反向凝固与高温轧制过程中元素互扩散对复合界面的作用

在反向凝固与高温轧制过程中 ,母带与凝固层间一直进行着互扩散 ,C元素靠反应扩散由母带扩散到凝固层 ,Cr由凝固层扩散到母带 ,母带与凝固层之间存在明显的扩散层。Cr在母带中的扩散厚度约为 13μ。扩散到母带中的Cr和母带中的Fe形成固溶体 ,并析出Cr的碳化物。母带与凝固层界面实现了冶金结合     

热轧钢卷强制冷却工艺的研究

试验研究了热轧钢卷的强制冷却工艺过程 ,探讨了钢卷强制冷却工艺参数对带钢表面质量、力学性能及板形等的影响 ,认为卷取后采用间断式强冷工艺可获得较好的表面质量、较均匀的力学性能 ,并能明显缩短钢卷库存时间     

固结赤泥碾压坝排灰渣的试验研究

本试验研究，通过来统试验，确定固结破碎碾压赤泥的各种物理力学指标。成功地运用了固结赤泥进行破碎碾压筑坝，解决了生产中的燃眉之急，为同类企业充分利用现有堆场及设施提供了经验。     

钢球纵轧成形后滑的研究

基于钢球坯纵轧成形工艺,应用弹塑性有限元法,建立了钢球坯连轧成形的实体模型;模拟了轧件在成形过程中的速度场;通过实验研究了后滑的存在及其影响因素。     

两种类型活套的张力控制模型

介绍了带钢热连轧过程中电动活套和液压活套各自的张力控制模型，前者以电机电流作为控制对象，后者以液压缸压力作为控制对象。     

热轧窄带钢车间改造设计实践

介绍了将串列式、横列式热带生产线改造成半连续、３／４连续式生产线的设计实践。改造后可以连铸坯为原料，实现一火成材，并使卷重增加，产量和成材率提高。     

自粘聚合物改性沥青防水卷材胶粘剂

在SBS改性沥青防水卷材表面涂敷一层自粘性胶粘剂并以隔离纸覆盖，使用时撕掉隔离纸直接粘贴于屋面即可粘接密封牢，不但施工方便而且消除了熔融法施工造成的污染。该胶粘剂由沥青40％～65％，SBS 5％～30％，增粘剂2％～25％和助剂5％～25％构成。胶层具有可塑性、延展性，可自行填补屋面出现的裂缝，保证防水卷材的防水密封效果。     

Distributed receding horizon control of large-scale nonlinear systems: Handling communication delays and disturbances

This paper studies the robust distributed receding horizon control (DRHC) problem for large-scale continuous-time nonlinear systems subject to communication delays and external disturbances. A dual-mode robust DRHC strategy is designed to deal with the communication delays and the external disturbances simultaneously. The feasibility of the proposed DRHC and the stability of the closed-loop system are analyzed, and the sufficient conditions for ensuring the feasibility and stability are developed, respectively. We show that: (1) the feasibility is affected by the bounds of external disturbances, the sampling period and the bound of communication delays; (2) the stability is related to the bounds of external disturbances, the sampling period, the bound of communication delays and the minimum eigenvalues of the cooperation matrices; (3) the closed-loop system is stabilized into a robust invariant set under the proposed conditions. A simulation study is conducted to verify the theoretical results.     

Artificial neural network application for modeling the rail rolling process

Rail rolling process is one of the most complicated hot rolling processes. Evaluating the effects of parametric values on this complex process is only possible through modeling. In this study, the production parameters of different types of rails in the rail rolling processes were modeled with an artificial neural network (ANN), and it was aimed to obtain optimum parameter values for a different type of rail. For this purpose, the data from the Rail and Profile Rolling Mill in Kardemir Iron & Steel Works Co. (Karabük, Turkey) were used. BD1, BD2, and Tandem are three main parts of the rolling mill, and in order to obtain the force values of the 49 kg/m rail in each pass for the BD1 and BD2 sections, the force and torque values for the Tandem section, parameter values of 60, 54, 46, and 33 kg/m type rails were used. Comparing the results obtained from the ANN model and the actual field data demonstrated that force and torque values were obtained with acceptable error rates. The results of the present study demonstrated that ANN is an effective and reliable method to acquire data required for producing a new rail, and concerning the rail production process, it provides a productive way for accurate and fast decision making.