Optimization of Holding Temperature and Holding Thickness for Controlled Rolling on Plate Mill

来源 :钢铁研究学报(英文版) | 被引量 : 0次 | 上传用户:ash0
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
Holding temperature and holding thickness are main parameters for two-phase controlled rolling on plate mill. The optimization of holding temperature and holding thickness for pass schedule calculation of two-phase controlled rolling on plate mill was presented and its feature is as follows: (1) Determination of holding thickness can be automatically obtained based on the influence of mill safety limits, tracking zone length and holding time on holding thickness; (2) Determination of holding temperature can be automatically obtained and the holding time can be reduced as much as possible; (3) Algorithm can modify the holding temperature and thickness depending on slab size and product size.
其他文献
用Faddeev-Jackiw(FJ)方法对与规范场偶合的规范自对偶场进行了研究,获得了一个新的辛Lagrangian密度,导出了此系统的FJ广义括号,并对其进行了FJ量子化.进而把FJ方法和Dirac
To evaluate the potentiality of applying gene therapy to endotoxemia in high-risk patients, we investigated the effects of transferring an adeno-associated viru
Two new coordination polymers, [M(phen) (e, a-cis-1, 4-chdc) (H2O) ] n (M=Mn(1);M=Cu(2);chdc=cyclohexanedicarboxylic acid;phen=1, 10-phenanthroline), were prepa
Based on Chen et al. (2006), the scheme of the combination of the pentad-mean zonal height departure nonlinear prediction with the T42L9 model prediction was de
To study load transfer mechanism and bearing capacity of a mixed pile with stiffness core (MPSC), which is formed by inserting a precast reinforced concrete pil
We determine the asymptotic order of entropy number and optimal non - linear approximations of anisotropic periodic Besov class of Brpθ(Td) (1≤p≤∞, 1≤θ≤
设计了双层LSO晶体和位置灵敏型光电倍增管耦合构成的用于小动物PET成像的深度编码探测器.众所周知,晶体的不同的表面处理影响着光输出量,进而影响着它们构建的PET探测器的性
This paper will correct some gaps existing in the proof of a theorem written in an earlier paper by the author on the lower bounds for sums of BDH type publishe
A learning-based deformable registration method was presented for MR brain images. First, best geometric features are selected for each location and each resolu