Numerical analysis for the multi-phase flow of pulverized coal injection inside blast furnace tuyere

The pulverized coal injection (PCI) system was modified from single lance injection into double lance injection at No. 3 Blast Furnace of CSC. It is beneficial to reduce the cost of coke. However, the injected coal was found very close to the inner wall of the tuyere during the operation, such as to cause the possibility of erosion for the tuyere. In this study a three-dimensional mathematical model has been developed based on a computational fluid dynamics software PHOENICS to simulate the fluid flow phenomena inside blast furnace tuyere. The model was capable of handling steady-state, three-dimensional multi-phase flow of pulverized coal injection. The model was applied to simulate the flow patterns of the injection coal inside the tuyere with two kinds of lance design for the PCI system. The distribution of injection coal was simulated such as to estimate the possibility of erosion for the tuyere. The calculated results agreed with the operating experience of CSC plant and the optimum design of double lance was suggested. The model was also applied to simulate the oxygen concentration distribution with these different oxygen enrichments for the coal/oxygen lance system. The calculated results agreed with the experimental measurement. These test results demonstrate that the model is both reasonably reliable and efficient.     

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.     

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.     

An advanced dynamic process model for industrial horizontal anode baking furnace

The global aluminum industry is facing new challenges due to new technological developments. Carbon anodes, consisting of mainly petroleum coke and coal tar pitch, are used in the electrolytic production of aluminum. High amperage utilization in the electrolytic cells with the objective of increasing production requires high quality carbon anodes. The anode quality depends both on raw material quality, anode recipe as well as forming and baking conditions of anode manufacturing process. The cost of the baking process constitutes 15 to 25% of the total aluminum production cost [1]. The industrial challenge is to produce better quality anodes consuming less energy, and reducing environmental emissions.A transient two dimensional (2D⁺) process model for horizontal anode baking furnace was developed during this study. The main objective was to develop an efficient furnace model with low computation load and time, using the transient Finite Difference Method and simplified furnace geometry. The model represents several phenomena involved during the anode baking process such as heat transfer (convection, radiation and conduction), fuel combustion, volatile matter (tar, methane and hydrogen) generation and combustion, air infiltration and energy loss to the atmosphere from the walls, the top of the furnace and the foundation. The model was developed using two coupled sub-models; the first one describes the thermal conduction through the solid materials (brick refractory wall, packing coke and anode block) as well as the volatile release, and the second one describes the gas flow, heat and mass transfer as well as the combustion of fuel and volatiles in the flue. Compared to the existing process models (where the gas flow in flue is assumed as unidirectional along the horizontal furnace direction), the present model also considers the gas flow in vertical direction and uses four vertical planes per pit section to predict the temperature of the solids. The model predicts 2D temperature distribution within the flue gas (xy plane) and the pit solid materials (yz plane) allowing then the prediction of the pseudo tridimensional distribution of the solid temperature. This model is a useful tool for the continuous monitoring of anode temperature and studying of the horizontal anode baking furnace behaviour. The effect of any change in operational parameters and the energy consumption on the furnace operation can be predicted.     

A knowledge-based multi-role decision support system for ore blending cost optimization of blast furnaces

Literature illustrates the difficulties in obtaining the lowest-cost optimal solution to an ore blending problem for blast furnaces by using the traditional trial-and-error method in iron and steel enterprises. To solve this problem, we developed a cost optimization model which we have implemented in a multi-role-based decision support system (DSS). On the basis of analyzing the business flow and working process of ore blending, we propose an architecture of DSS which is built based on multi-roles. This DSS construction pre-processes the data for materials and elements, builds a general database, abstracts the related optimal operations research models and introduces the reasoning mechanism of an expert system. A non-linear model of ore blending for blast furnaces and its solutions are provided. A database, a model base and a knowledge base are integrated into the expert system-based multi-role DSS to meet the different demands of data, information and decision-making knowledge for the various roles of users. A comparison of the results for the DSS and the trial-and-error method is provided. The system has produced excellent economic benefits since it was implemented at the Xiangtan Iron & Steel Group Co. Ltd., China.     

Convexity analysis in detecting a steel plant hidden global optimum

This case study demonstrates the value of classical analysis and to a lesser degree, system decomposition for finding a global optimum missed by a sequential linear programming scheme which converges to a non-global local minimum. The example is a 20 variable steelmaking problem in which the variable annual cost to be minimized is linear, as are all constraints except a non-convex one in each blast furnace. The sequential linear programming method gives a provenlocal minimum, although the non-convex nonlinearity prevents any proof of global optimality. The provenglobal minimum found here has a 4% lower cost. The local minimum costs only 0.2% per annum less than the rather flat global maximum, so the original local minimization only achieved about 5% of the economy possible. In the overall plant, the cost saving is over three million US$ (1972) annually.Symbol Name of variable H combined hot iron rate (X ₄ + X ₄) - r ₁,r ₂ sinter/iron ratio for BF1 and BF2 - u ₁,u ₂ unit composition cost variation for BF1 and BF2 - v ₁,v ₂ variable feed cost for BF1 and BF2 - v _b(H) total variable feed cost for both blast furnaces - v _s (H) total variable cost for both steel furnaces - x ₁ sintered iron ore rate into BF1 - x ₂ pelleted iron ore rate into BF1 - x ₃ coke rate into BF1 - X ₄ hot iron rate from BF1 - x ₅ sintered iron ore rate into BF2 - x ₆ pelleted iron ore rate into BF2 - x ₇ coke rate into BF2 - X ₈ hot iron rate from BF2 - x ₉ hot iron to basic oxygen furnace (BOF) - x ₁₀ home scrap to BOF - x ₁₁ bought scrap to BOF - x ₁₂ silicon carbide to BOF - x ₁₃ crude steel from BOF - x ₁₄ home scrap to open-hearth furnace (OH) - x ₁₅ bought scrap to OH - x ₁₆ hot iron to OH - x ₁₇ crude steel from OH - x ₁₈ total crude steel - x ₁₉ total home scrap - x ₂₀ total bought scrap - Y ₁,Y ₂ additional hot iron from BF1 and BF2     

Stochastic optimization for blending problem in brass casting industry

A critical process in brass casting is blending of the raw materials in a furnace so that the specified metal ratios are satisfied. The uncertainties in raw material compositions may cause violations of the specification limits and extra cost. In this study, we proposed a chance-constrained stochastic programming approach for blending problem in brass casting industry to handle the statistical variations in raw material compositions. The proposed approach is a non-linear mathematical model that is solved global optimally by using GAMS/BARON solver. An application has been performed in MKEK brass factory in Kırıkkale, Turkey and the solution of the application has been compared with alternative solution approaches based on cost and specification violation risk conditions. This comparison demonstrates that the proposed model is the most effective solution approach for managing stochastic uncertainties in blending problems and successfully can be used other industries such as alloy steel or secondary aluminum production.     

Study on intelligent monitoring methodology based on the mathematical model of heat transfer for blast furnace stave

In order to monitor the thermal status of a blast furnace stave, an intelligent simulation technique is developed. The intelligent simulation model is built using a combined model based on the mathematical model of heat transfer and the technique of artificial intelligence. The intelligent simulation model of blast furnace cast steel stave is based on correction factor of parameters obtained by training the samples of test data of the cast steel cooling stave. Simulating currently existing blast furnace stave situation which is only a monitoring point on the stave and the velocity and temperature of cooling water are difficult to real-time be detected, the experimental verification of the model is done. The results show that the data of intelligent simulation model is nearly consistent with that of experiment. The model of high accuracy can on-line predict the thermal status of blast furnace stave.     

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.     

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.     

Three-dimensional simulation of the pulverized coal combustion inside blast furnace tuyere

A three-dimensional multi-phase model using Eulerian approach has been developed to simulate the coal heat transfer, devolatilization and combustion process inside a blast furnace tuyere. The information including velocity field, temperature distribution and combustion characteristics has been obtained in details and the effect of coal particle diameter, coal type and coal injection angle on the pulverized coal combustion process has been presented. The predicted results show that the coal combustion process inside tuyere are affected by coal particle size, coal type and coal injection angle. For the smaller coal particle diameter, the volatile matter released from the coal more rapidly, this results in a higher coal burnout at the exit of the tuyere. The coal burnout is depended on the coal volatile matter content; a higher coal burnout will be obtained for the coal with a higher volatile matter content. The coal injection angle affects the flow patter inside the tuyere, which results in a different mixing and burning process of the pulverized coal. When the coal diameter changes from 30 μm to 90 μm, the coal burnout decreases from 51.03% to 44.21%; when the coal volatile matter is reduced from 34.32% to 19.95%, the coal burnout decreases from 46.04% to 35.02% and for the coal injection with an angle, the coal burnout is 46.04%, a little bit higher than that of 44.51% without injection angle.     

Circumferential burden distribution behaviors at bell-less top blast furnace with parallel type hoppers

It is of critical importance to master the circumferential burden distribution behaviors at bell-less top blast furnace with parallel type hoppers, targeting to reduce the uneven degree (UD) of burden distribution along the circumference. Combining with the burden motion conditions, both circumferential falling point (FP) and mass flow (MF) models are established in present work to determine the basic distribution behaviors systematically. The results show that the positive amplitude of either FP or MF is not equal to the negative counterpart in the circumferential direction. Besides, the UD of MF is nearly 10 times as large as that of FP, which could be ignored in actual production. After validating the circumferential MF model against both laboratory and industry-scale measurements from previous literatures, alternating the hoppers while keeping the same chute rotating direction in burden charging process is considered as the best countermeasure to promote even burden circumferential distribution at bell-less top blast furnace with parallel type hoppers.     

Optimal order size to take advantage of a one-time discount offer with allowed backorders

In this paper, we develop an inventory model for determining the optimal ordering policies for a buyer who operates an inventory policy based on an EOQ-type model with planned backorders when the supplier offers a temporary fixed-percentage discount and has specified a minimum quantity of additional units to purchase. A distinguishing feature of the model is that both fixed and linear backorder costs are included, whereas previous works include only the linear backordering cost. A numerical study is performed to provide insight into the behavior of the model.     

Scheduling at coal handling facilities using Simulated Annealing

The main thrust of this study is the operational scheduling of the continuous coal handling and blending processes when considering multiple, and sometimes conflicting, objectives. A widely applicable generic goal programming model is proposed. Furthermore, assumptions regarding the certainty of demand during different periods are challenged, endeavoring to provide more robust schedules in a largely stochastic environment. As the study aims to provide scheduling solutions to any coal handling facility, the Simulated Annealing metaheuristic is proposed to ensure that acceptably good solutions for large instances of the generic model can be found in reasonable computational time. The generic approach and its suggested application will be valuable not only in the coal handling environment, but also in the continuous product manufacturing/blending or continuous material handling environment.     

多周期多种设备公用工程系统优化模型的改进及应用

本文提出了多周期多种设备公用工程系统改进的混合整数双线性优化模型,它含有两种优化变量和系统运行过程的离散动态约束,期望系统总设备投资(含设备折旧)与全周期运行操作费用之和最小。针对改进优化模型求解上的困难,给出将改进优化模型分解成有限多个关于连续变量的线性规划。论述了改进优化模型与分解模型的等价性以及两种模型的主要数学性质,并在此基础上提出了求解策略。最后将改进优化模型应用于某石化企业的蒸汽动力系统最优设计与运行优化集成实例。     

Multiobjective stochastic programming for feed formulation

The minimum cost linear programming model used traditionally for feed formulation does not take account of variability of nutrients in feed ingredients. Therefore, it may be that the nutrient requirements of the animal are not adequately met. In this paper, we show how a multiobjective stochastic model that permits confronting the cost of the ration with the probabilities of meeting the nutrient requirements of the animal can enhance the process of animal diet formulation. The model presented here does not require any a priori information from the decision maker, eliciting his preferences through an interactive process. This is the main advantage in relation to other models found in the literature for treating the problem of nutrient variability, which introduce stochastic constraints in the single objective minimum cost model requiring fixing the level of probability desired for each one of the nutrients in advance.     

Modelling and optimisation of electricity,steam and district heating production for a local Swedish utility

District heating may help reduce environmental impact and energy costs, but policy instruments and waste management may influence operations. The energy system optimisation model MODEST has been used for 50 towns, regions and a nation. Investments and operation that satisfy energy demand at minimum cost are found through linear programming. This paper describes the application of MODEST to a municipal utility, which uses several fuels and cogeneration plants. The model reflects diurnal and monthly demand fluctuations.Several studies of the Linköping utility are reviewed. These indicate that the marginal heat cost is lower in summer; a new waste or wood fired cogeneration plant is more profitable than a natural-gas-fired combined cycle; material recycling of paper and hard plastics is preferable to waste incineration from an energy-efficiency viewpoint; and considering external costs enhances wood fuel use. Here, an emission limit is used to show how fossil-fuel cogeneration displaces CO₂ from coal-condensing plants.     

A strategy for an efficient simulation of countercurrent flows in the iron blast furnace

A recently developed anisotropic Ergun equation for layered porous media is embedded into equations characterizing a chemically inert, axially symmetric model of the iron blast furnace. A novel transformation is used to deal with the furnace geometry, and additional modifications cater for convection, heat transfer, and the softening and melting of the iron ore. The equations are identified as examples of a generic convection-anisotropic diffusion problem, and a modular solution method is proposed for both single- and double-phase cases. The result is an algorithm that is significantly more efficient than existing techniques. It is used to demonstrate some features relating the gas distribution to the shape, structure, and location of the cohesive zone.     

A two-dimensional strip cutting problem with sequencing constraint

We study a strip cutting problem that arises in the production of corrugated cardboard. In this context, rectangular items of different sizes are obtained by machines, called corrugators, that cut strips of large dimensions according to particular schemes containing at most two types of items. Because of buffer restrictions, these schemes have to be sequenced in such a way that, at any moment, at most two types of items are in production and not completed yet (sequencing constraint). We show that the problem of finding a set of schemes of minimum trim loss that satisfies an assigned demand for each item size is strongly NP-hard, even if the sequencing constraint is relaxed. Then, we present two heuristics for the problem with the sequencing constraint, both based on a graph characterization of the feasible solutions. The first heuristic is a two-phase procedure based on a mixed integer linear programming model. The second heuristic follows a completely combinatorial approach and consists of solving a suitable sequence of minimum cost matching problems. For both procedures, an upper bound on the number of schemes (setups) is found. Finally, a computational study comparing the quality of the heuristic solutions with respect to an LP lower bound is reported.