数值模拟温度场在中厚板轧后控冷过程的应用

介绍了为国内某中厚板厂设计开发的轧后加速冷却在线使用的控冷数学模型,包括空冷和水冷换热系数模型等,该控冷模型采用有限差分法计算钢板在冷却过程中沿钢板厚度和宽度方向的温度场分布.根据本模型计算轧后控冷温度场及进行控冷工艺参数的设定值,通过在线使用证明该控冷模型预报精度较高,与实测值偏差小,控冷钢板的板形和性能均达到设计要求,能够满足现场实际生产的需要.     

中厚板冷却过程高精度温度模型

实现高满意度轧后冷却控制目标必须依赖于轧后冷却过程控制系统高精度的温度场计算模型。以钢板内部热传导、空冷及水冷换热系数为主要研究对象,建立了轧后冷却数学模型,回归了空冷和水冷换热系数,采用Crank-Nicolson有限差分法求解钢板温度场。将该模型嵌入到国内某中厚板厂轧后冷却控制系统,对不同钢种不同厚度钢板进行轧后冷却试验,试验结果表明,实际终冷温度和目标终冷温度偏差±10℃的命中率在90%以上,很好地实现了冷却过程温度控制。     

中厚板轧后控冷数学模型研究

通过分析钢板的冷却过程,构建了中厚板控制冷却过程的数学模型,建立了冷却过程温度场计算的有限差分方程,并在理论分析的基础上确定了空冷、水冷换热系数模型及比热、热传导率的权重系数模型,同时结合现场实测数据,借助Matlab编程对模型进行了验证。结果表明,钢板温度偏差均控制在5℃以内,偏差率<1%,该模型具有较高的精度和准确性。     

小型H型钢超快冷“内并外扩”的有限元模拟

 超快速冷却对于H型钢的组织优化和性能提升具有重要的意义,冷却后的“内并外扩”是影响产品质量和生产稳定性的重要因素,也限制了超快速冷却工艺的推广和应用,在H型钢冷却过程中,换热系数是关键参数。为了研究换热系数对小型H型钢超快冷条件下“内并外扩”的影响,采用有限元模拟计算软件Abaqus建立了轧后冷却二维热力耦合模拟计算模型。考虑翼缘、腹板、R角处不同部位的冷却特点,将H型钢断面划分16个特定冷却特征区域并分别为其指定不同的换热系数,制定3个不同的冷却方案,分别进行模拟计算,得出温度场、应力场和上下翼缘宽度差,分析了温度场和应力场不均匀分布的特点。通过冷却试验模拟了小型H型钢轧后冷却过程,采用热成像仪获得冷却后的H型钢温度场。温度场与宽度差的计算结果与试验结果吻合良好。在此基础上分析了采用3种不同换热系数组合的冷却方案时上下翼缘横向、R角处纵向代表性特征截面上Mises应力与等效应变分布的规律,研究了R角处换热系数对翼缘扩并及上下翼缘宽度差的影响,发现R角处换热系数与上下翼缘宽度差具有线性关系,建立了描述其线性关系的数学模型。研究结果对于优化冷却方案以及提高小型H型钢超快速冷却的均匀性具有理论意义和参考价值。     

圆形喷口紊流冲击射流流动与传热过程数值模拟

中厚板无约束淬火主要采用上下集管圆形射流冲击冷却方式，使淬火钢板在向前行进的过程中得到冷却。本文通过建立单股圆形喷口紊流冲击射流流动与传热过程数学模型，对单股射流冲击热钢板的射流流场、温度场、压力场和自由液面进行了数值模拟，得到了冲击射流各物理场的变化规律及钢板表面的换热特性。数值计算结果不仅为钢板淬火过程的温度场模拟、热应力应变场模拟提供了较为准确的换热边界条件，也为优化钢板淬火控冷工艺、保证钢板淬火质量提供了坚实的理论基础。     

中厚板超快速冷却条件下的温度模型

 结合中厚板轧后超快速冷却的工业实践,以传热学为基础,利用有限元法开发了中厚板轧后超快速冷却过程的一维温度场模型。为了同时满足在线模型的精度和实时性要求,在建模过程中采用了逐层细分法对钢板的厚向进行表面密集、心部稀疏的离散化处理;在求解过程中采用了变步长模型对时间步长进行动态调整。将该模型应用于工业现场,获得了钢板在超快速冷却条件下的水冷温降曲线和瞬时温度分布。现场应用表明,钢板终冷温度的计算值与实测平均值吻合较好,两者的偏差在±15℃以内,满足了新一代TMCP工艺的生产需求。     

控冷工艺参数对中厚板均匀冷却的影响

 确定了中厚板ACC冷却系统的换热边界条件,建立了钢板温度场有限元计算模型,利用现场实测数据对模型计算结果进行了验证,并且分析了不同冷却工艺参数包括集管开启方式、辊道速度以及冷却介质温度对钢板终冷温度、返红温度以及温差的影响规律,从而为实际生产中提高钢板控冷过程中的冷却均匀程度提供理论依据。     

k-NN自学习模型在中厚板轧后冷却温控中的应用

<正>在中厚板生产过程中,轧后冷却对钢板的最终质量起到了至关重要的作用,因此,建立更为精确的温度控制模型来实现预设冷却规程并满足目标终冷温度是中厚板轧制领域关注的重要问题。终冷温度是决定中厚板组织性能的关键工艺参数之一。换热系数是温度控制模型的核心参数,由于其影响因素多且复杂,故很难有一个固定的模型来计算。提出一种简单有效的换热系数的自     

厚规格钢板在ACO中极限冷却速度研究

通过数值模拟方法对钢板冷却过程温度变化进行研究,分析冷却速度随换热系数的变化规律.结果表明,随着表面换热系数增大,冷却速度呈S形,逐渐达到一稳定值.随着换热系数的增大,当冷却结束时,钢板表面温度接近于冷却水温度,冷却速度达到极限值.极限冷却速度远大于加速冷却和超快速冷却的冷却速度.极限冷却速度随钢板厚度的增大、开冷温度升高和终冷温度的降低而减小.冷却水温度对极限冷却速度影响较小.     

[k-NN]自学习模型在中厚板轧后冷却温控中的应用

 在中厚板生产过程中,轧后冷却的温度控制是决定产品组织性能的关键工艺技术。换热系数是温度控制模型的核心参数,由于其影响因素多且复杂,故很难有一个固定的模型来计算。提出一种简单有效的换热系数的自学习模型：先通过参数节点化和插值法得出全范围内的各换热系数影响因素的特征值;再基于[k-NN]原理,寻找待冷目标钢板与各已冷样本钢板之间的相似度;最后,通过IDW加权平均算法,预估出目标冷却钢板所需的换热系数。现场实际的应用情况表明,使用该自学习模型相比以往可提高控制精度约5%。     

The Influence of Oxide Scale on Heat Transfer during Reheating of Steel

The present work presents methodology and development of a mathematical model for prediction of the influence of oxide scale on heat transfer during reheating of steel in an industrial furnace. In this developed model, temperatures inside the steel billet were measured and with thermocouples at selected places and were collected by a water cooled computer that was traveling inside the slab. CFD is used to calculate the flow field inside of a furnace. The mass‐transfer coefficient of the scale formation is obtained by solving the convection mass‐diffusion equation across a boundary layer to the surface of a flat plate. A model for inverse heat conduction is employed to calculate the local surface temperature and heat flux on top of the growing oxide scale layer on a slab moving through a walking beam reheating furnace. By using the inverse method, the transient temperature and heat flux was firstly determined on the surface of the steel. During subsequent computations, the growth of the scale was calculated and the surface temperature of the oxide scale was extracted by using the Cauchy data from the previous calculations. The sensibility of the model on steel physical parameters is studied, and suitable parameters were obtained for heating a low carbon steel plate in the reheating furnace. Results show that the oxide scale layer should not be neglected in reheating models.     

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.     

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In order to solve the problems of time-consuming and intense vibration during the calculation process of inverse heat conducting problem (IHCP) with conjugate gradient method (CGM), a non-iterative model was developed based on finite element method (FEM) and related program code was compiled with Fortran. This non-iterative method was then applied to IHCP of laminar cooling process of hot rolled steel plate to calculate the convective heat transfer coefficient in the boundary. Through comparison of the convective heat transfer coefficient obtained by both CGM and the non-iterative method, the results were shown to be consistent with each method. Furthermore, the computing result of the non-iterative method were more stable, and had an obviously faster speed, which eventually cut down the whole computing by 76%. The new method could retain high sparsity of the matrix, which is more concise than the exiting non-iterative method. Besides, the new non-iterative method could also be an efficient way to calculate the heat flux and wall temperature at the same time, which made it possible for real-time output of boundary conditions during laminar cooling process of hot rolled steel plate.     

改善中厚板轧后超快冷均匀性的措施及其应用

 以改善中厚板轧后冷却均匀性为目的,从高压水射流冲击换热原理出发,研究在超快速冷却条件下的改善钢板冷却均匀性方法。通过合理设计集管及其布置形式,采用上集管位置设定、水比设定以及钢板头尾速度遮蔽等措施,实现了在超快速冷却过程中钢板各个方向上的冷却均匀性。将上述措施用于在线生产,结果表明,钢板各向均匀性控制良好,长度方向95%以上的温度被控制在距离目标返红温度±25℃的范围之内。     

中厚板加热炉板坯温度控制模型研究与优化

板坯温度控制模型是加热炉过程控制的核心,主要任务是根据生产工艺和相关数学模型控制、协调和优化获得加热质量较好的板坯。针对中厚板加热炉过程控制的板坯加热环节多变量和温度预报不精准等问题,选取了热流密度和热物性参数,并结合有限差分法建立的二维差分模型,对板坯温度控制模型进行了优化。将优化后的模型嵌入到在线燃烧二级自动控制系统,主要现场应用效果为加热炉各段的温度稳定度在±10 ℃以内,板坯的开轧工艺温度合格率达到了98.28%,煤气节能率提高了5.56%,氧化烧损率降低了15.05%。通过现场应用效果可知,优化后的板坯温度控制模型在节能降耗的基础上,获得了加热质量较好的板坯,为各钢厂加热炉实际生产提供了重要的参考依据。     

冷却工艺对高速连铸结晶器传热的影响

 为了分析冷却水的供水工艺对结晶器铜壁和冷却水温度场的影响,基于结晶器铜壁热电偶实测温度,构建铸坯/铜壁传热反问题和铜壁/冷却水正问题数学模型,采用ANSYS建立铸坯/铜壁/冷却水数值分析模型,对薄板坯结晶器温度场进行耦合传热分析,解析不同冷却工艺对高速薄板坯连铸结晶器内传热行为的影响。结果表明,水缝内冷却水流动方向对铜壁温度场具有显著影响,采用自上而下“反向供水”,比常规冷却工艺时铜壁热面温度峰值降低117 ℃,铜壁侧冷却水最高温度降低24 ℃,有效改善铜板工作状态,抑制冷却水局部沸腾趋势。提高冷却水速度可以进一步降低铜壁和冷却水温度,冷却水温度对铜壁温度场影响较小。     

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.