Algorithms for On-line Computer Control of Steel Ingot Processing

Cook, James; Longwell, Edward J.; Nachtigal, C. L.

doi:10.1016/s1474-6670(17)65934-2

Cited by 9 publications

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“…Typical ingot models for this purpose are the two-dimensional model (Sevrin, 1970;Massey et al, 1971), the cylindrical model (Cook et al, 1978) and the spherical model (Maeda, 1975). The cylindrical (one dimensional) form will be followed in this investigation.…”

Section: Introductionmentioning

confidence: 99%

“…description of the temperature behavior of steel ingots during solidification, cooling and heating has received the attention of numerous investigators. t. [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] They have employed various approaches to establish the mathematical models for these ingots. For the development of these ingot models, the following main approaches have been applied to date: lumped parameter linear models, distributed parameter models, on-line optimal estimation, and regression analysis.…”

Section: Introductionmentioning

confidence: 99%

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Applications of a Discrete Dynamic Model of Steel Ingot Temperature Behavior to Soaking Pit Operations

Williams

1984

Chemical Engineering Communications

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A discrete, linear, time-variant, state equation model of the heat transfer processes involved has been applied to describe the behavior of steel ingots during teeming, prior to and following stripping, during soaking pit heating and on extraction. This model gives accurate representations of the solidus formation and of the transient temperature behavior of the ingot while in the molds and while in the soaking pit furnaces. A major application of the resulting model has been to the charging of ingots with partially liquid cores into the soaking pits with a resulting substantial reduction in the energy requirements for the soaking pit operation and a correspondingly large increase in soaking pit throughput or productivity. INTRODUCTIONOne of the major areas of steel plant operation today is that of ingot processing. The objective in controlling the soaking pits is to achieve suitably high and uniform ingot temperature profiles for rolling while minimizing the total energy consumption in the soaking process.During the past few decades, the mathematical. description of the temperature behavior of steel ingots during solidification, cooling and heating has received the attention of numerous investigators. t.3-20 They have employed various approaches to establish the mathematical models for these ingots. For the development of these ingot models, the following main approaches have been applied to date: lumped parameter linear models, distributed parameter models, on-line optimal estimation, and regression analysis. King et al. (1963), have detailed the basic equations involved and their application to ingot processing modelling.Ingot models can readily be described in the form of partial differential equations (Lausterer, 1978). Ray et al. (1979), have indicated some potential applications of distributed parameter system theory to control of soaking pits. In addition, Soliman (1972) has applied the finite element method to solve the distributed parameter models , Presently Associate Professor of Chemical Engineeringof ingots during the solidification process. In practice, the solution of the partial differential equations of a distributed parameter model with the necessary boundary conditions is a difficult and time consuming task. Most investigators therefore choose to transform the model into a set of linear equations using the integral profile method or a finite difference approximation.In order to simplify the problem further, the resulting models can usually be reduced from three dimensions to one or two by means of some appropriate assumptions. Typical ingot models for this purpose are the two-dimensional model (Sevrin, 1970;Massey et al., 1971), the cylindrical model (Cook et al., 1978) and the spherical model (Maeda, 1975). The cylindrical (one dimensional) form will be followed in this investigation.The objective in controlling soaking pits is to achieve a suitable internal metal temperature profile for rolling, while minimizing surface oxidation and total energy consumption. Unfortunately, in practice, thes...

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Applications of a Discrete Dynamic Model of Steel Ingot Temperature Behavior to Soaking Pit Operations

Williams

1984

Chemical Engineering Communications

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Numerical modelling of the heat transfer in and around a steel bar during hot rolling

Visser

Mathews

1988

Commun. appl. numer. methods

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By modelling the heat transfer in and around a hot-rolled steel bar, the temperature distribution in the bar can be predicted at any stage of the hot rolling process. Knowledge of these temperatures is useful when the process is to be optimized. This paper presents a finite difference simulation of the heat transfer and resulting temperature distribution. The numerical procedure accounts for thermal radiation from the bar, convective heat transfer to the atmosphere and cooling water, and conduction between the moving bar and the mill rolls and manipulators. Measured values for convective heat transfer coefficients are used at the boundaries. The following effects are also accounted for in the procedure: deformation of the bar during rolling, tilting the bar between passes through a mill, cropping the bar and contraction resulting from heat losses. Predicted and measured temperatures correlate favourably.

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Energy savings and productivity increases with computers — A case study of the steel ingot handling process

Williams

1983

Computers in Industry

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Algorithms for On-line Computer Control of Steel Ingot Processing

Cited by 9 publications

References 1 publication

Applications of a Discrete Dynamic Model of Steel Ingot Temperature Behavior to Soaking Pit Operations

Applications of a Discrete Dynamic Model of Steel Ingot Temperature Behavior to Soaking Pit Operations

Numerical modelling of the heat transfer in and around a steel bar during hot rolling

Energy savings and productivity increases with computers — A case study of the steel ingot handling process

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