Distribution Of Process Variables Research Articles

Roasting Process in a Pellet Shaft Furnace

Background: The pellet shaft furnace is widely used to roast pellets, which is essential for the blast furnace burden structure; however, the study on the roasting process in the pellet shaft furnace is very critical for obtaining high-quality pellets. Objective: A theoretical model of the pellet roasting process in the pellet furnace (8 m2) has been developed on the basis of reaction engineering. The present study aims at investigating the roasting process in the pellet shaft furnace by taking into account gas flow and heat transfer so that a reasonable structural design for the shaft furnace can be obtained. Methods: A numerical model for an 8m2 pellet shaft furnace has been developed on the basis of reaction engineering by taking into account gas flow, heat exchange between pellets and gas, and oxidation reaction of pellets. Results: The results show that four reaction zones (preheating, roasting, soaking, and cooling) exist obviously in the pellet shaft furnace. About 80% coolant gas flows through the gas coolant passage in the roasting zone, and the non-uniformity of coolant gas in the cooling zone exists under normal operative conditions. Furthermore, effects of some operation conditions on the distributions of process variables in the furnace are also examined. The numerical results are in agreement with industrial experiment results. Conclusion: The results reveals that the non-uniform flow of gas occurs in the cooling zone. The non-uniform flow of gas greatly affects the cooling effect. The present results can provide a theoretical basis for the prediction of the furnace process, the optimization of operation and the rational design of furnace shape. At the same time, the present work is helpful in realizing the automatic control and computer management of furnace production. In the future, the movement of pellets should be observed by means of a visualized model experiment to verify that the descending movement of pellets is approximately a potential flow in the furnace and piston flow except for the cooling zone. In addition, the experimental study of a single pellet under a widely varying range of conditions should be carried out to investigate the controlling step of oxidation reaction for pellets in the furnace.

A dynamic sampling for monitoring nonparametric multivariate processes

In the context of big data, multivariate processes must often be monitored in a timely and accurate manner. Usually, the distribution of process variables is unknown. This paper proposes a new strategy for multivariate process monitoring when the distribution of a process variable is unknown. We address monitoring by means of a rank-based method that is completely nonparametric. We also discuss the optimal strategy of parameters. A simulation study demonstrates that the proposed method is efficient in detecting shifts for multivariate processes. A real data example is presented to illustrate the performance of the proposed method.

CFD simulation of two-phase gas-particle flow in the Midrex shaft furnace: The effect of twin gas injection system on the performance of the reactor

In the present study a mathematical model is developed to examine the effect of dual gas injection system on the distribution of process variables and energy consumption in the Midrex shaft furnace. The developed model was constructed by considering the major chemical reactions and physical structures within the furnace and describes a counter-current moving bed reactor in which hematite pellets are reduced to sponge iron by pure hydrogen gas. Governing equations containing overall continuity, momentum, energy and mass equations are developed for both gas and solid phases in cylindrical coordinate system. Unreacted shrinking core model is implemented to simulate gas–solid reactions in the reactor. The complicated equations are solved by applying finite volume technique. The model is applied to simulate multiphase flow inside the reactor when it is equipped with one and two hydrogen gas intake ports to examine the impact of gas injection arrangement on the process variables. The radial and axial distributions of operational parameters including gas and solid temperature, fractional reduction of iron oxides and hydrogen and water vapor concentration are obtained for both cases. The results indicate that reduction degree and energy consumption are improved by utilizing dual gas injection system.

A Non-optimality Detection Technique for Continuous Processes

This paper develops a novel non-optimality detection technique for continuous processes based on the theory of process monitoring. Since the optimal statuses have some common features so as to satisfy optimality necessary conditions, the distributions of process variables are found to fall in some subspace that is determined from the disturbances. To detect those statuses that are not optimally operated, non-optimality is considered as a special kind of process fault. An equivalent interpretation is also provided to demonstrate the rationale of proposed analogy. For illustration, the principal component analysis (PCA) is particularly employed as a detection tool, whose effectiveness is verified through an exothermic reactor example.

Detailed Dynamic Modeling of a Molten Carbonate Fuel Cell Stack with Indirect Internal Reformers

AbstractA detailed dynamic model of a molten carbonate fuel cell (MCFC) stack that can predict the distribution of process variables over the cell surface and along the stacking direction is presented. The model describes a repeating unit of the stack, which is composed of eight cells and one indirect internal reformer (IIR). The set of partial differential equations for the MCFC model is reduced to a set of ordinary differential equations through discretization using the cubic spline collocation method and the finite difference method. The steady‐state and dynamic behaviors of the eight‐cell stack model are compared with those of the one‐cell model, which has been commonly used in previous studies on MCFC dynamics, and three‐cell aggregate model. The distribution of the process variables along the stacking direction cannot be disregarded, and thus more detailed model should be used for the accurate reproduction of MCFC dynamics.

Multivariate EWMA control charts for monitoring the variance-covariance matrix

We know that the exponentially weighted moving average (EWMA) control charts are sensitive to detecting relatively small shifts. Multivariate EWMA control charts are considered for monitoring of variance-covariance matrix when the distribution of process variables is multivariate normal. The performances of the proposed EWMA control charts are evaluated in term of average run length (ARL). The performance is investigated in three types of shifts in the variance-covariance matrix, that is, the variances, covariances, and variances and covariances are changed respectively. Numerical results show that all multivariate EWMA control charts considered in this paper are effective in detecting several kinds of shifts in the variance-covariance matrix.

Analysis of strain stress state in roller compaction process

The process of drawing and densification of powdered microcrystalline cellulose by roller press in a steady state operation is analyzed using a 2D modeling with the finite element method and the modified Drucker–Prager Cap model as material behavior. Distributions of process variables in contact surface between powder and roller such as pressure, shear stress and relative speed were predicted and used to analyze the basic mechanisms of the transport and the densification of powder between rolls. The results show clearly the existence of three contiguous zones: a phase where the powder is drawn between rolls by a sliding mechanism, a sticking phase where the powder is transported with the same velocity as the roll and where the densification by deforming the powder bed is achieved under the increase of roll pressure that reaches its peak before the neutral angle. The formed compact is then expulsed out of the gap by a slip mechanism resulting from the change of the sign of the shear stress. The predicted density distribution between the rolls, shows a gradual increase. The density reaches its maximum before the neutral point and shows values in agreement with the density of strips prepared with an instrumented roll press. The effect of varying the material parameters on the maximum pressure and the nip angle is also investigated. Beyond the description of the basic mechanisms of roller compaction, this modeling shows a real potential of the optimization of the roller compaction process.

Online Probabilistic Assessment of Operating Performance Based on Safety and Optimality Indices for Multimode Industrial Processes

Operating performance of industrial process on safety and optimality may deteriorate with time due to process characteristic variation, and it is crucial to develop strategies for online operating performance assessment. Although there have been some studies and applications on process safety assessment, optimality assessment has not yet been paid sufficient attention. This paper proposes a probabilistic framework of online operating assessment for industrial processes. First, a Gaussian mixture model (GMM) is used to characterize multiple operating modes. Considering the distribution of process variables, safety and optimality indices (SI and OI) are defined and calculated by two successive nonlinear mappings. A hierarchical-level classification method is then presented to divide these indices into different performance levels, and margin analysis on each level is introduced. Finally, performance prediction and preliminary suggestions for improvement are provided. The proposed assessment strategy is then...

Numerical investigation of nonisothermal reduction of hematite using Syngas: the shaft scale study

A mathematical model is developed to investigate the reduction process of hematite in the reduction zone of the Midrex shaft furnace as a moving bed reactor. It is described as a counter-current moving bed cylindrical reactor in which hematite pellets are reduced by a gaseous mixture of hydrogen, water vapour, carbon dioxide and carbon monoxide, namely Syngas. It is laterally injected into the bed at the lower part close to the bottom. Governing equations, including continuity, momentum, energy and mass equations, are derived based on the conceptual model for both gas and solid phases in the cylindrical coordinate system. A three interface unreacted shrinking core model (USCM) is applied to describe the reduction process in the pellet scale at the hematite–magnetite, magnetite–wustite and wustite–iron interfaces. The concluded equations are solved numerically based on the finite volume method. The model predictions are validated by a comparison with the operating data of the Gilmore Midrex plant. It was seen that the model can reproduce the operating data satisfactorily. Finally, the distribution of process variables in the bed is exhaustively explained.

Supervised learning for change-point detection

The detection of changes in the distribution of process variables is referred to as the change-point problem. Existing methods focus on detecting a single (or few) change point in a univariate (or low-dimensional) process. We consider the important high-dimensional multivariate case with multiple change points and without an assumed distribution. In this work the problem is transformed into a supervised learning problem with time as the output response and the process variables as inputs. Our focus is to identify the subset of variables that change. This important, practical scenario is analysed through a supervised learner with a variable importance measure that is used to identify the variables that change among hundreds of variables. Simulated cases are discussed in the paper to verify the proposed method. Moreover, the same data sets are compared with a multivariate exponentially weighted moving average control chart and the advantages of the supervised learner are illustrated.

等温固定層による酸化鉄ペレットの還元プロセスの研究

A mathematical model for the isothermal fixed bed and one of the numerical calculating method are presented. The reaction rate used in this model is determined on the basis of the rate measured for single iron oxide pellet.In order to clarify the availability of the mathematical model for analyzing the metallurgical reactors, change in the average fractional reduction over the whole bed with the lapse of time was observed during the reduction of iron oxide pellets with CO and H2 in the experimental fixed bed.The observed data were in good agreement with the calculated values except in the case where the pellets cracked badly during the reduction. It is, therefore, found that the distributions of process variables in isothermal fixed bed are estimated with the considerable accuracy by the model mentioned above and that the reaction rates of pellets with CO and H2 used in this paper are expected to be available for the process analysis of metallurgical reactors.

高炉の炉内状況および出銑量とカーボン比に及ぼすパラメータ変化の効果

高炉の炉内状況および出銑量とカーボン比に及ぼすパラメータ変化の効果