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Kolbasin Sergei

Kolbasin Sergei

Faculty:

The Faculty of Computer Information Technologies and Automatics

Speciality:

Informational Controlled Systems and Technologies

Theme of master's work:

To develop a computer subsystem of management of cooling of continuous moulding of an ingot in a zone of secondary cooling by Continuous Сasting Machine of metal product

Leader of work:

Sekirin A.

Content




Introduction


Mathematical modelling is the effective tool of research of various technological processes. It also is necessary for construction of the automated and automatic control systems by these processes.

To guarantee stability of controlled parameters of quality, it is enough to have the adequate mathematical model establishing interrelation between them and managing parameters influencing them.

Difficulty of realization of many mathematical models is connected to absence of necessary values (physical constants or dependences) for factors of the equations which are included in model. Thus, there is a task of identification of parameters of technological process. High requirements to accuracy of models compel to consider unknown sizes of parameters of model distributed in space or in time.

Process of heat exchange can serve in an ingot moving inside the machine of continuous moulding of preparations (CCM) which mathematical model is developed in work [1] to one of examples. In this model processes of internal heat exchange are described by the nonlinear parabolic equations in individual derivatives and take into account carry of heat together with the moving environment (ingot). At modelling such process for concrete industrial conditions each time is required to define the some people warmly physical parameters, in particular factor теплоотдачи (КТ) on a surface of an ingot in a zone of secondary cooling (ZSC) which depends on many factors. In connection with that КТ can accept various values along a surface of an ingot in ZSC, there is a task of identification of the distributed parameter. Size КТ depends on many factors, for example, matters, whether there is a given site of a surface under a torch spraying cooling water-air mix, whether the steam layer between a surface of an ingot and a cooling mix was formed, whether the surface of an ingot with scale, and many other things is covered. All this substantially complicates a task of definition of factor KT. Besides for use of mathematical model in a control system, it is desirable to establish dependence of factor теплоотдачи from the charge of cooling water.

There are various ways of definition КТ, for example, in [2] the method using the equation of dependence is described is warm physical and design data. In work [3] the following ways of identification КТ are resulted:

Method of automated selection КТ by means of analog means, for example, devices in which thermal process is modelled by similar electric process;

Way of identification of boundary conditions at the big intensity of heat exchange by definition of fictitious factor warmly feedbacks aф (or fictitious external thermal resistance 1/aф) on some conditional border which is taking place on distance sygma from a surface;

Way of definition КТ as partially-constant function by a method of iterations.

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The urgency of the tasks


The problem of identifying the coefficient of heat in the zone of secondary cooling machines continuous casting billets. Unsteady processes of internal heat describes parabolic nonlinear partial differential equations. Boundary conditions include radiation and convection heat transfer components and take into account the complex mechanism of heat from water-cooling air. We propose a method of solution of the problem with the method of least squares. There are analyzed and the results of calculations.

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Tasks


To reduce the calculations, give a simplified mathematical model in rectangular coordinates. Consider some station continuously moving steel ingot in the system of coordinates, tied to the construction of continuous casting machines.

5 frames for 1 seconds. 10 repetitions. Animation is made using GifAnimator


The equation for a two-dimensional model of heat and mass transfer in a rectangle (0, l) x (0, m) is as follows:

F_1

where v (t) - speed environment, T (t, x, y) - temperature, c (T) - specific heat, p (T) - density, and lyambda (T) - thermal conductivity continuum.

Perform initial:

F_2

and boundary conditions:

F_3

here a (x) - coefficient of heat convection, sigma - given the rate of radiant heat, T - the temperature inside the ingot, T | y = l - the temperature on the surface of ingot, To.s. -- Ambient temperature.

To simplify the task in three parts of the boundary review rectangle raised the heat flow as zero. On the border, an appropriate surface cooled ingot, set the boundary conditions 3 - the first kind. In general, the heat flow in ZSC has two components: convection (Newton's law-Rihmana) and radiant (Stefan-Boltzmann Law).

Since the surface of ingot in ZSC is in the range of temperatures, in which a large proportion in the total belongs to radiant heat flow component, the boundary conditions (4) take into account both sorts of heat. You need to define the rate of heat loss a (x). As additional information were measurements of temperature on the surface of ingot.

Such tasks are called boundary inverse problem [3.4]. They are incorrect in the classical sense. Correctness in the classical sense (or even speak on Adamaru correctness) means the existence of a solution of the task, its uniqueness and sustainability (ie continuous dependence on the input data). In our case, not running third condition - a condition of sustainability.

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The method of direct treatment


The method of direct treatment. To get an idea of the degree of volatility solutions problem, use direct treatment. To do this from (4) express a (x)

F_5

The measurements of temperature on the surface of ingot known, so the task falls into two parts: the definition of temperature field inside the ingot and then the definition of the coefficient of heat a (x).

The first task is to challenge boundary with boundary conditions 1 - the first kind (Dirichlet conditions) and 2 - the first kind (conditions Neumann). It used finite differences. In a rectangle before us introduce finite-difference grid wq, p, uniform in each direction with the steps q, p = const, q = l / N, p = m / M, where N, M - the number of segments along the partitioning and spatial coordinates x y respectively (Figure 2).

As a result of the decision-course challenges, we can see the difference field temperatures before us plot. To calculate the derivative F_51 nodes in the grid imposed, it certainly replace the analogue-difference.

F_6

From (5) and (6) receive an expression for calculating a (x):

F_7

The coefficient of heat found in a manner suitable for little practical use. Summand corresponding radiant heat transfer increases the error until the fourth order. In addition, the formula is present numerical differentiation, which in itself is an incorrect challenge. Ultimately, the relatively small deviations (errors in measurements) correspond fairly high temperature deviations in the coefficient of heat. The results of calculations by direct treatment are presented in Fig. 4.

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The method of least squares


To apply the method of least squares take into account the following information.

The coefficient of a (x) has a special distribution along the surface of ingot. It is known that at the site, covering a torch jets, it could bring parabolic function, which is the maximum value at a point corresponding to coordinate nozzle jets, while the remaining stations - a constant. Because the jets in the same section before us, they give the same water-air torch, hence the rate of heat loss - the same parabola, move along the axis abscissa (Fig.3).

Here are all the sites under the jets to top coordinate such a way as to peak over the parabola was the beginning of coordinates. The value of h is determined polushirinoy capture plume jets. Consequently, we have to identify only two options - A and a book. As has been said, a c = const, but at sites subject to forced cooling, will seek a (x) in the form of:

F_8

Consider the first sites at which a (x) = a c = const. Let many knots xi, which we believe KT permanent, K. lot of other nodes, where KT is distributed according to a parabolic law denote V. From (7) get a formula for the residual heat flow at the border:

F_81

Denote

F_83

A necessary condition for the existence of extremum S (a):

F_84

Hence, we find a

F_85

Each node xi from the set in place in line yi point on the interval [-h, h] in a manner that | yi | equal distance from the coordinates to the nearest xi jets. From (7) and (8) receive residual

F_86

We find A, in which

F_87

Of the necessary conditions for the existence of extremum

F_88

A find

F_89

It should also be noted that in certain values with the help of MNCs and with a sufficient condition for the existence of running a minimum function S. Easy to verify that the second order partial derivatives S for each of these parameters strictly greater than zero.

Thus, we find some spline approximation distributed in the space of the coefficient of heat at the surface moving ingot, which gives us the minimum rms deviation between the surface temperature measured and calculated on the model solutions as a result of direct challenges.

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The results of calculations


Both the above methods were carried out numerical calculations. As thermophysical parameters for the models were chosen data process continuous casting steel (for stamps art 40), the width of 1 m slabs, slabs polutolschiny l = 0,1 m and speed ingot v = 1 m / min. These calculations are presented in Fig. 4. Here one can see that the decision obtained by direct treatment, is unsustainable and unsuitable for practical use. The second curve is spline approximation, which is the result of the decision of the same tasks of the method of least squares.


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Conclusions


Thus, the method of least squares allows quite easily and quickly find convenient for practical use solution to the problem of identification in the form of spline approximation distributed in the space parameter. The advantage of this method is also true that the decision received relatively stable temperature measurement error on the surface of the body investigated.

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The literature


1. В. Н. Ткаченко, А. А. Иванова. Анализ температурных полей криволинейной МНЛЗ на основе математического моделирования. // Матеріали 3-ї міжнародної науково-практичної конференції “Прогресивні технології у металургії сталі: ХХІ сторіччя”. Донецьк: ДонНТУ. – 2007. – с. 242-249.

2. А. А. Иванова. Математическая модель процесса затвердевания непрерывного слитка в зоне вторичного охлаждения. // Труды ИПММ НАН Украины. – Вып.12. – Донецк, ИПММ. – 2006. – С.76-84.

3. Ю.М. Мацевитый. Обратные задачи теплопроводности. В 2-х т. : Т.2. Приложения. – НАН Украины, институт проблем машиностроения. – Киев: Наукова думка, 2003.

4. А.А. Самарский, П.Н. Вабищевич. Численные методы решения обратных задач математической физики. // М.: Едиториал УРСС, 2004.

5. Толмачев С.Т., Рожненко Ж.Г. Вiсник СНУ iм. В. Даля - 2008 - № 1 (119)

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