Temperature estimation method, furnace operation method, furnace design method, furnace operation process development method, object packing state setting method and processing apparatus

Abstract

To provide a temperature estimation method and a processing apparatus which can estimate the temperature of a fluid passing through voids in a packed bed of plural objects and / or the objects.SOLUTION: A temperature estimation method according to the present invention includes the steps of: creating the data of a fluid space as a space through which a fluid flows from the shape data of a packed bed; creating calculation grid points at the inside of the fluid space; regarding the created respective calculation grid points, calculating a signed distance showing a distance between the calculation grid points and the surfaces of the objects different in signs depending on whether the positions of the calculation grid points are inside the objects or not; determining whether the created respective grid points are located inside the objects or not based on the calculated signed distance; calculating the speed of the fluid in the fluid space by solving a fluid equation in the calculation grid points determined not to be inside the objects; and estimating the temperatures of the fluid and the objects by solving heat advection-diffusion equations in the respective calculation grid points using the calculated speed of the fluid.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a temperature estimation method for estimating the temperature of a fluid and / or an object passing through a void in a packed bed packed with a plurality of objects, a method for operating a furnace, a method for designing a furnace, a method for developing an operating process for a furnace, a method for setting the filling state of an object, and a processing device. [Background technology]

[0002] In order to improve the operating efficiency of electric furnaces, there are preheating type electric furnaces that preheat scrap, which is an iron source, using high-temperature exhaust gas generated in the electric furnace. This preheating type electric furnace is equipped with a preheating section that preheats the scrap, and a melting section that melts the scrap using heat from an arc generated by graphite electrodes or the like. The preheating section and the melting section are connected, and in the preheating section, the scrap preheated by the high-temperature exhaust gas generated in the melting section is loaded into the melting section by its own weight or mechanical operation and melted. In order to improve the operating efficiency of this preheating type electric furnace, it is necessary to steadily transfer the heat of the exhaust gas to the scrap in the preheating section.

[0003] Therefore, in order to determine the operating conditions with high preheating efficiency for each scrap, it is necessary to investigate how the heat of the exhaust gas is transferred to each scrap. As a means of investigation, it is possible to use heat transfer calculation, which is a type of simulation that can investigate the time-dependent change in temperature of the scrap and the exhaust gas in detail. Specifically, as a method of estimating the temperature of the scrap packed bed in which multiple scraps are packed in the preheating section, a method using a heat transfer equation as described in Patent Documents 1 and 2 is considered. Patent Document 1 describes a method of estimating the thickness of the slag coating on the side of an electric furnace by performing unsteady heat transfer calculation using a model using the finite element method. In addition, Patent Document 2 describes a method of predicting the furnace wall temperature based on the sensor temperature using an unsteady heat conduction equation to determine the melting and falling of the scrap. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2009-85549 A [Patent Document 2] JP 2017-226864 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, scrap has various shapes because it is generated from various products such as automobiles, home appliances, and building materials, or during the manufacture of products. For this reason, it is very difficult to assume that the scrap packed bed in the preheating section is a collection of "perfectly spherical objects" as is usually done in simulations using information processing devices such as computers. Furthermore, the shape of the scrap packed bed varies depending on the type of scrap charged and the charging method. For example, a scrap packed bed containing a lot of thin plates and a scrap packed bed containing a lot of H-shaped steel will have different shapes even if they have the same weight.

[0006] The methods described in the above Patent Documents 1 and 2 cannot accurately predict the temperature of the exhaust gas passing through the scrap packed bed having a complex shape. In detail, in the method described in Patent Document 1, the thickness of the slag is almost cylindrical, and a complex shape is not applied to the calculation shape. In addition, a method for simulating the flow of the exhaust gas is not described, and the flow of the exhaust gas entering the scrap packed bed cannot be calculated. Similarly, Patent Document 2 only describes a theoretical formula for the heat conduction equation of the electric furnace wall, and does not describe a calculation method for heat transfer to the scrap packed bed having a complex shape. In addition, a method for calculating the flow of the exhaust gas is not described, and the temperature of the exhaust gas passing through the scrap packed bed cannot be estimated.

[0007] The present invention has been made to solve the above problems, and an object of the present invention is to provide a temperature estimation method and processing device capable of accurately estimating the temperature of a fluid and / or an object passing through a void in a packed bed filled with a plurality of objects. Another object of the present invention is to provide a furnace operation method, a furnace design method, a furnace operation process development method, and a method for setting the packed state of objects, which can reduce operation costs and operate the furnace stably. [Means for solving the problem]

[0008] [1] The temperature estimation method according to the present invention is a temperature estimation method for estimating the temperature of a fluid and / or an object passing through a gap in a packed bed filled with a plurality of objects, and includes the following steps: a first step of creating data of a fluid space, which is a space through which the fluid flows, from shape data of the packed bed; a second step of creating computational grid points in the fluid space; a third step of calculating, for each computational grid point created in the second step, a signed distance indicating the distance between the computational grid point and a surface of the object, the sign of which differs depending on whether the position of the computational grid point is within the object or not; a fourth step of determining whether each computational grid point created in the second step is located within the object based on the signed distance calculated in the third step; a fifth step of calculating the velocity of a fluid in the fluid space by solving a fluid equation at the computational grid points determined in the fourth step to be not within the object; and a sixth step of estimating the temperature of the fluid and the object by solving a heat advection-diffusion equation at each computational grid point using the fluid velocity calculated in the fifth step.

[0009] [2] The temperature estimation method according to the present invention is the temperature estimation method according to [1], wherein the fifth step includes a step of calculating a fluid velocity using a lattice Boltzmann method that uses a lattice Boltzmann equation as the fluid equation.

[0010] [3] The temperature estimation method of the present invention is the temperature estimation method of [1] or [2], wherein the sixth step includes a step of calculating the temperature by setting a heat transfer coefficient to a computational grid point located within the object and to a computational grid point adjacent to a computational grid point not located within the object.

[0011] [4] A method for operating a furnace according to the present invention is a method for operating a furnace equipped with a heat source for burning an object, and includes an estimation step of estimating a temperature of the object charged into the furnace and / or a fluid in the furnace using any one of the temperature estimation methods [1] to [3], and a control step of controlling the amount of the object charged into the furnace and / or the heat source based on the temperature of the object and / or the fluid in the furnace estimated in the estimation step.

[0012] [5] A furnace design method according to the present invention is a method for designing a furnace equipped with a heat source for burning an object, which sets a shape of the furnace and / or specifications of the heat source based on a temperature of the object loaded into the furnace and / or a fluid in the furnace, which is estimated in advance using any one of the temperature estimation methods [1] to [3].

[0013] [6] The method for developing an operation process of a furnace according to the present invention is a method for developing an operation process of a furnace equipped with a heat source for burning an object, which develops an operation process of the furnace including control of the amount of the object charged into the furnace and / or the heat source based on the temperature of the object charged into the furnace and / or the fluid in the furnace, which has been estimated in advance using any one of the temperature estimation methods [1] to [3].

[0014] [7] A method for setting the filling state of an object according to the present invention is a method for setting the filling state of an object to be loaded into a furnace for burning an object, which determines the amount of the object to be loaded into the furnace and / or its arrangement at the time of loading based on the temperature of the object loaded into the furnace and / or the temperature of a fluid in the furnace, which is estimated in advance using any one of the temperature estimation methods [1] to [3].

[0015] [8] A processing device according to the present invention is a processing device that estimates the temperature of a fluid and / or an object passing through a gap in a packed bed filled with a plurality of objects, and includes: a spatial data creation unit that creates data on a fluid space, which is a space through which the fluid flows, from shape data of the packed bed; a computational grid point creation unit that creates computational grid points in the fluid space; a signed distance function calculation unit that calculates a signed distance indicating the distance between a computational grid point and a surface of the object, for each computational grid point created by the computational grid point creation unit, the signed distance differing depending on whether the position of the computational grid point is within the object or not; a space determination unit that determines whether each computational grid point created by the computational grid point creation unit is located within the object based on the signed distance calculated by the signed distance function calculation unit; a flow calculation unit that calculates the velocity of a fluid in the fluid space by solving a fluid equation at a computational grid point determined by the space determination unit to not be within the object; and a temperature estimation unit that estimates the temperature of the fluid and the object by solving a thermal advection-diffusion equation at each computational grid point using the fluid velocity calculated by the flow calculation unit. Effect of the Invention

[0016] The temperature estimation method and processing device according to the present invention make it possible to accurately estimate the temperature of a fluid and / or an object passing through a gap in a packed bed filled with a plurality of objects. Also, the furnace operation method, furnace design method, furnace operation process development method, and object filling state setting method according to the present invention make it possible to reduce operation costs and operate the furnace stably. [Brief description of the drawings]

[0017] [Figure 1] FIG. 1 is a schematic diagram showing the configuration of an electric furnace according to one embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram showing the configuration of a processing device according to an embodiment of the present invention. [Diagram 3] FIG. 3 is a flowchart showing the flow of the temperature estimation process according to one embodiment of the present invention. [Figure 4]FIG. 4 is a diagram showing an example of a scrap packed bed. [Diagram 5] FIG. 5 is a diagram showing an example of a fluid space. [Figure 6] FIG. 6 is a diagram illustrating an example of computational grid points. [Figure 7] FIG. 7 is a diagram for explaining the object signal and the fluid space signal. [Figure 8] FIG. 8 is a diagram for explaining the boundary conditions. [Figure 9] FIG. 9 is a diagram showing an example of calculation of the fluid flow in the scrap packed bed. [Figure 10] FIG. 10 is a diagram showing an example of estimated temperature distribution of the scrap and the fluid. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0018] Hereinafter, a temperature estimation method and a furnace operation method according to an embodiment of the present invention will be described with reference to the drawings.

[0019] [Configuration of electric furnace] First, with reference to FIG. 1, a configuration of an electric furnace to which a temperature estimation method and a furnace operation method according to an embodiment of the present invention are applied will be described.

[0020] FIG. 1 is a schematic diagram showing the configuration of an electric furnace according to one embodiment of the present invention. As shown in FIG. 1, an electric furnace 1 according to one embodiment of the present invention is a preheating type electric furnace that preheats scrap S, which is an iron source, using high-temperature exhaust gas G generated in the electric furnace 1. In this embodiment, the electric furnace 1 includes a preheating section 2 that preheats a scrap packed bed filled with a plurality of scraps S using the exhaust gas G, and a melting section 4 that melts the scrap S using the heat of an arc generated by a graphite electrode 3 to produce molten iron SA. The preheating section 2 and the melting section 4 are in communication with each other, and in the preheating section 2, the scrap S in the scrap packed bed preheated by the high-temperature exhaust gas G generated in the melting section 4 is charged into the melting section 4 by the weight of the scrap S or a mechanical operation and melted.

[0021] [Configuration of Processing Device] Next, with reference to FIG. 2, a configuration of a processing device that executes a temperature estimation method according to an embodiment of the present invention will be described.

[0022] In this embodiment, the scrap S is used as an example of an object. It is very difficult to assume that the shape of the scrap packed bed is a collection of "perfectly spherical objects". This is because the scrap S has a wide variety of shapes. For this reason, the void distribution in the scrap packed bed differs depending on the scrap S. As a result, the way in which the scrap packed bed is heated by the exhaust gas G differs depending on the scrap S. In the processing device and temperature estimation process described below, the void distribution in the scrap packed bed can be accurately reflected without significantly increasing the load on an information processing device such as a computer that performs the simulation. Therefore, the present invention is more effective when the shape of the object in the packed bed is "other than a perfect sphere". Of course, the effect can also be obtained when the shape of the object in the packed bed is "perfectly spherical". In the present invention, "objects other than perfect spheres" refer to objects whose distances to the surface are different at some or all positions within the object. On the other hand, "perfectly spherical objects" refer to objects whose surfaces have curved surfaces and whose distances to the surface are all the same at certain points within the object.

[0023] Fig. 2 is a block diagram showing the configuration of a processing device according to one embodiment of the present invention. As shown in Fig. 2, a processing device 10 according to one embodiment of the present invention is configured by an information processing device such as a computer. An input device 21 and an output device 22 are connected to the processing device 10. The input device 21 is configured by known input devices such as a keyboard and a mouse pointer, and inputs various information such as setting values ​​to the processing device 10. The output device 22 is configured by known output devices such as a display device, a printer, and an audio output device, and outputs various information according to control signals from the processing device 10.

[0024] The processing device 10 includes an object packed layer creation unit 11, a space data creation unit 12, a computational grid point creation unit 13, a signed distance function calculation unit 14, a space determination unit 15, a flow calculation unit 16, and a temperature estimation unit 17. The functions of each of these units are realized by an arithmetic processing unit such as a CPU in the information processing device executing a computer program stored in the storage unit. The functions of each of these units will be described later. The storage unit may be a storage medium fixed to the computer or the like, or a storage medium removable from the computer. Examples of storage media fixed to the computer include an EPROM (Erasable Programmable ROM) and a hard disk drive (HDD, Hard Disk Drive).

[0025] Examples of recording media that can be removed from a computer include a universal serial bus (USB) memory, a flexible disk, a magneto-optical disk, a compact disc-read only memory (CD-ROM), a compact disc-rewritable (CD-RW), a digital versatile disc (DVD), a Blu-ray (registered trademark) disc (BD), a digital audio tape (DAT), an 8 mm tape, and a memory card. A solid state drive (SSD) can be used as a storage medium that can be removed from a computer or the like, or as a storage medium fixed to a computer. The computer program may be stored on a computer connected to a telecommunications line such as the Internet, and provided by downloading the program via the telecommunications line. The computer program may be provided or distributed via a telecommunications line such as the Internet.

[0026] The processing device 10 having such a configuration executes the temperature estimation process described below to estimate the temperatures of the exhaust gas G and the scrap S passing through the gaps in the scrap packed bed formed in the preheating section 2. Hereinafter, with reference to FIG. 3, the operation of the processing device 10 when executing the temperature estimation process will be described.

[0027] [Temperature Estimation Processing] Fig. 3 is a flowchart showing the flow of a temperature estimation process according to an embodiment of the present invention. The flowchart shown in Fig. 3 starts when an execution command for the temperature estimation process is input to the processing device 10, and the temperature estimation process proceeds to step S1.

[0028] In the process of step S1, the object packed bed creation unit 11 uses objects of multiple scraps S of various shapes created by a shape creation tool such as three-dimensional CAD software to simulate the state in which the scraps S are introduced and piled up in the preheating unit 2. An example of a simulation method is a method of simulating the movement of an object (falling motion, contact motion, etc.) using a motion equation. Then, the object packed bed creation unit 11 uses the simulation result to create shape data of the scrap packed bed in which multiple scraps S are piled up as shown in FIG. 4. The shape data of the scrap packed bed includes shape data of each scrap S (exterior shape, dimensions, etc.) and position data in the scrap packed bed. Note that the shape data of the scrap packed bed may be obtained by actually measuring the shape of the scrap packed bed in the preheating unit 2 using a measurement method such as a laser scanner. This completes the process of step S1, and the temperature estimation process proceeds to the process of step S2.

[0029] In the process of step S2, the spatial data creation unit 12 uses the shape data of the scrap packed bed created in the process of step S1 to create data on the fluid space, which is a space through which a fluid such as exhaust gas G passing through the scrap packed bed flows. Specifically, the spatial data creation unit 12 calculates data on the space including the scrap packed bed as fluid space data, as shown in FIG. 5. Note that if the region to be calculated is only a part of the scrap packed bed, fluid space data may be created only for the region to be calculated. This completes the process of step S2, and the temperature estimation process proceeds to the process of step S3.

[0030] In the process of step S3, the computational grid point creation unit 13 creates a plurality of computational grid points (mesh points) required for numerical calculation in the fluid space created in the processes of steps S1 and S2. An example of computational grid points in a cross section with a scrap packed layer is shown in FIG. 6. In FIG. 6, the intersections of the grid lines indicate computational grid points N, the black areas indicate scrap, and the white areas indicate fluid space. The interval between adjacent computational grid points should be set to a size equal to or smaller than the interval between computational grid points that can be created in the area of ​​scrap S. If the interval between computational grid points is shortened and a large number of computational grid points are created, the calculation time will be significantly extended, but the calculation accuracy can be improved. Also, a large number of computational grid points may be provided locally in a required area. As for the arrangement of the computational grid points, a structured grid in which computational grid points are regularly arranged is more convenient for numerical calculation, and a non-structured grid that is easy to match with the shape of the object may also be used. With this, the process of step S3 is completed, and the temperature estimation process proceeds to the process of step S4.

[0031] In the process of step S4, the signed distance function calculation unit 14 calculates the signed distance from the nearest scrap S (object) surface position for each computation grid point created in the process of step S3. The signed distance indicates the distance from the nearest scrap S surface position (the position of the perpendicular line from the computation grid point to the scrap surface) to the computation grid point of interest, and is assigned a negative sign if the computation grid point is located within the scrap S, and a positive sign if it is not located within the fluid space. However, as long as it can be determined whether the computation grid point is located within the scrap S or within the fluid space, it does not matter whether the value is positive or negative. This completes the process of step S4, and the temperature estimation process proceeds to the process of step S5.

[0032] In the process of step S5, the space determination unit 15 assigns an object signal or a fluid space signal to the data of each computational grid point based on the signed distance calculated in the process of step S4. Specifically, as shown in FIG. 7, when the signed distance (distance from the surface SF of the scrap S) calculated for the computational grid point NA to be processed is a positive value, the space determination unit 15 judges that the computational grid point NA is located within the scrap S, and assigns an object signal to the data of the computational grid point NA. On the other hand, when the signed distance calculated for the computational grid point NB to be processed is a negative value, the space determination unit 15 judges that the computational grid point NB is located within the fluid space, and assigns a fluid space signal to the data of the computational grid point NB. Note that, for example, numbers such as 0 and 1 may be used as the signal, or symbols such as True and False may be used. With this, the process of step S5 is completed, and the temperature estimation process proceeds to the process of step S6.

[0033] In the process of step S6, the flow calculation unit 16 discretizes a fluid equation such as the Navier-Stokes equation using the finite volume method, the finite difference method, the finite element method, or the like. Then, the flow calculation unit 16 calculates the velocity of the fluid at each computational grid point using the discretized fluid equation based on the multiple computational grid points created in the process of step S3 and the signal assigned to each computational grid point in the process of step S5. Note that when calculating the velocity of the fluid, it may be a steady calculation in which a steady state in which physical variables such as velocity do not change over time is assumed, or it may be a non-steady calculation in which a process in which physical variables change over time is calculated. However, since the fluid space in the scrap packed bed changes greatly, with locally narrow areas and suddenly wide spaces, the law of conservation of mass is easily broken in the calculation, and the calculation often becomes unstable and diverges. In addition, since there are locally narrow areas, the interval between computational grid points must be shortened and a large number of computational grid points must be installed, which increases the calculation time and may not be completed within a realistic time.

[0034] For this reason, it is desirable to use the lattice Boltzmann method, which uses the lattice Boltzmann equation as the fluid equation, as a method for calculating the velocity of the fluid. The Boltzmann equation is a higher-level equation of the fluid equations that are commonly used, and is derived using the kinetic theory of gas molecules. By imposing a continuity constraint, a continuum fluid equation such as the Navier-Stokes equation can be derived from the Boltzmann equation. The Boltzmann equation assumes collisions of gas molecules, so generally requires a large amount of calculation, but the lattice Boltzmann equation can reduce the amount of calculation by modeling the collisions of gas molecules. During calculation, the fluid is considered as a virtual particle, and calculations are performed taking into account the collisions of virtual fluid particles, so mass conservation is less likely to be broken. By applying this lattice Boltzmann method to the fluid space in the scrap packed bed, where locally narrow spaces and suddenly wide spaces exist, the velocity of the fluid can be calculated stably.

[0035] The lattice Boltzmann method for unsteady calculations is an explicit calculation because it calculates the movement of fluids by particle collisions. With an explicit method, for example, when updating the next time, only physical variables such as the velocity at the current time are required. Therefore, parallelization can be easily performed for each block of computational grid points, and the speed improvement effect of parallel calculation can be easily achieved. In particular, by using a computation accelerator such as a GPU with many computational cores for parallel calculation of the lattice Boltzmann method, it may be possible to improve the calculation speed by several hundred times. Even in flow calculations with a large number of computational grid points, such as the computational grid points of the fluid space in a scrap packed bed, the calculation can be completed within a realistic time by applying the lattice Boltzmann method.

[0036] The flow calculation unit 16 sets boundary conditions and physical properties of the fluid, and obtains the velocity of the fluid in the fluid space by fluid calculation using the above-mentioned calculation method. In detail, the flow calculation unit 16 sets an inflow boundary condition of velocity or pressure at the inflow point of the fluid, sets a wall boundary condition where the flow does not penetrate the wall area, and sets an outflow boundary condition where the pressure, velocity, or the contents inside flow out as they are at the outflow point of the fluid. For example, as shown in FIG. 8, the flow calculation unit 16 sets the lower boundary of the fluid space as the inflow boundary, the periphery of the fluid space as the wall boundary, and the upper side of the fluid space as the outflow boundary, and sets boundary conditions for each boundary. Note that the symbol LA in the figure indicates a scrap packed layer. As for the fluid properties, the fluid properties required for fluid calculation, such as the viscosity and density of the fluid, are given to the computational grid points to which the fluid space signal is assigned. Then, after setting various conditions, the flow calculation unit 16 gives an initial condition if it is unsteady, performs a fluid calculation numerically, and obtains the velocity of the fluid in the fluid space (the computational grid points to which the fluid space signal is assigned) by numerically calculating it. An example of the calculation of the fluid velocity is shown in FIG. 9. 9, it is understood that it is possible to calculate the flow of fluid between the scraps S. This completes the process of step S6, and the temperature estimation process proceeds to step S7.

[0037] In the process of step S7, the temperature estimation unit 17 sets temperature boundary conditions for each boundary shown in FIG. 8. Then, the temperature estimation unit 17 estimates the temperature of the scrap S (object) and the fluid using the fluid velocity in the fluid space calculated in the process of step S6 and the discretized heat advection-diffusion equation. An example of the estimated temperature distribution of the scrap S and the fluid is shown in FIG. 10. From the example shown in FIG. 10, it can be confirmed that the scrap at the initial temperature absorbs heat from the exhaust gas, and the exhaust gas temperature drops. It can also be confirmed that the temperature of the scrap S is increased by the exhaust gas. This makes it possible to predict the temperature of the scrap packed bed and the exhaust gas flowing within the scrap packed bed, which is difficult to calculate.

[0038] It is also possible to calculate only the temperature of either the scrap or the exhaust gas. The temperature estimation unit 17 may estimate the temperatures of the scrap S and the fluid by applying the above-mentioned lattice Boltzmann method to the temperature. The computational grid points may be the same as the computational grid points used by the flow calculation unit 16, or a staggered grid may be used in which a polyhedron with each computational grid point as a vertex is considered and the center of the polyhedron is the temperature calculation point in order to stabilize the calculation. When estimating the temperature, the temperature estimation unit 17 gives each computational grid point thermophysical properties such as thermal conductivity, density, and specific heat corresponding to the scrap S or the fluid space according to the object signal or fluid space signal of each computational grid point. When using a staggered grid, the computational grid points to which the object signal is assigned are given the thermophysical properties of the scrap S, and the computational grid points to which the fluid space signal is assigned are given the thermophysical properties of the fluid.

[0039] In addition, the temperature estimation unit 17 assigns a heat transfer coefficient to the computational grid points adjacent to the computational grid points to which the object signal is assigned and the computational grid points to which the fluid space signal is assigned, because heat transfer, which is heat transfer between a fluid and a solid, occurs. The heat transfer coefficient may be assigned by applying Newton's law of cooling as a heat transfer coefficient term. For the computational grid points to which the heat transfer coefficient is assigned, the temperature estimation unit 17 sets a heat transfer coefficient term representing heat transfer by heat transfer to the source term of the thermal diffusion-advection equation. The temperature of the fluid may be calculated steadily by fixing the velocity at a certain time calculated by the flow calculation unit 16, or may be calculated unsteadily by calculating the temperature at a certain time based on the velocity of the fluid space calculated at a certain time. In addition, the flow calculation unit 16 may calculate the velocity of the fluid again by changing the physical property value such as the fluid viscosity based on the temperature calculated by the temperature estimation unit 17. In the case of unsteady temperature calculation, the temperature of the fluid that changes at each time can be calculated by setting the temperature of the initial condition at each computational grid point, giving the boundary temperature condition of the fluid to the inflow boundary, and applying the temperature calculation method set for each time. This completes the process of step S7, and ends the series of temperature estimation processes.

[0040] As is clear from the above description, in the temperature estimation process according to one embodiment of the present invention, the space data creation unit 12 creates data on the fluid space, which is the space through which the fluid flows, from the shape data of the scrap packed bed, the computational grid point creation unit 13 creates computational grid points in the fluid space, and the signed distance function calculation unit 14 calculates a signed distance indicating the distance between the computational grid point and the surface of the scrap, the signed distance being different depending on whether the computational grid point is located within the scrap or not. Then, the space determination unit 15 determines whether each computational grid point is located within the scrap or not based on the calculated signed distance, the flow calculation unit 16 calculates the velocity of the fluid in the fluid space by solving the fluid equation at the computational grid point determined not to be within the scrap, and the temperature estimation unit 17 estimates the temperature of the fluid and the scrap by solving the heat advection-diffusion equation at each computational grid point using the calculated fluid velocity. This allows the temperature of the fluid and the scrap passing through the voids in the scrap packed bed to be accurately estimated.

[0041] (Example 1: Furnace operation method) The method for operating a furnace according to the present invention utilizes the temperature estimation method according to the embodiment. Specifically, after the processing of step S7, a control step is included in which the amount of scrap S to be charged into the preheating section 2 and the heat source such as the arc heat generated from the graphite electrode 3 and the burner are controlled based on the estimated temperatures of the scrap S and the fluid. The control step may be performed immediately after the temperature designation process, but the temperature estimation process may be performed separately before the control step, and the temperature of the object charged into the furnace and / or the fluid in the furnace may be calculated in advance. The furnace may also be equipped with a preheating section 2 like the electric furnace 1 described in this embodiment. In this case, the preheating section 2 is also included in the "furnace". By using the temperature estimation method according to the present embodiment, it is possible to perform an operation that reduces energy costs. In addition, by devising a way to charge scrap based on the calculated temperatures of the scrap S and the fluid, it is possible to reduce the bias in heat transfer to the scrap S and realize stable operation of the electric furnace 1.

[0042] (Example 2: Furnace design method) The temperature estimation method according to the embodiment can be used in a design method for a furnace in which objects are charged. In this case, the temperature of the object charged in the furnace and / or the fluid in the furnace is estimated in advance using the temperature estimation method. Then, the shape of the furnace and / or the specifications of the heat source are set based on the estimated temperature of the object charged in the furnace and / or the fluid in the furnace. The furnace may also include a preheating section 2 like the electric furnace 1 described in this embodiment. In this case, the preheating section 2 is also included in the "furnace".

[0043] (Application example 3: How to develop furnace operation processes) The temperature estimation method according to the embodiment can be used in a method for developing an operation process of a furnace in which objects are charged. In this case, the temperature of the object charged into the furnace and / or the fluid in the furnace is estimated in advance using the temperature estimation method. Then, based on the estimated temperature of the object charged into the furnace and / or the fluid in the furnace, an operation process of the furnace is developed, including control of the amount of the object charged into the furnace and / or the heat source.

[0044] (Example 4: How to set the filling state of objects in a furnace) The temperature estimation method according to the embodiment can be used to determine the filling state of objects to be charged into a furnace. In this case, the temperature of the objects charged into the furnace and / or the fluid in the furnace is estimated in advance using the temperature estimation method. Then, the amount of objects to be charged into the furnace and / or the placement at the time of filling are set based on the estimated temperature of the objects charged into the furnace and / or the fluid in the furnace.

[0045] Although the embodiments of the present invention have been described above, the present invention is not limited by the descriptions and drawings that form part of the disclosure of the present invention according to the present embodiments. In other words, other embodiments, examples, and operation techniques, etc., made by those skilled in the art based on the present embodiments are all included in the scope of the present invention. [Explanation of symbols]

[0046] 1 Electric furnace 2 Preheating section 3. Graphite Electrode 4 Melting part 10 Processing equipment 11. Object Packing Layer Creation Section 12 Spatial Data Creation Department 13 Computational grid point creation section 14 Signed distance function calculation unit 15 Spatial judgment section 16 Flow Calculation Section 17 Temperature estimation section 21 Input Devices 22 Output Devices G. Exhaust gas N, NA, NB calculation grid points S Scrap SA Molten Iron

Claims

1. A temperature estimation method for estimating a temperature of a fluid and / or an object passing through a gap in a packed bed packed with a plurality of objects, comprising: a first step of creating data on a fluid space, which is a space through which the fluid flows, from shape data of the packed bed; A second step of generating computational grid points in the fluid space; a third step of calculating, for each computational grid point created in the second step, a signed distance indicating a distance between the computational grid point and a surface of the object, the signed distance being different depending on whether the position of the computational grid point is inside the object or not; a fourth step of determining whether or not each computational grid point created in the second step is located within the object based on the signed distance calculated in the third step; a fifth step of calculating a velocity of a fluid in the fluid space by solving a fluid equation at a computational grid point determined not to be within the object in the fourth step; a sixth step of estimating temperatures of the fluid and the object by solving a thermal advection-diffusion equation at each computational grid point using the fluid velocity calculated in the fifth step; A temperature estimation method comprising:

2. The temperature estimation method according to claim 1 , wherein the fifth step includes a step of calculating a velocity of the fluid by utilizing a lattice Boltzmann method using a lattice Boltzmann equation as the fluid equation.

3. 2. The temperature estimation method according to claim 1, wherein the sixth step includes a step of calculating the temperature by setting a heat transfer coefficient to a computational grid point located within the object and a computational grid point adjacent to a computational grid point not located within the object.

4. 1. A method of operating a furnace having a heat source for combusting an object, comprising: A control step of controlling the amount of the object charged into the furnace and / or the heat source based on the temperature of the object charged into the furnace and / or the temperature of the fluid in the furnace, which is calculated in advance using the temperature estimation method according to any one of claims 1 to 3; A method of operating a furnace, comprising:

5. 1. A method for designing a furnace having a heat source for burning an object, comprising: A method for designing a furnace, comprising: setting a shape of the furnace and / or a specification of the heat source based on a temperature of the object charged in the furnace and / or a temperature of a fluid in the furnace, the temperature being calculated in advance using the temperature estimation method according to any one of claims 1 to 3.

6. 1. A method for developing an operating process for a furnace having a heat source for burning an object, comprising: A method for developing an operation process of a furnace, the method including controlling the amount of the object charged into the furnace and / or the heat source, based on the temperature of the object charged into the furnace and / or the temperature of the fluid in the furnace, which is calculated in advance using the temperature estimation method described in any one of claims 1 to 3.

7. 1. A method for setting a loading state of objects to be charged into a furnace for burning objects, comprising the steps of: A method for setting the filling state of an object, which determines the amount of the object to be charged into the furnace and / or the arrangement at the time of charging based on the temperature of the object charged into the furnace and / or the fluid in the furnace, which is calculated in advance using the temperature estimation method described in any one of claims 1 to 3.

8. A processing device for estimating a temperature of a fluid and / or an object passing through a gap in a packed bed in which a plurality of objects are packed, comprising: a space data creation unit that creates data on a fluid space, which is a space through which the fluid flows, from the shape data of the packed bed; a computational grid point creation unit that creates computational grid points in the fluid space; a signed distance function calculation unit that calculates, for each computational grid point created by the computational grid points, a signed distance indicating a distance between the computational grid point and a surface of the object, the signed distance having a different sign depending on whether the position of the computational grid point is within the object or not; a space determination unit that determines whether or not each computational grid point created by the computational grid point creation unit is located within the object based on the signed distance calculated by the signed distance function calculation unit; a flow calculation unit that calculates a velocity of a fluid in the fluid space by solving a fluid equation at a computational grid point that is determined by the space determination unit to not be within the object; a temperature estimation unit that estimates temperatures of the fluid and the object by solving a thermal advection-diffusion equation at each computational grid point using the fluid velocity calculated by the flow calculation unit; A processing device comprising:

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