 steel plate has been investigated by using air atomized spray at different air and water flow rates. The initial temperature of the plate, before the cooling starts, is kept at 900°C or above. The spray was produced from a full cone internal mixing air atomized spray nozzle at a fixed nozzle to plate distance; and the average spray mass flux was varied from 130 to 370 kg m^?2 s by selecting different combinations of air and water flow rates. The surface heat flux and surface temperature calculations have been performed by using INTEMP software and the calculated results have been validated by comparing with the measured thermocouple data. The heat transfer analysis indicates that the cooling occurs in the transition boiling regime up to surface temperature of 500°C and thereafter it changes to nucleate boiling regime. The superposed flow of air on the hot plate enhances the cooling in the temperature range of 900–500°C by sweeping the partially evaporated droplets from the hot surface. However, due to the high percentage of fine water droplets in the resultant spray produced at higher air flow rates, the maximum cooling rate is achieved at the medium air flow rate of 30 N m³ h^?1. The cooling rate (182°C s^?1) produced by an air atomized spray is found to be in the UFC regime of a 6 mm thick steel plate. The findings of this research can be considered as the basis for the fabrication of cooling system in the run‐out table of a hot strip mill.     

Estimation of the Transient Surface Temperature,Heat Flux and Effective Heat Transfer Coefficient of a Slab in an Industrial Reheating Furnace by using an Inverse Method

In the steel industry it is of great importance to be able to control the surface temperature and heating or cooling rates during heat treatment processes. In this paper, a steel slab is heated up to 1300°C in an industrial reheating furnace and the temperature data are recorded during the reheating process. The transient local surface temperature, heat flux and effective heat transfer coefficient of the steel slab ares calculated using a model for inverse heat conduction. The calculated surface temperatures are compared with the temperatures achieved by using a model of the heating process with the help of the software STEELTEMP® 2D. The results obtained show very good agreement and suggest that the inverse method can be applied to similar high temperature applications with very good accuracy.