热连轧层流冷却系统设定模型的自适应

针对某热轧厂层流冷却系统的技术改造，建立了一套水冷及空冷的自适应温降模型，模型已通过模拟现场轧钢的ALPHA机上的离线集成测试，结果表明，这种具有自适应能力的水冷及空冷温降模型比以往采用单一综合换热系数的温降模型具有更高的稳定性和精度，实用性强，能够满足现场生产需要。     

定张减温降计算模型

在对轧制时钢管的温降原因进行分析的基础上，给出一种定张减温降计算模型，该模型考虑了辐射、接触传导、内部传导对温度的影响。通过对轧制实验测定得到钢管的温降数据与此模型实例计算的结果进行对比分析，表明该模型比较准确，能够满足生产实际的要求，可用于自动控制系统中定张减温降的计算，从而为控制系统比较准确地对轧机进行设定及调整提供依据。     

武钢1700 mm带钢热连轧精轧机组温降模型研究

对武钢1700mm热连轧计算机控制系统中现有的精轧机组温降模型进行分析，并且根据长期的实践经验及大量实测数据，用传热理论经优化带钢热连轧精轧机组温降模型。将模型的预报值与实测结果进行了比较，表明该温降模型可以用于带钢热连轧生产过程的温度预报中。该温降模型的现场应用证明预报值与实测值吻合良好。     

步进式加热炉的最佳控制

本文简要介绍了一种由最佳加热曲线、热状态模型、出炉钢坯温降模型、最佳设定值计算组成的加热炉最佳化控制系统。在本系统的控制下,当装炉钢坯品种规格变化大或轧线出现计划、非计划生产停顿时,仍能精确控制钢坯出炉温度和温度均匀性,达到提高产量和节约能源的目的。     

CVC四辊冷轧机板形预设定控制研究

预设定控制是一个完整的板形闭环控制系统中必不可少的重要环节，本文了一种具有自适应自学习功能的板形预设定控制模型，此模型已在宝钢冷轧厂的２０３０ｍｍＣＶＣ五机架冷连轧机上投入生产应用，控制效果良好。     

多模型自适应控制理论及应用

作为对经典自适应控制改进的控制方法,多模型自适应控制是解决复杂的大范围参数不确定系统的一种有效途径,并在理论和实践中取得了丰富成果。依据控制器集的不同综合策略,其被分为多种类型,本文旨在对加权型的多模型自适应控制进行综述。加权多模型自适应控制的基本思路是采用“分而治之”的办法,离线建立多个局部模型和对应的多个局部控制器,在线加权融合各个局部控制器的控制输出,从而形成全局控制,是实现鲁棒自适应控制的一类重要方法。首先比较详细地介绍了加权多模型自适应控制研究的历史及现状,然后给出相关研究的新进展和一些观点,包括新的加权算法和相应的加权多模型自适应控制系统的稳定性结果等,最后指出未来的几个研究方向。      

基于小波神经网络的通用模型自适应控制

提高控制系统鲁棒性的一种有效的方法是应用自适应控制.本文结合通用模型控制策略(Common Model Control-CMC),应用小波神经网络(Wavelet Neurall Network-WNN)自适应控制方法实现对被控对象的逆控制,从而提出基于小波神经网络的通用模型自适应控制(Common Modlel Adaptive Control-CMAC).基于小波神经网络的自适应控制器能产生复杂的控制规律,能更精确地逼近非线性被控对象,也克服了通用模型控制策略要求过程一阶微分模型应该有显式解的局限性.该控制策略的参考轨迹是一条典型的二阶曲线,仿真结果验证了该控制策略的有效性.     

25t转炉炉外钢水温降规律研究总结

炉外钢水温降数据是制定工艺，质量控制及生产组织的重要参数，文中通过对炼钢现场生产情况的调查和分析，系统地测试和分析了各种因素对温降的影响，初步得到了２５ｔ转炉炉外钢水温降规律并针对存在的问题提出了改进措施。     

900mm中宽带热连轧精轧机组温降模型研究

主要介绍了唐山建龙中宽带热连轧精轧机组的温降模型,结合耐候钢SPA-H的开发对温降数据进行了计算,实测数据与该温降模型计算数据基本接近.     

鱼雷罐车热量损失的影响因素及控制方法

鱼雷罐车在铁水运输过程中的温降严重影响产品质量和生产成本.目前对于鱼雷罐车运输过程温降的研究方法以模拟为主.本论文综述了前人对鱼雷罐车热损失影响因素的分析,总结了鱼雷罐车热损失的控制方法,并提出建立更加完整高效的在线控制模型是未来研究的主要方向.     

热连轧精轧设定模型及其优化方法研究

简要介绍了某厂热连轧生产线精轧过程设定模型,如温度模型、轧制力模型、变形抗力模型、前滑模型、辊缝模型及自适应模型等,并说明了相关模型参数优化方法和实际应用效果。     

Chance-Constrained Optimization-Based Parameter Estimation for Muskingum Models

The development of a chance-constrained optimization-based model for Muskingum model parameter estimation is presented. The desired Muskingum model parameters are to be useful to give the flood forecast in terms of expected flood for given limits of tolerance and probability of occurrence. When errors of observation occur, an error term is added to a mean flow to give the actual flow. The developed model minimizes the sum of squares of difference between the actual observed and computed outflows in order to determine the Muskingum model parameters. The constraints are the chance-constrained Muskingum flow routing equations. The first-order second moment method of chance-constrained optimization is used to develop the optimization model. The developed model is demonstrated for four scenarios of Muskingum model parameter estimation. The results show that, given the allowable limits of error in Muskingum model parameters, the developed model has a capability to give expected values of Muskingum model parameters when the historic data that are used for the parameter estimation process contain a specified amount of observation errors and obey a specified probability distribution. The chance-constrained optimization-based model for Muskingum model parameter estimation results into Muskingum model parameters that can give flood forecasts such that the forecasted flood allows the provision of better flood damage mitigation facilities.     

Hybrid Modeling for Soft Sensing of Molten Steel Temperature in LF

 Aiming at the limitations of traditional thermal model and intelligent model, a new hybrid model is established for soft sensing of the molten steel temperature in LF. Firstly, a thermal model based on energy conservation is described; and then, an improved intelligent model based on process data is presented by ensemble ELM (extreme learning machine) for predicting the molten steel temperature in LF. Secondly, the self adaptive data fusion is proposed as a hybrid modeling method to combine the thermal model with the intelligent model. The new hybrid model could complement mutual advantage of two models by combination. It can overcome the shortcoming of parameters obtained on line hardly in a thermal model and the disadvantage of lacking the analysis of ladle furnace metallurgical process in an intelligent model. The new hybrid model is applied to a 300 t LF in Baoshan Iron and Steel Co Ltd for predicting the molten steel temperature. The experiments demonstrate that the hybrid model has good generalization performance and high accuracy.     

Reduction-Based Model Updating of a Scaled Offshore Platform Structure

This paper attempts to develop a reduction-based model updating technique for jacket offshore platform structure. A reduced model is used instead of the direct finite-element model of the real structure in order to circumvent such difficulties as huge degrees of freedom and incomplete experimental data that are usually civil engineers’ trouble during the model updating. The whole process consists of three steps: reduction of FE model, the first model updating to minimize the reduction error, and the second model updating to minimize the modeling error of the reduced model and the real structure. According to the performance of jacket platforms, a local-rigidity assumption is employed to obtain the reduced model. The technique is applied in a downscale model of a four-legged offshore platform where its effectiveness is well proven. Furthermore, a comparison between the real structure and its numerical models in the following model validation shows that the updated models have good approximation to the real structure. Besides, some difficulties in the field of model updating are also discussed.     

常见的钛合金热变形本构模型分析及未来发展

概括总结了钛合金热变形本构模型的三种建立途径,分别介绍了并联概率模型、多项式模型、Arrhenius方程、动态回复与动态再结晶本构模型、Johnson-Cook模型、Zerrilli-Armstrong模型、人工神经网络模型等钛合金本构模型的建立方法、优缺点以及应用现状。结合材料的微观组织结构与宏观变形行为建立本构模型,统一本构模型建立方法及模型形式,依据具体实验条件修正本构模型,建立精确高效的计算系统将成为钛合金本构模型发展的主要方向。     

Hot Strip Laminar Cooling Control Model

The control model of laminar cooling system for hot strip, including air-cooling model, water-cooling model, temperature distribution model along thickness direction, feedforward control model, feedback control model and self-learning model, was introduced. PID arithmetic and Smith predictor controller were applied to feedback control. The sample of model parameter classification was given. The calculation process was shown by flow chart. The model has been proved to be simple, effective and of high precision.     

基于AutoCAD的露天矿三维建模与应用研究

露天矿三维地质模型是数字矿山建设中的信息平台,对露天矿的工程设计、生产管理有重要的指导意义。在AutoCAD平台下,以某露天矿为例,建立地质数据库,根据断层线构建断层线框模型,根据采场现状图和地形等高线构建地形模型,根据钻孔数据和内插点构建煤岩实体模型,实现了露天矿三维地质模型的可视化显示;根据煤岩实体模型建立块体模型,对块体模型添加属性、赋值,并将其应用到露天矿采剥工程量计算中,与传统算量方法相比,该方法操作简单,提高了计算的速度与精度。     

Development of a Kinetic Model for the Biosorption of Cationic Dyes by Dead Macrofungi

A new kinetic model has been proposed that describes the kinetics of the biosorptive processes. The proposed model is based on the concept of “available active sites.” The developed model has been investigated at different sorbent dose and temperature. Uptake of a cationic dye, Basic Violet 16 by a biosorbent prepared from the dead macrofungus, Fomitopsis carnea, has been considered to validate the model. This model has been used to determine the mass transfer coefficients under various sorption conditions. Sorbent concentration-time profiles generated by the model have been compared with the experimental data to validate the model. The model generated concentration profiles match the batch kinetic data closely.     

A critique of the correlated trait-correlated method and correlated uniqueness models for multitrait-multimethod data.

The correlated trait-correlated method (CT-CM) and correlated uniqueness (CU) confirmatory factor analysis models for multitrait-multimethod data are critiqued. Although the CU model often returns convergent and admissible factor solutions when the CT-CM model does not, the CU model is shown to have theoretical and substantive shortcomings. On the basis of this critique, the authors recommend that the CT-CM model be regarded as the generally preferred model and that the CU model be invoked only when the CT-CM model fails. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

枝晶凝固过程中的微观偏析半解析数学模型

基于典型微观凝固单元体内的溶质质量守恒,结合前人的研究工作,建立了一个适合于枝晶凝固方式的二元合金微观偏析半解析模型.本模型同时考虑了反向扩散和粗化对微观偏析的影响,并对枝晶臂间距的粗化直接进行计算,因此更为精确.若只考虑反向扩散的影响,本模型可以简化为BF模型形式;而如果只考虑粗化的影响,本模型可简化为Mortensen模型.本模型完整地统一了以BF模型为代表的反向扩散类模型和以Mortensen模型为代表的粗化模型.利用本模型同样可以对多元合金的微观偏析进行很好预测.以Fe-C-X（Si,Mn,P,S）合金体系为例对本模型的求解过程进行了详细的阐述.本模型可以很好地预测Al-4.9%Cu二元合金的共晶分数以及Fe-C-X（Si,Mn,P,S）多元合金体系的零强度温度和零塑性温度,并与实测值吻合良好.