Information processing device, raw material particle size search method and program

Abstract

To reduce a calculation cost for searching for a desired raw material particle size in a dry smelting method.SOLUTION: When smelting with a rotary kiln, an information processor includes: a first simulation execution unit that executes a first simulation for calculating a one-dimensional in-furnace temperature distribution in the rotary kiln; a second simulation execution unit for calculating relationship between a dusting rate of the raw material and a particle size in the smelting using the rotary kiln; and a raw material particle size determination unit that determines particle sizes of the raw material for realizing a desired in-furnace particle size distribution, based on the calculation result of the first simulation and the calculation result of second simulation.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device, a raw material particle size searching method, and a program. [Background technology]

[0002] In the pyrometallurgical process using a rotary kiln, the heat from the combustion of coal supplied from the charging end and the heat from the combustion of pulverized coal or heavy oil from a burner are used to dry and partially reduce the ore. The region inside the rotary kiln where gas and dust flow is called the gas phase, and the region where raw materials such as ore move is called the bed layer.

[0003] In a rotary kiln, the rotation of the kiln promotes heat exchange and mixing between the bed layer and the gas phase, thereby achieving the desired process such as drying. Factors related to the mixing efficiency of the bed layer include the kiln rotation speed, inner diameter, furnace wall structure, processing volume, and angle of repose of the raw material.

[0004] Due to the rolling of the raw material and the gas, some of the raw material in the bed layer turns into dust and moves into the gas phase. The raw material in the bed layer and the dust in the gas phase generally have different combustion reaction rates, so depending on the amount of dust, appropriate treatment can be difficult. One of the factors related to the dust conversion rate of the raw material in the bed layer is the particle size of the raw material.

[0005] To understand the state of the rotary kiln, the temperature distribution inside the furnace is measured. The temperature distribution inside the furnace is one of the indicators that shows whether the intended processing is being carried out properly. Therefore, a temperature distribution inside the furnace that is considered to be appropriate for processing is set, and the operating conditions are set to satisfy this.

[0006] Several simulation methods for heat transfer and reactions within a rotary kiln have been proposed to ensure appropriate processing, for example, efficient use of combustion heat. For example, Non-Patent Document 1 discloses a simulation method for calculating one-dimensional temperature distribution within the kiln based on the reaction rate of the raw materials, the movement speed between the gas phase and the bed layer, etc. Also, Non-Patent Document 2 discloses a simulation method for representing phenomena within a rotary kiln using fluid calculations of three-dimensional multiphase flow. [Prior art documents] [Non-patent literature]

[0007] [Non-Patent Document 1] K. Penttila, et al., "Advanced Thermochemical Process Model of Rotary Kilns - KilnSimu", International Chemical Recovery Conference (ICRC) 2017 [Non-patent document 2] S. Dissanayake et al., "CFD Study of Particle Flow Patterns in a Rotating Cylinder Applying OpenFOAM and Fluent", Linkoping Electronic Conference Proceedings, 2017 Summary of the Invention [Problem to be solved by the invention]

[0008] Conventionally, there is a problem in that it is difficult to find the particle size of the raw material that will achieve a desired temperature distribution in the furnace as a trial calculation before an experiment. For example, the simulation method described in Non-Patent Document 1 does not treat the raw material as particles, so it is not possible to find the particle size. Furthermore, finding the particle size of the raw material using the simulation method described in Non-Patent Document 2 requires complex calculations, which is time-consuming and costly, and is therefore not practical.

[0009] The present invention has been made in view of the above circumstances, and aims to reduce the calculation cost required to search for a desired particle size of raw material in a pyrometallurgical process. [Means for solving the problem]

[0010] In order to achieve the above object, an information processing device according to one aspect of the present invention includes: a first simulation execution unit that executes a first simulation to calculate a one-dimensional furnace temperature distribution in a rotary kiln in smelting using the rotary kiln; A second simulation execution unit that calculates the relationship between the dusting rate and particle size of the raw material in smelting using the rotary kiln by a second three-dimensional simulation of the rotary kiln; a raw material particle size determination unit that determines the particle size of the raw material to realize a desired temperature distribution in the furnace based on the calculation results of the first simulation and the calculation results of the second simulation. picture, the first simulation executing unit executes the first simulation for each of the selected movement speeds of the raw material; a dusting rate calculation unit that calculates a dusting rate corresponding to the moving speed of the raw material; the raw material particle size determination unit determines the dusting rate corresponding to a moving speed of the raw material that results in a temperature distribution in the furnace that is close to the desired temperature distribution in the furnace, and calculates the particle size that results in the determined dusting rate based on the calculation result of the second simulation; The raw material is a carbon raw material used for smelting using a rotary kiln. [Effects of the Invention]

[0011] The calculation cost for searching for a desired particle size of raw materials in a pyrometallurgical process can be reduced. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram showing an example of the structure of a rotary kiln. [Figure 2] 1 is a diagram illustrating an example of a functional configuration of an information processing device according to an embodiment of the present invention. [Figure 3] 1 is a flowchart showing an example of the flow of a raw material particle size search process according to an embodiment of the present invention. [Figure 4]1 is a diagram illustrating an example of a hardware configuration of an information processing device according to an embodiment of the present invention. [Figure 5] FIG. 10 is a first diagram for explaining the contents of symbols. [Figure 6] FIG. 10 is a second diagram for explaining the contents of the symbols. [Figure 7] FIG. 10 is a diagram showing an example of a temperature distribution inside a furnace calculated by a first simulation. [Figure 8] FIG. 10 is a first diagram showing an example of the volume fraction of raw materials calculated by a second simulation. [Figure 9] FIG. 10 is a second diagram showing an example of the volume fraction of the raw material calculated by the second simulation. [Figure 10] FIG. 10 is a diagram showing an example of the relationship between the particle size of the raw material and the dust generation rate calculated by the second simulation. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, an embodiment of the present invention (the present embodiment) will be described with reference to the drawings.

[0014] The information processing device according to this embodiment executes a simulation (first simulation) for calculating a one-dimensional temperature distribution in a rotary kiln, and a simulation (second simulation) for calculating the relationship between the particle size of raw materials and the dust fraction of raw materials by fluid calculation of a three-dimensional multiphase flow, in a pyrometallurgical process using a rotary kiln. By using these two simulations together, it is possible to reduce the calculation cost for searching for a desired particle size of raw materials in a pyrometallurgical process.

[0015] (Outline of pyrometallurgy using rotary kilns) FIG. 1 is a diagram showing an example of the structure of a rotary kiln. As shown by arrow 901, raw material 3 (e.g., carbon) is injected into the rotary kiln 1 from an injection section 4. The raw material 3 is agitated by the rotation of the rotary kiln 1 as shown by arrow 903, and is heated by a heater 2. The refined raw material 3 is then injected from an injection section 5 as shown by arrow 904. Air is also injected in the direction shown by arrow 902.

[0016] As shown in FIG. 1, the Z-axis direction is the longitudinal direction of the rotary kiln 1, and the end portion in the negative Z-axis direction is called the hearth end.

[0017] (Functional configuration of information processing device) 2 is a diagram showing an example of the functional configuration of an information processing device 10 according to an embodiment of the present invention. The information processing device 10 is a device for calculating, by simulation, the particle size of the raw material 3 that will achieve a desired temperature distribution in the furnace in the pyrometallurgical method using the rotary kiln 1 described above.

[0018] Specifically, the information processing device 10 includes a first simulation condition information acquisition unit 11, a movement speed selection receiving unit 12, a dust conversion rate calculation unit 13, a first simulation execution unit 14, a second simulation condition information acquisition unit 15, a raw material particle size selection receiving unit 16, a second simulation execution unit 17, a raw material particle size determination unit 18, and an output unit 19.

[0019] The first simulation condition information acquisition unit 11 acquires information (first simulation condition information) indicating conditions for a simulation (first simulation) for calculating a one-dimensional in-furnace temperature distribution. Specifically, the first simulation condition information includes the structure of the rotary kiln 1, operating conditions, calculation conditions for the first simulation, etc.

[0020] An example of the structure of the rotary kiln 1 is as follows. ·Total length [m]:1 ·Inner diameter [m]:0.3 ·Outer diameter [m]:0.40 Inner wall conductivity [W / mK]: 1.28 Exterior wall insulation rate [W / mK]: 40 Injection method: Countercurrent Heating method: External heater (700℃)

[0021] An example of the operating conditions is as follows: Rotation speed [rpm]: 0.6 ·Angle of repose [°]:30 Material movement time [h]: 5 Feed rate [kg / h]: 4 Intake air volume [L / min]: 46.5

[0022] An example of the calculation conditions is as follows: Number of cells: 40 Reaction rate and activation temperature of each substance

[0023] The first simulation condition information acquiring unit 11 may acquire the above-mentioned first simulation condition information by accepting an input operation by a user, or may receive the information from another device or the like via a communication network or the like.

[0024] The transfer speed selection receiving unit 12 receives a user's selection operation of a transfer speed. The transfer speed is the speed at which the raw material moves from the bed layer to the gas phase. Note that the transfer speed may be the speed at which the raw material moves from the gas phase to the bed layer, or a combination thereof.

[0025] The moving speed selection receiving unit 12 receives a selection operation of one or more moving speeds. For example, the moving speed selection receiving unit 12 receives a selection operation of 15[1 / m 2 ], 3.5[1 / m 2 ], 1.5[1 / m 2 ], 0.35[1 / m 2 ], 0.15[1 / m 2 When the moving speed selection receiving unit 12 receives a plurality of selection operations, the first simulation executing unit 14 executes the received number of simulations, respectively.

[0026] The dust rate calculation unit 13 calculates a dust rate indicating the probability that the raw material will turn into dust. Specifically, the dust rate calculation unit 13 calculates the dust rate for each raw material movement speed based on one or more movement speeds accepted by the movement speed selection acceptance unit 12. A specific calculation method will be described later.

[0027] The first simulation execution unit 14 executes a first simulation to calculate the one-dimensional (longitudinal direction of the rotary kiln 1, i.e., the Z-axis direction) temperature distribution inside the kiln (bed layer, gas phase, inner wall, outer wall) for each raw material movement speed. The first simulation may be, for example, a simulation using the method described in Non-Patent Document 1. The first simulation execution unit 14 may also calculate the one-dimensional change in the amount of material inside the kiln (solids, molten material, and gas in the bed layer, and solids, molten material, and gas in the gas phase).

[0028] The second simulation condition information acquisition unit 15 acquires information (second simulation condition information) indicating the conditions of a simulation (second simulation) that calculates the relationship between the particle size of the raw material and the dust conversion rate of the raw material by fluid calculation of a three-dimensional multiphase flow. Specifically, the second simulation condition information includes the structure of the rotary kiln 1, operating conditions, calculation conditions of the second simulation, etc.

[0029] An example of the structure of the rotary kiln 1 is as follows. ·Total length [m]:0.2 ·Inner diameter [m]:0.3 Inner wall conductivity [W / mK]: 1.28

[0030] An example of the operating conditions is as follows: Feed rate [kg / h]: 1 Intake air volume [L / min]: 46.5

[0031] An example of the calculation conditions is as follows: ·Calculation method: Multiphase flow Mesh count: 15,000 Time span [ms]: 1 ·Calculation time [s]: 5

[0032] In the second simulation, since the purpose is to calculate the relationship between the particle size of the raw material and the dusting rate of the raw material, factors with little effect (such as heating and rolling of the rotary kiln 1) may be omitted. This reduces the amount of calculation required for the second simulation.

[0033] The raw material particle size selection receiving unit 16 receives a selection operation of a raw material particle size by the user. The raw material particle size is information that serves as a condition for the second simulation. The raw material particle size selection receiving unit 16 receives a selection operation of one or more raw material particle sizes. For example, the raw material particle size selection receiving unit 16 may receive a selection operation of 1 [μm], 2 [μm], 3 [μm], 4 [μm], 5 [μm], 10 [μm], 50 [μm], and 100 [μm]. When the raw material particle size selection receiving unit 16 receives multiple selection operations, the second simulation executing unit 17 executes the received simulations for each of the selected operations.

[0034] The second simulation executing unit 17 executes a second simulation to calculate the volume fraction (bed layer, gas phase) for each particle size of the raw material. The second simulation may be, for example, a simulation according to the method described in Non-Patent Document 2. The second simulation executing unit 17 calculates the relationship between the particle size of the raw material and the dust fraction of the raw material based on the calculated volume fraction.

[0035] The raw material particle size determination unit 18 determines the particle size of the raw material to achieve a desired in-furnace temperature distribution based on the calculation results of the first simulation and the calculation results of the second simulation. Specifically, based on the calculation results of the first simulation, it determines the movement speed and dust rate of an in-furnace temperature distribution that is close to the desired in-furnace temperature distribution. Here, the raw material particle size determination unit 18 may obtain information indicating the desired in-furnace temperature distribution by accepting input from a user or by receiving it from another device or the like via a communication network or the like.

[0036] Then, the raw material particle size determining unit 18 determines the particle size of the raw material corresponding to the determined dust formation rate, based on the relationship between the particle size of the raw material calculated in the second simulation and the dust formation rate of the raw material.

[0037] The output unit 19 outputs the determined particle size of the raw material. Specifically, the output unit 19 displays the determined particle size of the raw material on a screen such as a display. The output unit 19 may transmit information indicating the determined particle size of the raw material to another device (not shown) via a communication network or the like. For example, a design device may select raw materials, set operating conditions, etc. based on the received information.

[0038] (Operation of information processing device) Next, the operation of the information processing device 10 will be described.

[0039] FIG. 3 is a flowchart showing an example of the flow of the raw material particle size search process according to the embodiment of the present invention.

[0040] In response to a user's operation, the first simulation condition information acquisition unit 11 acquires first simulation condition information (step S11).

[0041] Next, the moving speed selection receiving unit 12 receives the selected moving speed, and the dust formation rate calculation unit 13 calculates the dust formation rate corresponding to the moving speed (step S12).

[0042] Next, the first simulation executing unit 14 performs a first simulation based on the first simulation condition information for each moving speed, and calculates a one-dimensional in-furnace temperature distribution in the rotary kiln (step S13).

[0043] Then, the raw material particle size determining unit 18 determines the dusting rate corresponding to the simulation number that results in a temperature distribution close to the desired one in the furnace (step S14).

[0044] Next, the second simulation condition information acquisition unit 15 acquires the second simulation condition information (step S15).

[0045] Next, the raw material particle size selection receiving unit 16 receives the selection of the particle size of the raw material (step S16).

[0046] Next, the second simulation executing unit 17 calculates the relationship between the particle size of the raw material and the dust generation rate by the second simulation (step S17).

[0047] Next, the raw material particle size determining unit 18 determines the particle size of the raw material to achieve a desired temperature distribution in the furnace based on the calculation results of the first simulation and the calculation results of the second simulation (step S18).

[0048] The output unit 19 displays the determined particle size of the raw material (step S19).

[0049] Each of the above steps will be described in detail later.

[0050] (Hardware configuration of information processing device) Next, the hardware configuration of the information processing device 10 will be described.

[0051] FIG. 4 is a diagram illustrating an example of a hardware configuration of an information processing device according to an embodiment of the present invention.

[0052] The information processing device 10 is configured by a computer and includes, for example, a CPU (Central Processing Unit) 101, a main memory device 102, an auxiliary memory device 103, an input device 104, a display device 105, a communication interface device 106, and a drive device 107. Each of these devices is connected via a bus.

[0053] The CPU 101 is a main control unit that controls the operation of the information processing device 10, and realizes various functions described below by reading and executing programs stored in the main storage device 102.

[0054] The main storage device 102 reads and stores programs from the auxiliary storage device 103 when the information processing device 10 is started up. The auxiliary storage device 103 stores installed programs, as well as files, data, etc. required for various functions described below.

[0055] The input device 104 is a device for inputting various types of information and is realized by, for example, a keyboard, a pointing device, etc. The display device 105 is for displaying various types of information and is realized by, for example, a display, etc. The communication interface device 106 includes a LAN card, etc., and is used for connecting to other devices, etc.

[0056] The program according to this embodiment is at least a part of various programs that control the information processing device 10. The program is provided, for example, by distributing a storage medium 108 or by downloading it from a network. The storage medium 108 on which the program is recorded can be of various types, including storage media that record information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, or a magneto-optical disk, and semiconductor memories that record information electrically, such as a ROM or a flash memory.

[0057] When storage medium 108 storing the program is set in drive device 107, the program is installed from storage medium 108 into auxiliary storage device 103 via drive device 107. A program downloaded from a network is installed into auxiliary storage device 103 via communication interface device 106.

[0058] (Calculation method for dust generation rate) Next, a method for the dust conversion rate calculation unit 13 to calculate the dust conversion rate of the raw material based on the moving speed in step S12 shown in FIG. 3 will be described.

[0059] FIG. 5 is the first diagram for explaining the meaning of symbols. FIG. 5 shows a cross section of the rotary kiln 1. ω is a symbol indicating the rotation speed of the rotary kiln 1. P bg is a symbol indicating the cross-sectional length of the boundary between the bed layer and the gas phase.

[0060] Fig. 6 is a second diagram for explaining the contents of the symbols. Fig. 6 is a diagram for explaining the symbols that indicate the change in material quantity in the kth cell when the rotary kiln 1 is divided into N cells in the longitudinal direction (Z-axis direction).

[0061] m is the symbol for the quantity of matter. Δz is the cell length. The subscripts b and g are the symbols for the bed layer and gas phase, respectively.

[0062] At this time, the amount of compound j in the bed layer m bj The movement speed in the Z-axis direction is expressed by Equation 1.

[0063]

number

[0064] where k bgj is the transfer rate coefficient from the bed layer to the gas phase, P bg is the length of the interface between the bed layer and the gas phase (see Figure 5), R bj is the reaction rate. The mass of the bed layer of compound j in the kth cell is given by Equation 2.

[0065]

number

[0066] On the other hand, the dusting rate is expressed by Equation 3.

[0067]

number

[0068] Therefore, the transfer rate coefficient k of compound j from the bed layer to the gas phase bgj and dusting rate d j The relationship is as shown in Equation 4.

[0069]

number

[0070] That is, the dust formation rate calculation unit 13 calculates the dust formation rate based on the relationship of Equation 4 in step S12 shown in FIG.

[0071] [Table 1]

[0072] Table 1 shows an example of the moving speed selected as a condition for the first simulation and the dust generation rate calculated in the process of step S12 shown in FIG.

[0073] (Calculation results of the first simulation) Next, the calculation results of the first simulation in the process of step S13 shown in FIG. 3 will be described.

[0074] 7 is a diagram showing an example of the temperature distribution inside the furnace calculated by the first simulation. Graphs 801 to 805 are graphs showing the temperature distribution inside the furnace calculated in the first simulations with simulation numbers 1 to 5 in Table 1, respectively.

[0075] Graph 800 is a graph showing a desired in-furnace temperature distribution as a one-dimensional in-furnace temperature distribution. In the process of step S14 shown in Fig. 3, the raw material particle size determination unit 18 determines the dusting rate (0.10 from Table 1) corresponding to the simulation number (simulation number 2 corresponding to graph 802) that results in a result close to the desired in-furnace temperature distribution (graph 800).

[0076] The dusting rate calculation unit 13 may execute the process of step S12 described above following step S14. In this case, in step S14, the raw material particle size determination unit 18 determines a simulation number that results in a temperature distribution close to the desired in-furnace distribution. Then, the dusting rate calculation unit 13 may calculate only the dusting rate corresponding to the determined simulation number.

[0077] (Calculation results of the second simulation) Next, the calculation results of the second simulation in step S17 shown in FIG. 3 will be described.

[0078] Fig. 8 is a first diagram showing an example of the volume fraction of the raw material calculated by the second simulation, where the particle size of the raw material is 5 [µm].

[0079] Fig. 9 is a second diagram showing an example of the volume fraction of the raw material calculated by the second simulation, where the particle size of the raw material is 50 [µm].

[0080] 8 and 9 show the average volume fractions in the longitudinal direction (Z-axis direction) of a plurality of consecutive cells, for example, five cells, among the N cells obtained by dividing the rotary kiln 1 in the longitudinal direction (Z-axis direction), calculated in step S17 shown in Fig. 3. The second simulation execution unit 17 calculates the volume fractions for each of the five cells among the N divisions, as shown in Figs.

[0081] [Table 2]

[0082] Table 2 shows the relationship between the particle size of the raw material and the dusting rate calculated in step S17 shown in FIG.

[0083] Figure 10 is a diagram showing an example of the relationship between the particle size of the raw material and the dust formation rate calculated by the second simulation. Graph 906 in Figure 10 is a graph created by interpolating between the discrete values ​​of the particle size of the raw material and the dust formation rate calculated as shown in Table 2. That is, the raw material particle size determination unit 18 may interpolate between the calculated particle size of the raw material and the discrete values ​​of the dust formation rate to calculate a continuous relationship between the particle size of the raw material and the dust formation rate within the range of the dust formation rate calculated by the first simulation.

[0084] Dashed lines 901 to 905 respectively show the dusting rates calculated in the first simulations with simulation numbers 1 to 5 in Table 1. The raw material particle size determination unit 18 calculates the raw material particle size corresponding to the dusting rate determined by the first simulation (dashed line 902) to be, for example, 4 μm, based on the continuous relationship (graph 906) between the raw material particle size and the dusting rate.

[0085] In fact, it has been experimentally proven that under the first simulation conditions described above, a dust generation ratio of 0.14 provides the highest combustion efficiency. Therefore, a dust generation ratio of 0.10 calculated as a result of the first simulation is a sufficiently valid value as a result of a simple simulation.

[0086] Furthermore, the particle size of the raw material corresponding to a dusting rate of 0.14 is approximately 3 μm. Therefore, if the particle size of the raw material calculated as the result of the second simulation is 4 μm, this is a sufficiently valid value as a result of a simple simulation. For example, the user can calculate a more accurate particle size by conducting experiments focusing on values ​​close to the calculated particle size.

[0087] According to the information processing device 10 of this embodiment, in a pyrometallurgical process using a rotary kiln, a simulation (first simulation) is performed to calculate a one-dimensional temperature distribution in the furnace, and a simulation (second simulation) is performed to calculate the relationship between the particle size of the raw material and the dusting rate of the raw material by fluid calculation of a three-dimensional multiphase flow. By using these two simulations in combination, it is possible to reduce the calculation cost for searching for a desired particle size of the raw material in the pyrometallurgical process.

[0088] Although the present invention has been described above based on the present embodiment, the present invention is not limited to the requirements set forth in the above embodiment. These requirements can be changed without departing from the spirit of the present invention, and can be appropriately determined depending on the application form. [Industrial Applicability]

[0089] The present invention can be applied to the design of raw materials, operating conditions, etc. in a pyrometallurgical process using a rotary kiln. [Explanation of symbols]

[0090] 1. Rotary kiln 2 Heater 3 Raw materials 4 Injection part 5 Injection part 10. Information processing equipment 11 First simulation condition information acquisition unit 12. Movement speed selection reception section 13 Dust generation rate calculation section 14 First Simulation Execution Unit 15 Second simulation condition information acquisition unit 16 Raw material particle size selection reception area 17 Second Simulation Execution Unit 18 Raw material particle size determination section 19 Output section 101 CPU 102 Main storage 103 Auxiliary storage device 104 Input Device 105 Display device 106 Communication interface device 107 Drive device 108 Storage medium

Claims

1. In smelting using a rotary kiln, a first simulation execution unit executes a first simulation to calculate a one-dimensional furnace temperature distribution in the rotary kiln; A second simulation execution unit that calculates the relationship between the dusting rate and particle size of the raw material in smelting using the rotary kiln by a second three-dimensional simulation of the rotary kiln; a raw material particle size determination unit that determines a particle size of the raw material to realize a desired temperature distribution in the furnace based on a calculation result of the first simulation and a calculation result of the second simulation, the first simulation executing unit executes the first simulation for each of the selected movement speeds of the raw material; a dusting rate calculation unit that calculates a dusting rate corresponding to the moving speed of the raw material; the raw material particle size determination unit determines the dusting rate corresponding to a moving speed of the raw material that results in a temperature distribution in the furnace that is close to the desired temperature distribution in the furnace, and calculates the particle size that results in the determined dusting rate based on the calculation result of the second simulation; The raw material is a carbon raw material used for smelting using a rotary kiln. Information processing device.

2. The method further includes a first simulation condition information acquisition unit that acquires first simulation condition information including a structure of the rotary kiln, operating conditions, and calculation conditions of the first simulation as conditions of the first simulation, the first simulation executing unit executes the first simulation based on the first simulation condition information. The information processing device according to claim 1 .

3. The second simulation condition information acquisition unit acquires second simulation condition information including the structure, operating conditions, and calculation conditions of the second simulation as conditions of the second simulation, the second simulation condition information including the structure, operating conditions, and calculation conditions of the second simulation, the second simulation condition information being information indicating conditions omitting part of the first simulation condition information; the second simulation executing unit executes the second simulation based on the second simulation condition information. The information processing device according to claim 2 .

4. the raw material particle size determination unit interpolates between the calculated particle sizes of the raw material and the discrete values ​​of the dusting rate to calculate a continuous relationship between the particle sizes of the raw material and the dusting rate within the range of the dusting rate calculated by the first simulation; The information processing device according to claim 1 .

5. A computer-implemented method for searching for raw material particle size, comprising: In smelting using a rotary kiln, a step of performing a first simulation to calculate a one-dimensional furnace temperature distribution in the rotary kiln; Calculating the relationship between the dusting rate and particle size of the raw material in smelting using the rotary kiln by a second three-dimensional simulation of the rotary kiln; determining a particle size of the raw material for realizing a desired temperature distribution in the furnace based on a calculation result of the first simulation and a calculation result of the second simulation; In the step of executing the first simulation, the first simulation is executed for each of the selected moving speeds of the raw material, further comprising a step of calculating a dusting rate corresponding to the moving speed of the raw material; In the step of determining the particle size of the raw material, the dusting rate corresponding to the moving speed of the raw material that results in a temperature distribution in the furnace close to the desired temperature distribution in the furnace is determined, and the particle size that results in the determined dusting rate is calculated based on the calculation result of the second simulation; The raw material is a carbon raw material used for smelting using a rotary kiln. Raw material particle size search method.

6. On the computer, In smelting using a rotary kiln, a step of performing a first simulation to calculate a one-dimensional furnace temperature distribution in the rotary kiln; Calculating the relationship between the dusting rate and particle size of the raw material in smelting using the rotary kiln by a second three-dimensional simulation of the rotary kiln; determining a particle size of the raw material to realize a desired temperature distribution in the furnace based on the calculation results of the first simulation and the calculation results of the second simulation; In the step of executing the first simulation, the first simulation is executed for each of the selected moving speeds of the raw material, further comprising a step of calculating a dusting rate corresponding to the moving speed of the raw material; In the step of determining the particle size of the raw material, the dusting rate corresponding to the moving speed of the raw material that results in a temperature distribution in the furnace close to the desired temperature distribution in the furnace is determined, and the particle size that results in the determined dusting rate is calculated based on the calculation result of the second simulation; The raw material is a carbon raw material used for smelting using a rotary kiln. program.

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