The study of structure optimization of blast furnace cast steel cooling stave based on heat transfer analysis

The three-dimensional mathematical model of temperature and thermal stress field of cast steel cooling stave in a blast furnace has been modeled. Kinds of the parameters optimization of cast steel cooling stave in a blast furnace are proposed based on the heat transfer analysis. The results indicate that the values of the parameters optimization for a cast steel cooling stave are 200 mm for cooling channels interdistance, 25 mm for inner radius of the water channel, 180 mm for thickness of the cooling stave body, 70 mm for thickness of inlaid brick and 1.5 m/s for speed of cooling water. Reducing the water temperature would be uneconomical. The water temperature can be chosen according to the local conditions. The best choice for lining material is silicon nitrogen bond silicon carbide brick or silicon carbide brick.     

Numerical analysis on blast furnace performance with novel feed material by multi-dimensional simulator based on multi-fluid theory

Multi-dimensional blast furnace operation simulator based on multi-fluid theory and reaction kinetics is applied to the novel operations of blast furnace. The effective use of carbon composite agglomerates (CCB) in blast furnace is expected to have several advantages to improve furnace efficiency. In this study, mathematical expression of reduction behavior of CCB was introduced into the blast furnace simulator and the effect of charging CCB to blast furnace and accompanying temperature lowering were numerically examined. The calculation results showed the increase in productivity and decrease in reducing agent rate with CCB charging while reduction of iron-bearing materials was retarded due to temperature decrease in stack region. Thermal analysis revealed that this improvement of heat efficiency is caused by the decrease in heat requirements for solution loss, sinter reduction and silicon transfer reactions, heat outflow by top gas and wall heat transfer.     

Analyses on 3-D gas flow and heat transfer in ladle furnace lid

In order to verify the reasonableness of off-gas pressure and wall temperature, a mathematical model for gas flow and heat transfer in ladle furnace (LF) lid is developed based on 3-D Navier–Stokes equations and k–ε two equation turbulent models as well as energy conservation equation. The gas velocity vector distribution of skirt clearance between the top edge of ladle and furnace lid and electrode gaps between three graphite electrodes and furnace lid, the gas flow line distribution, pressure and temperature distribution on the furnace lid wall are simulated. Simulation results show that appropriate off-gas pressures are 200 Pa, 200 Pa and 150 Pa when electric arc emerges from molten steel surface and alloy hole is unsealed, electric arc emerges from molten steel surface and alloy hole is closure, electric arc immerges into molten steel surface and alloy hole is closure, respectively. The maximum temperature presents in the middle of LF lid in all of heating conditions, and the temperature value are 563, 603 and 343 K. Finally, the relations between gas volume and off-gas pressure are analyzed in different width of skirt clearance, and some relevant mathematical expressions are obtained. By comparing both simulation results and practical data, the advice on reducing off-gas pressure is proposed, and the maximum temperatures of furnace lid wall have good agreement with actual data.     

FEM analysis for residual stress prediction in hot rolled steel strip during the run-out table cooling

With the increasing demand of higher quality hot rolled strips, flatness defects occurred on the strips during the cooling process on the run-out table have received significant attention and should be considered in the online shape control model. Non-uniform temperature distribution and cooling across the strip width are the main reasons why the strip becomes unflatten after cooling process although the strip is rolled flat at the finishing mill. A thermal, microstructural and mechanical coupling analysis model for predicting flatness change of steel strip during the run-out table cooling process was established using ABAQUS Finite Element Software. In this model, Esaka phase transformation kinetics model was employed to calculate the phase transformation, and coupled with temperature calculation by means of the user subroutine program HETVAL. An elasto-plasticity constitutive model of the material, in which conventional elastic and plastic strains, thermal strain, phase transformation strain and transformation induced plastic strain were taken into account, was derived and realized using the user subroutine program UMAT. The conclusion that the flatness of the steel strip will develop to edge wave defect under the functions of the different thermal and microstructural behaviors across strip width direction during the run-out table cooling procedure was acquired through the analysis results of this model. The calculation results of this analysis model agree with the actual measurements and observation, therefore this model has a high accuracy. To better control the flatness quality of hot rolled steel strip, the shape compensation control strategy of slight center wave rolling is proposed based on the analysis result. This control strategy has been verified by actual measurements, and applied in actual production.     

基于Lyapunov指数的高炉铁水[Si]预报

通过对国内两座中型高炉冶炼过程的[S i]时间序列的混沌分析,计算出相应的Lyapunov指数谱.由最大Lyapunov指数为正,定量的说明了两座高炉冶炼过程具有混沌性,并估计了两座高炉冶炼过程[S i]可预测的时间尺度.同时根据最大Lyapunov指数,建立了高炉冶炼过程[S i]预报模型,取得了较好的结果.     

Optimal control of cooling process in continuous casting of steel using a visualization-based multi-criteria approach

This paper is devoted to the application of a new visualization-based multi-criteria approach in an optimal control problem related to the cooling process in the continuous casting of steel. The purpose is to develop such a control that results in steel of the best possible quality, that is, minimizes the defects in the final product. Since the constraints describing technological and metallurgical requirements result in an empty set of the feasible controls of the cooling process, the aim of the study is to find a control that violates the constraints as little as possible. The problem is formulated as a multi-criteria optimization problem and the constraint violations play the role of selection criteria.Our approach is based on the application of both a nonlinear mathematical model of the cooling process that features a system of partial differential equations, and a new decision support technique, called Interactive Decision Maps technique, that uses the on-line visualization of the non-dominated frontier.     

On an inverse problem arising in continuous casting of steel billets

In continuous casting of steel, the control of the solidification front by means of the amount of water sprayed onto the strand is of great practical interest. We study the thermal history in a continuously cast cylindrical billet. The mathematical model is a two-dimensional nonlinear heat equation div[k(u)gradu] = ut subject to water-cooling and heat radiation boundary conditions. We establish existence, uniqueness and stability results for both the temperature field and the solidification front. We study the monotonicity behaviour of the temperature field and show that certain technically easy-to-realize cooling-strategies may generate double liquid fingers at the final stage of solidification. The inverse problem of determining the cooling strategy is an ill-posed problem. We therefore use Tikhonov regularization as a stable and convergent methodfor treating this problem.     

Gas-powder flow in blast furnace with different shapes of cohesive zone

With high PCI rate operations, a large quantity of unburned coal/char fines will flow together with the gas into the blast furnace. Under some operating conditions, the holdup of fines results in deterioration of furnace permeability and lower production efficiency. Therefore, it is important to understand the behaviour of powder (unburnt coal/char) inside the blast furnace when operating with different cohesive zone (CZ) shapes. This work is mainly concerned with the effect of cohesive zone shape on the powder flow and accumulation in a blast furnace. A model is presented which is capable of simulating a clear and stable accumulation region in the lower central region of the furnace. The results indicate that powder is likely to accumulate at the lower part of W-shaped CZs and the upper part of V- and inverse V-shaped CZs. For the same CZ shape, a thick cohesive layer can result in a large pressure drop while the resistance of narrow cohesive layers to gas-powder flow is found to be relatively small. Implications of the findings to blast furnace operation are also discussed.     

爆炸和冲击载荷下金属材料及结构的动态失效仿真

通过数值模拟研究爆炸冲击载荷下金属材料和结构的动态失效规律,对表征爆炸冲击毁伤效应及设计新型抗冲击结构有重要意义.强动载下金属材料失效涉及材料大变形、热力耦合、材料状态变化等多个复杂物理过程,给数值仿真带来了极大挑战,其中包括裂纹、剪切带等复杂失效模式的几何描述、动态失效准则的确定、塑性与损伤耦合演化的描述等问题.针对...     

基于卷积神经网络的智能制造过程质量异常诊断

针对现有方法在智能制造过程中诊断能力有限和识别精度不高的问题,提出了一种与智能制造过程相适应的基于卷积神经网络的质量异常诊断模型。首先建立基于实时数据的过程质量图谱,以精准表达制造过程运行状态。其次,构建用于识别质量图谱的卷积神经网络诊断模型。最后,利用滑动窗口取值的方式对当前过程运行状态进行动态诊断,并通过某球磨过程验证了所提方法的有效性与实用性。结果表明,所提方法优于传统浅层模型,能够有效的对过程异常状态进行识别与诊断。     

Mathematical framework for predicting solar thermal build-up of spectrally selective coatings at the Earth’s surface

A transient finite element thermal model is formulated valid for surface coatings on any substrate material and based on the continuum conduction equations with solar loading as a heat source. The model allows cooling to be applied at outer surfaces of the body, by natural convection and accounts for ambient radiative heat loss. Hemispherical spectral reflectivities are obtained for various polymer-based coatings on a steel substrate using spectrophotometers in the 0.1 μm to 25 μm wavelengths. A time-dependent solar irradiation energy source (blackbody equivalent) is applied to an object with spectrally diffuse outer surfaces, and the incoming heat flux is split by a band approximation into reflected and absorbed energy and finally integrated over the complete spectrum to provide thermal source terms for the finite element model.     

Multiple crane scheduling in a batch annealing process with no-delay constraints for machine unloading

In this work, we focus on the scheduling of multi-crane operations in an iron and steel enterprise for a two-stage batch annealing process. The first stage is the heating process, and the second stage is the cooling process. To start the heating (cooling) stage, a special machine called a furnace (cooler) must be loaded. The real constraints of no-delay machine unloading are defined as follows: once the heating (cooling) is completed, the furnace (cooler) must be unloaded by crane immediately. The goal is to schedule limited machines (furnaces and coolers) operated by multiple cranes to minimize the completion time of the last annealed coil (makespan). We formulate a mixed-integer linear programming model to address this problem. Certain feasible properties are identified to avoid crane conflicts and ensure that the machine unloading no-delay constraints are met. Based on these necessary conditions, we then present a heuristic algorithm with running time in connection with the number of cranes, coils and machines. A lower bound to the problem is also developed. Through theoretical analysis, we show the worst-case bound of our heuristic algorithm. The average performances of the solution approaches are computationally evaluated. The computational results show that the proposed heuristic algorithm is capable of generating good quality solutions.     

主动冷却点阵夹层防热结构温度响应计算模型北大核心CSCD

针对点阵夹层结构主动热防护问题,建立了夹层结构面板和芯体导热与冷却剂对流耦合的非稳态传热理论模型,利用有限体积法离散控制方程并在MATLAB中进行了迭代求解.模型首次考虑了面板与夹芯杆之间的收缩热阻,并利用分离变量法得到了收缩热阻的近似解析解.基于单胞模型和周期性边界条件,模拟得到了模型所需的表面对流传热系数h_(b)和h_(fin).最后,选取多单胞计算工况进行数值模拟和理论模型对比,并讨论了收缩热阻对模型预测精度的影响.结果表明:理论模型能够准确预测夹层结构及内部流体的温度变化,理论与仿真之间的最大误差不超过1%;随着外加热流密度不断增大,忽略收缩热阻使得计算结果造成的误差不断增大;与数值模拟相比,理论模型可显著地减少计算时间并节省计算资源,尤其适用于非均匀、非稳态复杂热载荷下点阵夹层结构的温度响应计算.     

Coal blending models for optimum cokemaking and blast furnace operation

An important problem at an integrated steel-producing plant is the blending of different types of coals to make coke for the blast furnace operation. Historically, linear blending models were not appropriate because coal properties important for both optimum cokemaking and blast furnace operation do not combine linearly and are not completely understood. In this paper, a solution methodology is developed that utilizes two techniques: (1) a mixed integer linear programming model for blending the candidate coals to produce coke at a minimum cost and (2) binary decision tree analyses and results that are converted into model constraints to ensure the production of high-quality coke. Subsequently, the model results are used at the pilot-scale oven for testing and for validating the new, improved blend(s) that have been recommended by the model. This is an on-going need that is dictated by changing availabilities in both coal prices and sources. These steps reduce costs by both minimizing the number of blends to be tested at the pilot-scale facility and ensuring a minimum cost coal blend that is useable for the operating facilities. Hypothetical, but realistic, data are used to illustrate how the model performs.     

Prediction of temperature distribution and phase transformation on the run-out table in the process of hot strip rolling

In this paper a mathematical model based on the finite element method and the Scheil additivity rule is presented for predicting the temperature distribution and phase transformation behavior on the run-out table during the hot strip rolling of a low carbon steel. The model considers the austenite to ferrite and pearlite transformations, the temperature-dependent material properties of the cooling austenite as well as the austenite work hardening effect on the kinetics of austenite transformation. To determine the validity of the model predictions, the time-temperature histories of a low carbon steel rod in different cooling media were measured and also hot rolling experiments were performed. Good agreement between the predictions and the experimental results indicates the reliability of the model.     

A hybrid multi-objective artificial bee colony algorithm for burdening optimization of copper strip production

To achieve burdening process optimization of copper strips effectively, a nonlinear constrained multi-objective model is established on the principle of the actual burdening. The problem is formulated with two objectives of minimizing the total cost of raw materials and maximizing the amount of waste material thrown into melting furnace. In this paper, a novel approach called “hybrid multi-objective artificial bee colony” (HMOABC) to solve this model is proposed. The HMOABC algorithm is new swarm intelligence based multi-objective optimization technique inspired by the intelligent foraging behavior of honey bees, summation of normalized objective values and diversified selection (SNOV-DS) and nondominated sorting approach. Two test examples were studied and the performance of HMOABC is evaluated in comparison with other nature inspired techniques which includes nondominated sorting genetic algorithm II (NSGAII) and multi-objective particle swarm optimization (MOPSO). The numerical results demonstrate HMOABC approach is a powerful search and optimization technique for burdening optimization of copper strips.     

The use of artificial intelligence technique for the optimisation of process parameters used in the continuous casting of steel

The productivity and quality of a continuous caster depend mainly on process parameters, i.e. casting speed, casting temperature, steel composition and cleanliness of the melt, water flow rates in the different cooling zones, etc. This work presents the development of an algorithm, which incorporates heuristic search techniques for direct application in metallurgical industries, particularly those using continuous casting process for the production of steel billets and slabs. This is done to determine the casting objectives of maximum casting rate as a function of casting constraints. These constraints are evaluated with the aid of a heat transfer and solidification model based on the finite difference technique, which has been developed and integrated with a genetic algorithm. The essential parts of continuous casting equipment, which must be subjected to monitoring, as well as a methodology of mathematical model and physical settlements in each cooling region, are presented. The efficiency of the intelligent system is assured by the optimisation of the continuous casting operation by maximum casting rate and defect-free products. This approach is applied to the real dimension of a steel continuous caster, in real conditions of operation, demonstrating that good results can be attained by using heuristic search, such as: smaller temperature gradients between sprays zones, reduction in water consumption and an increase in casting speed.     

基于可信性安全准则的模糊动态投资组合模型

研究了模糊环境下的动态投资组合模型,将证券的收益率描述为模糊变量,提出了基于可信性测度的安全准则,可信性安全准则反映了投资者对灾难事件的容忍水平.建立了基于可信性安全准则的模糊动态投资组合模型,对建立的模型设计了基于模糊模拟的混合智能算法进行求解,并在Visual C++环境下,用C语言实现了对实例的求解,证明了混合智能算法的有效性和合理性.     

Incorporating dust lift-off into a CFD model of a blast furnace gravity dust-catcher

A gravity dust-catcher separates a mixture of dusts from the spent top gas flow of a blast furnace. These dusts are predominantly made up of limestone, iron ore and coke/coal. As a result of the turbulent gas flow patterns within a dust-catcher, modelling of the flow pattern can be very complex, attributed to the turbulent vortices that can be formed within the main body of the structure. Using data from an experimental prototype test rig, a simple model to capture the lift-off characteristics of particle lift-off from dust pile surfaces is created and incorporated into a computational fluid dynamics (CFD) model of the dust-catcher.The variation of particle separation performance over a typical blast furnace (BF) operational cycle is analysed. An attempt is made to explain the observed phenomena in terms of particle–fluid interaction. It is found that particle separation efficiency is largely unaffected by dust lift-off at low dust-catcher hopper fullness levels, but is significant at higher levels. It is found that the topography of the dust surface is important when predicting particle lift-off trends. It is concluded that this is due to the exposure experienced by a given particle when subjected to a surface velocity.