JP2024059325A - Coke manufacturing method - Google Patents

Abstract

[Problem] To provide a method for analyzing the void volume around a molded coal that occurs when a coal blend containing molded coal and powdered coal is packed into a container, capable of analyzing the void volume around the molded coal with high accuracy regardless of the properties of the coal blend, a method for estimating the void volume around the molded coal using said analysis method, and a method for producing high-strength coke using said analysis method or said estimation method. [Solution] A method for analyzing the void volume around a molded coal that occurs when a coal blend containing molded coal and powdered coal is packed into a container, comprising the steps of: performing an expansion process in which the periphery of the molded coal part is expanded by one unit volume per time in a shape similar to the molded coal part in a 3D analysis of an X-ray CT cross-sectional image; multiplying the volume of the area that has increased in volume each time with the difference between the average density of the powdered coal part and the average density of the void part to calculate a packing reduction amount; accumulating the packing reduction amount over the total number of expansion processes to calculate an accumulated packing reduction amount; and using the accumulated packing reduction amount as an index of the void volume around the molded coal. [Selected Figure] Figure 1

Description

The present invention relates to a method for producing coke.

Conventionally, in the manufacture of coke used in blast furnace operation, various methods have been considered to address the depletion of high-quality highly caking coal resources while maintaining good coke strength by increasing the blending ratio of inferior coal such as non- or slightly caking coal in a coal blend consisting of molded coal and pulverized coal. In order to obtain the desired coke strength using a coal blend containing inferior coal, a coal pre-treatment process can be useful. For example, as a coal drying process, the Coal Moisture Coal (CMC) method, the Dry-cleaned and Agglomerated Pre-compaction System (DAPS) method, etc., as a process for blending molded materials such as molded coal, the Dry-cleaned and Agglomerated Precompaction System (DAPS) method, the molded coal blending method, and other methods for adjusting the crushed particle size of coal are known, and these are appropriately combined.

By appropriately adjusting the particle size composition and moisture content of the powdered coal using the above-mentioned coal pretreatment process, it is possible to reduce the remaining voids in the coke and obtain good coke strength, even if the powdered coal has a relatively low expansiveness. However, when molded coal is blended, voids are generated around the molded coal, and the voids around the molded coal may remain even after carbonization. Since the remaining voids around the molded coal cause a decrease in coke strength, it is important to manufacture molded coal that has sufficient expansiveness to fill the voids around the molded coal during carbonization. In order to understand the expansiveness of the molded coal required to fill the voids around the molded coal and to determine the blend of coals that make up the coal blend, it is important to accurately estimate the amount of voids around the molded coal in the coal blend charged into the coke oven.

Patent Document 1 provides a method for producing coke by charging a coal blend made of briquettes and pulverized coal powder into a coke oven and carbonizing the mixture, in which the briquettes and pulverized coal powder are naturally dropped into a container using a test device, a cross-sectional image of the inside of the container is taken by X-ray CT, and the maximum width W of the voids formed around the briquettes is quantified from the cross-sectional image obtained. The test device is also used to measure the maximum expansion volume of the briquettes during carbonization, and the expansion amount of the briquettes is calculated as the change in the equivalent circle diameter Δr (mm) before and after expansion. If the change Δr is less than 40% of the maximum width W (mm), the coal blend that makes up the briquettes is changed, a coal blend is determined such that the change Δr is 40% or more of the maximum width W, and the briquettes produced based on this blend are used.

JP 2014-224242 A

In the method described in Patent Document 1, the voids around the briquettes in a coal blend containing briquettes and pulverized coal are evaluated as their width using two-dimensional image analysis. However, this method still has room for improvement in terms of the accuracy of the evaluation when the voids around the briquettes are too small, when pulverized coal containing agglomerated coal is used, etc.

In addition, when producing coke, the amount of voids around the coal briquettes obtained by the method described in Patent Document 1 can be used to calculate the value of the expansion of the coal briquettes (specific volume (SV)) required to obtain the target coke strength, thereby determining the blend of coals that make up the coal blend. However, if the particle size composition of the powdered coal used is changed, there is a problem in that the correspondence between the briquettes SV required to obtain the target coke strength obtained by the method described in Patent Document 1 and the target coke strength may not match the correspondence between the actual measured value of the briquettes SV and the actual measured value of the coke strength.

As described above, the method described in Patent Document 1 leaves room for further improvement in order to enable highly accurate analysis of the amount of voids around the molded coal, regardless of the powder coal particle size composition.

One aspect of the present invention aims to solve the above problems and provide a method for analyzing the amount of voids around molded coal, which is capable of analyzing with high accuracy the voids around molded coal that occur when a coal blend containing molded coal and powdered coal is filled into a container, regardless of the particle size composition of the powdered coal, a method for estimating the amount of voids around molded coal using said analysis method, and a method for producing high-strength coke using said analysis method or said estimation method.

The gist of the present invention is as follows.
[1] A method for analyzing a volume of voids around briquettes that occurs when a coal blend containing briquettes and powdered coal is packed into a container, comprising:
Using a test device, the briquettes and powdered coal are loaded into a test vessel by gravity.
A cross-sectional image of the inside of the test vessel is taken using X-ray CT.
The amount of voids around the molded coal is calculated by 3D analysis of the obtained cross-sectional image.
In the 3D analysis,
A high density portion having a density exceeding a predetermined value and a low density portion having a density equal to or lower than the predetermined value are defined,
filtering the densified portion with predetermined shape parameters to define a briquette portion;
Optionally, a region of the high density part other than the molded coal part and having a volume exceeding a predetermined value is defined as an agglomerated coal part, and the agglomerated coal part is excluded from the analysis target by treating it as having no pixel data;
An expansion process is performed (n+1) times or more in which one unit volume is expanded from the periphery of the molded coal part in a shape similar to the molded coal part each time, where n is a natural number;
The (n+1) is a number at which the average density of the region whose volume has increased by the (n+1)th expansion process is substantially equal to the average density of the region whose volume has increased by the nth expansion process,
The average density of the area whose volume has increased by the nth or subsequent expansion process is set as a threshold value.
Regarding the region whose volume has increased in each expansion treatment, the region whose density exceeds the threshold value is defined as a powder coal portion, and the region whose density is equal to or less than the threshold value is defined as a void portion,
Calculate the difference between the average density of the powder coal portion and the average density of the void portion for the area whose volume has increased in each expansion treatment,
calculating a filling reduction amount by multiplying the volume of the area that has increased in volume in each expansion process by the difference value;
The amount of packing decrease is integrated over the total number of expansion processes to calculate an integrated amount of packing decrease, and the integrated amount of packing decrease is used as an index of the amount of voids around the molded coal.
A method for analyzing the amount of voids around molded coal.
[2] A method for estimating a volume of voids around briquettes that occurs when a coal blend containing briquettes and powdered coal is packed into a container, comprising:
A plurality of blended coal samples are prepared by combining each of a plurality of powdered coal samples selected to include different levels of particle size composition and different levels of moisture content with an arbitrarily selected molded coal sample;
For each coal blend sample, the accumulated packing reduction amount of the sample was determined according to the analysis method for the void volume around the coal briquettes described in [1] above;
Based on the relationship between the particle size composition and moisture content of the powder coal sample and the cumulative loading reduction amount of the sample, a relationship formula (I) between the particle size composition and moisture content of the powder coal sample and the cumulative loading reduction amount is obtained;
For a blended coal which is a combination of powdered coal to be used in coke production and arbitrarily selected briquettes for analysis, a particle size composition and a moisture content of the powdered coal to be used are substituted into the relational formula (I) to calculate an estimated cumulative packing reduction amount, and the estimated cumulative packing reduction amount is used as an index of the amount of voids around the briquettes.
A method for estimating the amount of voids around briquettes.
[3] A method for producing coke using a blended coal containing molded coal and powdered coal, comprising:
For a coal blend sample selected for testing, a relational expression (II) between an accumulated packing reduction amount calculated by the analysis method of the void volume around the coal briquette described in the above [1] and a lower limit of the coal briquette SV range in which the coke strength is constant even if the coal briquette SV is changed is obtained in advance;
For a blended coal which is a combination of powder coal to be used in coke production and arbitrarily selected coal briquettes for analysis, an accumulated packing reduction is calculated according to the analysis method for the void volume around the coal briquettes described in [1] above, or an estimated accumulated packing reduction is calculated according to the estimation method for the void volume around the coal briquettes described in [2] above,
The integrated filling reduction amount or the estimated integrated filling reduction amount is substituted into the relational expression (II) to obtain a lower limit value of the briquette coal part SV;
Produce briquettes having an actual SV value equal to or greater than the lower limit SV value of the briquettes,
The blended coal composed of the powdered coal to be used and the produced molded coal is subjected to coke production.
Coke manufacturing method.

According to one aspect of the present invention, a method for analyzing the amount of voids around molded coal, which is generated when a coal blend containing molded coal and powdered coal is filled into a container, can be provided that can analyze with high accuracy the voids around the molded coal regardless of the particle size composition of the powdered coal, a method for estimating the amount of voids around molded coal using the analysis method, and a method for producing high-strength coke using the analysis method or the estimation method.

FIG. 2 is a schematic diagram illustrating an image processing flow according to one aspect of the present invention. FIG. 4 is a schematic diagram for explaining a filling reduction amount. FIG. 1 is a diagram showing particle size distribution of powdered coal used in the examples and the conventional example. FIG. 2 is a diagram showing an X-ray CT image in Example 1. FIG. 1 is a diagram showing the relationship between the number of expansion treatments and the amount of filling reduction when pulverized coal (moisture content: 4% by mass) is used in Example 1. FIG. 1 is a diagram showing the relationship between the number of expansion treatments and the amount of filling reduction when pulverized coal (moisture content: 10% by mass) is used in Example 1. FIG. 1 is a diagram showing the relationship between the number of expansion treatments and the amount of packing reduction when granulated coal is used in Example 1. FIG. 1 is a diagram showing the relationship between the number of expansion treatments and the amount of packing reduction when a combination of coarse coal and agglomerated coal is used in Example 1. FIG. 1 is a diagram showing the relationship between the distance from molded coal and the amount of change in bulk density when pulverized coal (moisture content: 4% by mass) is used in Conventional Example 1. FIG. 1 is a diagram showing the relationship between the distance from molded coal and the amount of change in bulk density when pulverized coal (moisture content: 10% by mass) is used in Conventional Example 1. FIG. 1 is a diagram showing the relationship between the distance from the molded coal and the amount of change in bulk density when granulated coal is used in Conventional Example 1. FIG. 11 is a diagram showing the relationship between the distance from the briquettes and the amount of change in bulk density when a combination of coarse coal and agglomerated coal is used in Conventional Example 1. 1 is a diagram showing the relationship between the mass fraction of powder coal on a 3 mm sieve and the cumulative filling reduction amount in Example 2. FIG. 11 is a diagram showing the relationship between the 6 mm sieve mass fraction of powder coal and the cumulative filling reduction amount in Example 2. FIG. 11 is a diagram showing the relationship between the mass mean diameter of powder coal and the cumulative amount of packing reduction in Example 2. FIG. 11 is a diagram showing the relationship between the moisture content of powder coal and the cumulative amount of packing reduction in Example 2. This is a figure showing the relationship between the cumulative loading reduction amount estimated from the 3 mm sieve mass fraction and moisture content of powder coal in Example 2-1 and the cumulative loading reduction amount obtained by the procedure of Example 1. This is a figure showing the relationship between the cumulative filling loss amount estimated from the 6 mm sieve mass fraction and moisture content of the powder coal in Example 2-2 and the cumulative filling loss amount obtained by the procedure of Example 1. FIG. 11 is a diagram showing the relationship between the cumulative packing reduction amount estimated from the mass mean diameter and moisture content of powder coal in Example 2-3 and the cumulative packing reduction amount obtained by the procedure of Example 1. This is a diagram showing the relationship between the cumulative loading reduction amount estimated from the 3 mm sieve mass fraction of powdered coal in Reference Example 1 and the cumulative loading reduction amount obtained by the procedure of Example 1. This figure shows the relationship between the cumulative loading reduction amount estimated from the 6 mm sieve mass fraction of powdered coal in Reference Example 2 and the cumulative loading reduction amount obtained by the procedure of Example 1. 13 is a diagram showing the relationship between the cumulative packing reduction amount estimated from the mass mean diameter of powder coal in Reference Example 3 and the cumulative packing reduction amount obtained by the procedure of Example 1. FIG. 13 is a diagram showing the relationship between the cumulative loading reduction amount estimated from the moisture content of powdered coal in Reference Example 4 and the cumulative loading reduction amount obtained by the procedure of Example 1. FIG. This is a diagram showing the relationship between the cumulative loading reduction amount estimated from the 3 mm sieve mass fraction and moisture content of powder coal in Example 2-4 and the cumulative loading reduction amount obtained by the procedure of Example 1. This is a diagram showing the relationship between the cumulative loading reduction amount estimated from the 6 mm sieve mass fraction and moisture content of powder coal in Example 2-5 and the cumulative loading reduction amount obtained by the procedure of Example 1. FIG. 13 is a diagram showing the relationship between the cumulative packing reduction amount estimated from the mass mean diameter and moisture content of powder coal in Example 2-6 and the cumulative packing reduction amount obtained by the procedure of Example 1. FIG. 1 is a graph showing the relationship between the molded coal part SV and the coke strength DI ¹⁵⁰ ₆ when granulated coal was used in Evaluation Example 1. FIG. 1 is a diagram showing the relationship between the molded coal part SV and the coke strength DI ¹⁵⁰ ₁₅ when granulated coal was used in Evaluation Example 1. FIG. 1 is a graph showing the relationship between the molded coal part SV and the coke strength DI ¹⁵⁰ ₆ when pulverized coal (moisture content: 4 mass%) was used in Evaluation Example 1. FIG. 1 is a graph showing the relationship between the molded coal part SV and the coke strength DI ¹⁵⁰ ₆ when pulverized coal (moisture content: 10 mass%) was used in Evaluation Example 1. FIG. ₁₃ is a graph showing the relationship between the value based on Comparative Evaluation Example 1 and the value based on a carbonization test with respect to the lower limit value of the briquette part SV, which is the limit at which the coke strength DI ¹⁵⁰ 15 is maintained constant. FIG. 1 is a diagram showing the relationship between the cumulative packed-in reduction amount in Example 1 and the lower limit value of the briquette coal part SV, which is the limit at which the coke strength DI ¹⁵⁰ ₆ is maintained constant, in Evaluation Example 1. FIG. 1 is a diagram showing the relationship between the cumulative packed decrease amount in Example 1 and the lower limit value of the briquette part SV, which is the limit at which the coke strength DI ¹⁵⁰ _-15 is maintained constant, in Evaluation Example 1. FIG. 13 is a graph showing the relationship between the cumulative packed decrease amount in Example 2-5 and the lower limit value of the briquette part SV, which is the limit at which the coke strength DI ¹⁵⁰ ₆ is maintained constant in Evaluation Example 1.

The following describes exemplary aspects of the present invention (sometimes referred to as the present embodiment in this disclosure), but the present invention is not limited to the following aspects.

[Method for analyzing the amount of voids around molded coal]
One aspect of the present invention provides a method for analyzing the amount of voids around the briquettes in a coal blend composed of pulverized coal and briquettes. In this disclosure, pulverized coal refers to pulverized coal, and includes coal whose particle size has been further adjusted after pulverization, and agglomerated coal when agglomerated coal is mixed. In this disclosure, agglomerated coal refers to coal having a spherical equivalent radius of less than 6 mm obtained by adding a caking filler to pulverized coal (in one aspect, pulverized coal under a 0.3 mm sieve) and pressurizing the briquettes. In this disclosure, briquetted coal refers to coal having a spherical equivalent radius of 6 mm or more obtained by adding a caking filler to pulverized coal (in one aspect, pulverized coal under a 0.3 mm sieve) and pressurizing the briquettes.

In the method for analyzing the amount of voids around the molded coal according to this embodiment, a cross-sectional image of the blended coal obtained using X-ray computed tomography (CT) is analyzed in 3D. When attempting to evaluate the voids around the molded coal by 3D analysis of the cross-sectional image, the voids are areas with low packing but not completely zero density, so the evaluation results change depending on which area is considered to be a void. In the method described in the aforementioned Patent Document 1, the voids are evaluated by the width from the edge of the molded coal through 2D analysis of the cross-sectional image, so it is difficult to determine the area to be considered as a void when the voids are small. In particular, when agglomerated coal and molded coal are mixed, they cannot be clearly distinguished from each other, so the accuracy of distinguishing the molded coal is low, making it difficult to evaluate the amount of voids around the molded coal with high accuracy.

The inventors therefore came up with the idea of evaluating the voids around the molded coal by 3D analysis of cross-sectional images, and in doing so, adopting an index called the amount of packing reduction, which takes into account the weight of volume by multiplying the density by the volume in areas considered to be voids.

One aspect of the present invention is
A method for analyzing a volume of voids around briquettes that occurs when a coal blend containing briquettes and powdered coal is packed into a container, comprising:
Using a test device, the briquettes and pulverized coal are loaded into a test vessel by gravity.
A cross-sectional image of the inside of the test vessel is taken using X-ray CT.
The amount of voids around the molded coal is calculated by 3D analysis of the cross-sectional image obtained.
In the 3D analysis,
A high density portion having a density exceeding a predetermined value and a low density portion having a density equal to or lower than the predetermined value are defined,
The high density portion is filtered with a predetermined shape parameter to define it as a briquette portion;
Optionally, a region of the high density portion other than the molded coal portion and having a volume exceeding a predetermined value is defined as an agglomerated coal portion, and the agglomerated coal portion is excluded from the analysis target by treating it as having no pixel data;
An expansion process is performed (n+1) times or more in which one unit volume is expanded from the periphery of the molded coal part in a shape similar to the molded coal part each time, where n is a natural number;
The (n+1) is a number at which the average density of the region whose volume has increased by the (n+1)th expansion process is substantially equal to the average density of the region whose volume has increased by the nth expansion process,
The average density of the area whose volume has increased by the nth or subsequent expansion process is set as a threshold value.
Regarding the region whose volume has increased in each expansion treatment, the region whose density exceeds the threshold value is defined as a powder coal portion, and the region whose density is equal to or less than the threshold value is defined as a void portion,
Calculate the difference between the average density of the powder coal portion and the average density of the void portion for the area whose volume has increased in each expansion treatment,
calculating a filling reduction amount by multiplying the volume of the area that has increased in volume in each expansion process by the difference value;
The amount of packing decrease is integrated over the total number of expansion processes to calculate an integrated amount of packing decrease, and the integrated amount of packing decrease is used as an index of the amount of voids around the molded coal.
A method for analyzing the amount of voids around a coal mold is provided.
Evaluation using the amount of packing reduction enables highly accurate quantitative evaluation of the amount of voids around the molded coal, without restrictions on the size and shape of the voids.

In this disclosure, the expansion process refers to a process that considers one voxel (unit volume) (central voxel) and its 26 adjacent voxels (peripheral voxels), calculates the maximum value of the peripheral voxels, and if it is greater than the value of the central voxel, replaces the value of the central voxel with the maximum value. In cross-sectional images, the molded coal is denser (i.e. has a larger X-ray CT value) than its surroundings, so by performing this expansion process on the periphery of the molded coal, the molded coal is expanded into a similar shape at one voxel per time.

Figure 1 is a schematic diagram illustrating an image processing flow in one embodiment of the present invention. In the method of this embodiment, the voids around the molded coal are analyzed by performing 3D analysis in steps S12 to S18 on the X-ray CT cross-sectional image acquired in step S11. Below, an example of the procedure for the method of analyzing the amount of voids around the molded coal according to this embodiment will be described with reference to Figure 1.

(Step S11)
In this step, the briquettes and the powdered coal are filled into the test vessel by natural drop using a test device, and a cross-sectional image of the inside of the test vessel is taken by X-ray CT. The coal constituting each of the briquettes and the powdered coal may be one type or a combination of two or more types. In one embodiment, the powdered coal includes agglomerated coal, or does not include agglomerated coal. The test device and the X-ray CT device may be commercially available devices, and the measurement conditions of the X-ray CT may be appropriately set as desired. From the viewpoint of obtaining good analysis accuracy, the voxel size is preferably small, but is not particularly limited. In one embodiment of the present invention, it is set to 0.488 mm x 0.488 mm x 0.488 mm.

(Step S12)
In steps S12 to S18, software attached to the X-ray CT scanner may be used for the 3D analysis. In step S12, the analysis range (hereinafter also referred to as ROI) in the cross-sectional image (hereinafter also referred to as original image) acquired in step S11 is binarized according to density, and a high density part whose density exceeds a preset value and a low density part whose density is equal to or lower than the preset value are respectively defined. The preset value may be appropriately set so that the briquettes and agglomerated coal, if present, are classified into the high density part, and the powder coal part other than the agglomerated coal is classified into the low density part, and may be, for example, 1.0 g/cm ³ .

(Step S13)
In this step, the high density portion is filtered with a predetermined shape parameter to define a briquette portion. The briquette portion may be defined by the following procedure.
a) For the high density portion defined in step S12, small particles (in one embodiment, small particles of 100 voxels or less) are removed to remove noise.
b) After the above process of a), the particles in the high density portion are separated so that they can be distinguished one by one. The separation may be performed by a labeling process.
c) From the high density portion after the processing of b), a region corresponding to the molded coal is extracted by filtering with a preset shape parameter. The preset shape parameter is set so as to accurately define the molded coal portion, and in one embodiment, may be one or more of anisotropy (irregularity), flatness (flatness), elongation (elongation), volume (volume), etc. A combination of anisotropy, flatness, and elongation is preferred in that desired filtering can be easily performed regardless of the size of the molded coal. For example, filtering may be performed with anisotropy < 0.9, flatness < 0.4, and elongation > 0.4, etc.
d) Detect and remove constrictions from the area extracted in c) above. This is because molded coal generally has constrictions at the burr portion. Constrictions may be detected using the watershed method.
e) The area after processing d) above is processed in the following order: one contraction (i.e., one voxel contraction process), small particle removal in the same procedure as a) above, one expansion (i.e., one voxel expansion process), and smoothing, and the remaining area is defined as the molded coal part.

(Step S14)
This step may be performed only when the powdered coal contains agglomerated coal. In this step, the area of the high density portion defined in step S12 that is other than the briquetted coal portion defined in step S13 and has a volume exceeding a predetermined value is defined as the agglomerated coal portion. The agglomerated coal portion is treated as having no pixel data. When the powdered coal contains agglomerated coal, the agglomerated coal has a sphere-equivalent radius of less than 6 mm but has a high density similar to that of briquetted coal. If such agglomerated coal is included in the region to be expanded in addition to the briquetted coal, there is a risk that the voids cannot be accurately evaluated. Therefore, when the blended coal contains agglomerated coal, the agglomerated coal is excluded from the analysis target.

Specifically, the molded coal part defined in step S13 is subtracted from the high density part defined in step S12, and the remaining area is labeled. From this labeled area, the agglomerated coal part is extracted by filtering based on volume (in one embodiment, only areas that satisfy a volume parameter of Volume>15 ^mm3 are selected).

When the coal blend contains agglomerated coal, voids are formed around the agglomerated coal in addition to around the briquettes. When agglomerated coal is present around the briquettes, the amount of packing drop around the briquettes may include the amount of packing drop around the agglomerates, so it is possible to determine the amount of packing drop around the agglomerates and subtract it from the amount of packing drop around the briquettes. However, according to the study by the inventors, the proportion of the amount of packing drop around the agglomerates included in the amount of packing drop around the briquettes is small, and the presence of voids around the agglomerates has a small effect on coke strength. Therefore, in the evaluation of the amount of packing drop in this embodiment, the amount of packing drop around the agglomerates does not need to be taken into account. Specifically, in the 3D analysis of this embodiment, the area corresponding to the agglomerated coal is treated as an area that does not have pixel data and is therefore excluded from the analysis target of this embodiment. In this invention, the cumulative amount of packing drop refers to the amount of packing drop around the briquettes.

(Step S15)
In this step, within the ROI of the original image, the expansion process is performed (n+1) times or more to expand one unit volume (i.e., one voxel) per time from the periphery of the molded coal part in a shape similar to the molded coal part from the periphery of the molded coal part. Here, n is a natural number. (n+1) is a number in which the average density of the area whose volume has increased by the (n+1)th expansion process is approximately the same as the average density of the area whose volume has increased by the nth expansion process. Here, approximately the same can be exemplified by the average density of the area whose volume has increased by the (n+1)th expansion process being within ±0.3% in one embodiment with respect to the average density of the area whose volume has increased by the nth expansion process. Here, ±0.3% is equivalent to the measurement variation and is not particularly limited to this value.

Each time an expansion process is completed, the volume of the area that has increased by that expansion process (i.e., the volume increase by one expansion process) and the average density are calculated. The volume corresponds to the number of voxels in the area whose volume has increased. The average density is calculated by averaging the CT values of each voxel in the area whose volume has increased by the number of voxels in that area. The expansion process is performed at least until the average density of the area that has increased by one expansion process becomes approximately the same even if the number of expansion processes is increased. The total number of expansion processes may be (n+1) times, or may be more than (n+1), for example, 10 times or more, or 20 times or more. In one aspect, the total number of expansion processes may be 30 to 50 times, for example, 30 times.

(Step S16)
In this step, the average density of the area whose volume has increased by the expansion process from the nth time onwards is set as a threshold value, and for the area whose volume has increased by each expansion process, areas whose density exceeds this threshold are defined as powdered coal areas, and areas whose density is below this threshold are defined as void areas.

(Step S17)
Next, for the area whose volume has increased in each expansion process, a difference value between the average density of the powder coal part and the average density of the void part is calculated. The average density of the powder coal part is a value obtained by averaging the CT values of each voxel contained in the powder coal part by the number of voxels in the entire powder coal part, and the average density of the void part is a value obtained by averaging the CT values of each voxel contained in the void part by the number of voxels in the entire void part. Next, the volume of the area whose volume has increased in each expansion process is multiplied by the difference value to calculate the amount of filling reduction.

(Step S18)
In this step, the amount of packing reduction calculated in step S17 is integrated over the total number of expansion processes to calculate the integrated amount of packing reduction. This integrated amount of packing reduction can be used as an index of the amount of voids around the molded coal. FIG. 2 is a schematic diagram illustrating the amount of packing reduction of the present disclosure. The amount of packing reduction calculated as described above in this step changes due to the presence of voids up to a certain number of expansion processes (in one embodiment, the above n times), but if the number of times exceeds this number (in one embodiment, the above (n+1) times or more), the amount of packing reduction becomes almost constant because there are no voids in the area increased by the expansion process. For example, in FIG. 2, the amount of packing reduction in the area increased by one expansion process changes up to the eighth expansion process, but after the ninth expansion process, the amount of packing reduction becomes almost constant from the value of the eighth expansion process. The cumulative value of the amount of packing reduction through the number of expansion processes until the amount of packing reduction becomes almost constant reflects the total amount of voids present around the molded coal. From the above viewpoint, in one embodiment, the integrated amount of packing reduction obtained by summing the amount of packing reduction over the total number of expansion processes that is (n+1) times or more is useful as an index of the amount of voids around the molded coal.

[Method for estimating the amount of voids around molded coal]
Another aspect of the present invention provides a method for estimating a void volume around a briquette in a coal blend composed of fine coal and briquette.

For example, in the method described in the aforementioned Patent Document 1, when using various types of powdered coal with different properties such as particle size composition and moisture content, it was necessary to analyze the cross-sectional image each time. On the other hand, by using the method for analyzing the void volume around the molded coal according to the present embodiment, it is possible to estimate the layered packing drop amount of powdered coal with various different properties without actual image analysis by determining in advance the relationship between the particle size composition, moisture content, and other properties of the powdered coal and the layered packing drop amount.

Factors that affect the cumulative packing loss amount include the particle size composition of the powdered coal, the moisture content of the powdered coal, and other factors. However, according to the inventors' study of the cumulative packing loss amount obtained using the analysis method for the voids around the molded coal according to this embodiment, it is believed that the particle size composition of the powdered coal and the moisture content of the powdered coal have a particularly large effect on the void volume around the molded coal. Among the particle size composition, it is believed that the mass proportion of coarse particles contained in the powdered coal has a particularly large effect. It is also believed that the moisture content of the powdered coal affects the void volume around the molded coal by affecting the fluidity of the powdered coal.

Therefore, we came up with the idea of developing a method to estimate the voids around the briquettes by using the particle size composition of the pulverized coal, preferably the mass proportion of coarse particles in the pulverized coal, and determining the relationship between the combination of the particle size composition and the moisture content of the pulverized coal and the cumulative amount of packing reduction.

One aspect of the present invention is
A method for estimating a volume of voids around briquettes that occurs when a coal blend containing briquettes and powdered coal is filled into a container, comprising:
A plurality of blended coal samples are prepared by combining each of a plurality of powdered coal samples selected to include different levels of particle size composition and different levels of moisture content with an arbitrarily selected molded coal sample;
For each blended coal sample, the accumulated sample packing reduction amount was obtained according to the method for analyzing the void volume around the briquettes of this embodiment;
Based on the relationship between the particle size composition and moisture content of the powder coal sample and the cumulative loading reduction amount of the sample, a relationship formula (I) between the particle size composition and moisture content of the powder coal sample and the cumulative loading reduction amount is obtained;
For a blended coal which is a combination of powdered coal to be used in coke production and arbitrarily selected briquettes for analysis, a particle size composition and a moisture content of the powdered coal to be used are substituted into the relational formula (I) to calculate an estimated cumulative packing reduction amount, and the estimated cumulative packing reduction amount is used as an index of the amount of voids around the briquettes.
A method for estimating the amount of voids around a coal mold is provided.

<Selection of powdered coal sample>
The pulverized coal samples used in the estimation method of this embodiment are selected so as to include different levels of particle size composition and different levels of moisture content. The pulverized coal samples may include levels in which the particle size composition or moisture content is the same. The pulverized coal samples are composed of a group of levels in which the particle size composition and moisture content each have two or more, preferably three or more, different values in one embodiment. From the viewpoint of estimation accuracy, it is advantageous to have a large number of different values, but from the viewpoint of work efficiency, the number of different values may be 10 or less, or 8 or less, in one embodiment.

The value of the particle size composition used for the estimation is, in one embodiment, the value of the mass proportion of coarse particles, and is preferably one value selected from the group consisting of the sieve mass proportion and the particle size. The size of the briquettes is usually assumed to be 30 cc to 120 cc. The sieve size of the sieve mass proportion as an index of the mass proportion of coarse particles in the briquettes, more specifically, the mesh size according to JIS Z 8801-1, is typically 2 mm or more, and preferably 2.8 mm or more, or 5.6 mm or more. In one embodiment, the sieve size may be 8 mm or less, or 6.7 mm or less, from the viewpoint of more accurately estimating the effect of the coarse particles in the briquettes on the amount of voids around the briquettes. As the particle size, the mass average diameter, which is an index to which the presence of coarse particles greatly contributes, is preferable, but other average particle diameters, or parameters obtained by functional expression of the particle size distribution (e.g., 50% diameter), etc. may be adopted.

<Derivation of Relational Formula (I)>
For each coal blend sample, the sample cumulative packing loss is calculated according to the method for analyzing the void volume around the briquettes according to one embodiment of the present invention described above, and then, based on the relationship between the particle size composition and moisture content of the powder coal sample and the sample cumulative packing loss, a relational expression (I) between the particle size composition and moisture content of the powder coal sample and the cumulative packing loss is derived. In one embodiment, the relational expression (I) is expressed as the following relational expression (I-1).
Accumulative filling reduction amount = a × [value of particle size composition of powder coal] + b × [value of moisture content of powder coal] + c (I-1)
(In the formula, a and b are coefficients derived from the relationship between the particle size composition and moisture content of the powder coal sample and the cumulative sample loading reduction amount, and c is a constant term derived from the relationship between the particle size composition and moisture content of the powder coal sample and the cumulative sample loading reduction amount.)
The method of deriving the relational expression (I) from the relationship between the particle size composition and moisture content of the powder coal sample and the cumulative sample loading reduction amount may be, but is not limited to, a multivariate analysis such as a simple regression analysis or a multiple regression analysis. Each of these exemplary analysis procedures will be described below.

(Simple regression analysis)
In the simple regression analysis according to one embodiment, the particle size distribution and the moisture content are each used as a variable, and the relationship between each of these and the cumulative filling loss of the sample may be linearly or polynomially regression-based, typically linearly regression-based. Specifically, the particle size distribution and the moisture content are plotted on the x-axis, and the cumulative filling loss is plotted on the y-axis, and a simple regression equation may be obtained from the plot by, for example, linear regression using the least squares method.

Next, the value of the regression coefficient (in one embodiment, the slope of the linear regression equation) obtained from the simple regression equation showing the relationship between the particle size composition and the cumulative loading reduction amount is set as coefficient a of the above-mentioned relational equation (I-1), and the value of the regression coefficient (in one embodiment, the slope of the linear regression equation) obtained from the simple regression equation showing the relationship between the moisture content and the cumulative loading reduction amount is set as coefficient b of the relational equation (I-1). The coefficient c may be, for example, 0 or may be a value other than 0. In this way, the relational equation (I-1) can be obtained as the relational equation (I) between the particle size composition and moisture content of the powder coal and the cumulative loading reduction amount.

(Multiple regression analysis)
In the multiple regression analysis according to one embodiment, both the particle size composition and the moisture content are variables, and the relationship between these variables and the cumulative filling loss of the sample may be linearly or polynomially regression-based, typically linearly regression-based. Specifically, a multiple regression analysis may be performed in which the particle size composition and the moisture content are explanatory variables, and the cumulative filling loss is the objective variable. According to the study by the present inventors, since there is no strong correlation between the particle size composition and the moisture content, using them as explanatory variables may be advantageous in terms of performing a significant multiple regression analysis. The regression may be performed, for example, by the least squares method, but is not limited thereto.

Next, the regression coefficient values obtained from the multiple regression equation showing the relationship between the particle size composition and moisture content and the cumulative loading reduction amount are set as the coefficients a and b of the above-mentioned relational equation (I-1), and the intercept value of the multiple regression equation is set as the coefficient c. This makes it possible to obtain the above-mentioned relational equation (I-1) as the relational equation (I) between the particle size composition and moisture content of powder coal and the cumulative loading reduction amount. Note that in multiple regression analysis, it is possible to obtain the relational equation (I-1) in which the intercept c (i.e., the constant term) is 0 by standardization, but standardization may also be omitted.

There is no particular limitation on the method for confirming whether the multiple regression analysis has been performed effectively, and the test may be performed by a conventional method. The significance level may be selected as desired, for example, 5% or 1%. If the regression results do not satisfy the significance level, the parameters selected as the particle size composition may be changed and the multiple regression analysis may be performed again, and this operation may be repeated until the significance level is satisfied. When the on-sieve mass fraction is used as the particle size composition, if the multiple regression analysis using the on-sieve mass fraction at a certain sieve size does not satisfy the significance level, the sieve size may be changed to a larger one and the multiple regression analysis may be performed again. Increasing the sieve size of the on-sieve mass fraction, which is a variable, tends to decrease the significance F, which is preferable.

In the above, we have described the case where the particle size composition and moisture content of the powdered coal are used as variables in estimating the amount of voids around the molded coal, but if there are other factors that significantly affect the amount of layered packing reduction, it is possible to use those other factors instead of or in addition to the particle size composition and/or moisture content. For example, although the above example shows a case where there are two explanatory variables in the multiple regression analysis, there may be three or more explanatory variables.

<Calculation of Estimated Accumulative Charging Reduction Amount>
By using the relational expression (I) derived by the procedure exemplified above, an estimated cumulative packing loss amount of the coal blend can be calculated. In one embodiment, for a coal blend that is a combination of powder coal to be used in coke production and arbitrarily selected briquettes for analysis, the particle size composition and moisture content of the powder coal to be used are substituted into the relational expression (I) to calculate an estimated cumulative packing loss amount. This estimated cumulative packing loss amount can be used as an index of the void volume around the briquettes.

[Coke manufacturing method]
One aspect of the present invention also provides a method for producing coke using a coal blend containing molded coal and powdered coal. The inventors have found that by analyzing the amount of voids around the molded coal with high accuracy using the index of the packing drop amount of this embodiment, it is possible to produce high-strength coke while using a large amount of inferior coal. According to the study by the inventors, the coke strength of a coal blend containing molded coal and powdered coal is almost constant when the SV of the molded coal part is equal to or higher than a predetermined value, but when it falls below the predetermined value, it tends to decrease as the SV of the molded coal part decreases. This tendency is observed regardless of the expansion property, moisture content, and particle size composition of the powdered coal, and the predetermined value differs when the cumulative packing drop amount differs. Molded coal with a low SV can be inexpensive because it is of inferior quality. Therefore, it is advantageous in terms of obtaining high-strength coke at low cost to obtain the above-mentioned predetermined value of the SV of the briquettes, i.e., the lower limit value of the briquettes SV, which is the limit value at which the coke strength does not decrease when the briquettes SV is reduced, and to select and use briquettes showing this lower limit value of the briquettes SV. The relational expression (II) between the cumulative packing reduction amount and the lower limit value of the briquettes SV is obtained in advance, the cumulative packing reduction amount is obtained for a coal blend containing the powdered coal to be used, and this is substituted into the above relational expression (II) to calculate the lower limit value of the briquettes SV. The briquettes having an SV equal to or greater than the lower limit value of the briquettes SV can be blended with the powdered coal to be used. In order to form a coal blend capable of forming a high-strength coke while using a large amount of inferior coal, the closer the value is to the lower limit value of the briquettes SV, the more preferable it is. Specifically, taking into consideration that the variation in SV of the briquette coal part in actual operation is usually about ±0.1 cm ³ /g, it is preferable to blend briquette coal having an SV value of the lower limit of the briquette coal part SV +0.1 cm ³ /g with the powdered coal to be used.

In the coke manufacturing method of this embodiment,
A) For a coal blend selected for testing, a relational expression (II) between an accumulated packing reduction amount calculated by the method for analyzing the void volume around the briquettes of the present embodiment and a lower limit value of the briquettes SV, which is the lower limit of the range of the briquettes SV such that the coke strength is constant even if the briquettes SV is changed, is obtained in advance;
B) For a combination of powdered coal to be used in coke production and arbitrarily selected coal briquettes for analysis, B1) calculate an accumulated packing reduction amount using the analysis method of the void volume around the coal briquettes of this embodiment, or B2) calculate an estimated accumulated packing reduction amount using the estimation method of the void volume around the coal briquettes of this embodiment,
C) Substituting the accumulated charge reduction amount obtained in B1) or the estimated accumulated charge reduction amount obtained in B2) into the relational formula (II) to obtain a lower limit value of the briquette coal part SV;
D) Briquettes having an actual SV value equal to or greater than the lower limit SV value of the briquettes are produced, and a coal blend consisting of the powder coal to be used and the produced briquettes is subjected to coke production.
This will be explained in more detail below.

(Derivation of the relationship between the cumulative filling reduction amount and the lower limit value of the briquette coal part SV (II))
In the above A), for the coal blend selected for testing, a relational expression (II) between the cumulative packing reduction amount calculated by the method for analyzing the void volume around the briquettes in this embodiment and the lower limit value of the briquettes SV, which is the limit value at which the coke strength does not decrease when the briquettes SV is reduced, is obtained in advance. In one embodiment, multiple levels of powder coal with different moisture content and/or particle size composition and multiple levels of briquettes with different SV are selected. For the test coal blend combining each level of powder coal with one arbitrarily selected level of briquettes, the cumulative packing reduction amount is calculated by the method in this embodiment. For example, when three levels of powder coal and ten levels of briquettes are selected, the cumulative packing reduction amount is calculated for a total of three types of test coal blends. As the briquettes to be used for calculating the cumulative packing reduction amount, those without defects, etc. are selected from the multiple levels.

The lower limit of the briquette coal part SV, which is the limit value at which the coke strength does not decrease when the briquette coal part SV is reduced, is determined as follows.
a) For each level of briquettes selected for testing, the SV is measured by a carbonization test using a dilatometer in accordance with JIS M8801.
b) For each of the cokes obtained from the test coal blends, the coke strength is measured by a drum test in accordance with JIS K 2151. In one embodiment, the coke strength may be DI ¹⁵⁰ ₁₅ or DI ¹⁵⁰ _6. DI ¹⁵⁰ ₁₅ is the proportion of 15 mm oversize after 150 rotations in a drum test, and is an index that mainly represents the volumetric breaking strength of the coke, and DI ¹⁵⁰ ₆ is the proportion of 6 mm undersize after 150 rotations in a drum test, and is an index that mainly represents the surface breaking strength of the coke.
c) For all test coal blends, the relationship between the briquette SV (x-axis) and the coke strength (y-axis) obtained from the test coal blend is plotted for each level of powder coal. For example, when three levels of powder coal and ten levels of briquette coal are selected, a first plot is prepared for the test coal blend relating to a combination of a first level of powder coal and each of the first to tenth levels of briquette coal, a second plot is prepared for the test coal blend relating to a combination of a second level of powder coal and each of the first to tenth levels of briquette coal, and a third plot is prepared for the test coal blend relating to a combination of a third level of powder coal and each of the first to tenth levels of briquette coal. For each plot, the minimum value of the briquette SV in the region where the coke strength is maintained constant regardless of the value of the briquette SV is defined as the lower limit of the briquette SV. The region where the coke strength is maintained constant regardless of the value of the molded coal SV means a region where the value of the coke strength falls within the standard deviation in each plot. For example, when the standard deviation of each plot is 0.4, the region where the coke strength is maintained constant regardless of the value of the molded coal SV is a region where the coke strength falls within the range of ±0.4. In this way, the molded coal SV lower limit value for each level of powder coal is obtained. Note that if the degree of increase in the coke strength (y-axis) obtained from the test blended coal with respect to the increase in the molded coal SV (x-axis) clearly changes and is maintained at approximately the same value, it can be considered as a region where the strength is maintained constant, and the judgment is not limited to the standard deviation.
d) The cumulative packing reduction amount for each level of powdered coal calculated above is plotted on the x-axis, and the molded coal part SV lower limit value for each level of powdered coal specified above is plotted on the y-axis, and a relationship equation (II) between the cumulative packing reduction amount and the molded coal part SV lower limit value is derived, for example, by linear approximation.

(Selection of candidate coals for use in coke production)
In the above B1), for a combination of powder coal to be used in coke production and arbitrarily selected briquettes for analysis, the cumulative packing reduction amount is calculated using the analysis method for the void volume around the briquettes of this embodiment. Briquettes that have no defects may be selected.

Or, in the above B2), for a combination of powdered coal to be used in coke production and arbitrarily selected coal briquettes for analysis, an estimated cumulative packing reduction amount is obtained using the method for estimating the void volume around the coal briquettes of this embodiment.

In C) above, the cumulative packing reduction amount calculated in B1) above or the estimated cumulative packing reduction amount calculated in B2) above is substituted into the relational expression (II) calculated in A) above to calculate the lower limit of the briquette SV. This lower limit of the briquette SV indicates the limit at which the briquette SV can be lowered (i.e., inferior briquette can be utilized) without causing a decrease in coke strength due to briquette (more specifically, due to voids remaining in the coke due to insufficient expansion of the briquette during coking) in the blended coal containing the powdered coal to be used.

In the above D), molded coal is produced whose actual SV value is equal to or greater than the molded coal part SV lower limit value obtained above. The actual SV value of the molded coal produced is preferably as close to the molded coal part SV lower limit value as possible, but considering that the variation in the molded coal part SV in actual operation is usually about ±0.1 cm ³ /g, for example, a value of the molded coal part SV lower limit value +0.1 cm ³ /g is preferable. Such molded coal may be of the lowest quality to the extent that it does not cause a decrease in coke strength due to the molded coal. The actual SV value of the molded coal can be adjusted to a desired value, for example, by adjusting the type and/or amount of coal and/or caking filler used in the production of the molded coal. By subjecting a blended coal using the molded coal produced as described above to coke production, it is possible to produce coke that is inexpensive yet maintains a desired coke strength.

The following provides further explanation of exemplary aspects of the present invention with reference to examples, but the present invention is not limited to these examples.

[Example 1]
<Analysis of void volume around molded coal>
(Coal used)
For the analysis, pulverized coal of levels 1 to 4 shown in Table 1 and molded coal without defects were used. Note that "pulverized coal" refers to the coal itself obtained by crushing pulverized coal, "coarse coal" refers to coal excluding fine powder with a particle size of less than 0.3 mm, and "pre-sized coal" refers to coal with a particle size of 0.3 mm to 3 mm. The particle size distribution of each type of pulverized coal is shown in Figure 3. Pillow-type molded coal with a particle size of about 40 mm was used.

The voids around the molded coal were analyzed based on the amount of packing reduction using the following procedure.

(Step S11)
Using a test device, molded coal and powdered coal were filled into a test vessel by gravity falling, and cross-sectional images of the inside of the test vessel were taken by X-ray CT.

The test equipment used was a Mini ASTM device (drop height 1 m), which is a half-scale version of the ASTM improved bulk density measuring device (Kiyotaka et al., Coke Circular, 30 (11), 13-5 (1981)) that has the following improved conditions in the bulk density test according to ASTM D 291-86.

Into the test vessel (150 x 150 x 150 mm) of the Mini ASTM device, 1.5 kg of the powdered coal of each level was dropped, then molded coal (cup size 30 cc, particle size 39 mm in spherical equivalent) was dropped, and finally the remaining 2.75 kg of powdered coal of each level was dropped to fill the coal. The sample vessel filled with coal was photographed with an X-ray CT diagnostic device (TSX-201 (Aquilion LB) manufactured by Toshiba Medical Systems Corporation). The shooting conditions of the X-ray CT are as follows. A resolution of 0.488 mm per pixel was obtained under the following shooting conditions.
Scan mode: Helical
Tube voltage: 120 kV
Tube current: 400mA
FOV (field of view): 440 mm
Imaging slice thickness: 0.5 mm

The cross-sectional images obtained were processed using the image analysis software Avizosa. All analyses were performed in three dimensions. The region of interest (ROI) was set to the central 120 mm rectangular area (i.e., the central portion (120 x 120 x 120 mm) of the vessel dimensions (150 x 150 x 150 mm)) to eliminate wall effects.

(Step S12)
Based on the X-ray CT value of each pixel in the ROI, density (BD) was calculated using the following formula:
BD(t/ ^m3 )=0.001×(X-ray CT value)+1
The density was calculated according to the following formula: A region where the density exceeds 1.0 g/ ^cm3 is defined as a high density portion, and a region where the density is 1.0 g/cm3 or ^less is defined as a low density portion.

(Step S13)
a) For the high density portion defined in step S12, small particles of 100 voxels or less were removed.
b) The high density portion after the above process a) was subjected to a labeling process so that the particles could be separated and distinguished one by one.
c) From the high density portion after the above process b), only particles satisfying the shape parameters of anisotropy<0.9, flatness<0.4, and elongation>0.4 were selected as irregular shaped particles.
d) For the irregularly shaped particles extracted in c) above, constrictions were detected and removed using the watershed method.
e) The irregular particles after the above d) process were processed in the following order: 1 voxel shrinkage, small particle removal in the same procedure as above a), 1 voxel expansion, and smoothing, and the remaining area was defined as the molded charcoal part. All expansion and contraction processes were performed in a spherical shape (ball dilation/ball erosion).

(Step S14)
This step was performed only for the level including agglomerated coal. The molded coal part defined in step S13 was subtracted from the high density part defined in step S12, and the remaining area was labeled. From this labeled area, only the area satisfying the volume parameter Volume>15 ^mm3 was selected as the agglomerated coal part. This area was excluded from the analysis by performing mask processing.

(Step S15)
Within the ROI of the original image, the expansion process was performed 30 times for the molded coal part defined in step S13 above, in which one voxel was expanded each time from the periphery of the molded coal part in a shape similar to the molded coal part.

(Step S16)
Each time the expansion process was completed, the volume of the area increased by one expansion process (i.e., the volume increase by one expansion process) and the average density were calculated. Since the average density hardly changed after 21 expansion processes, the average density after 21 expansion processes was defined as the average density of the powder coal part. This average density was defined as a threshold value, and the area exceeding the threshold value was defined as the powder coal part, and the area below the threshold value was defined as the void part.

(Step S17)
The average density of the powdered coal part was determined as the number average of the densities calculated from the X-ray CT values of each voxel corresponding to the powdered coal part, and the average density of the void part was determined as the number average of the densities calculated from the X-ray CT values of each voxel corresponding to the void part, and the difference between the average density of the powdered coal part and the average density of the void part was calculated. The amount of filling reduction was calculated for each expansion treatment according to the following formula.
Filling reduction amount = [Volume of the area that has increased in volume in each expansion treatment] x [Difference between the average density of the powder coal part and the average density of the void part]

(Step S18)
The amount of packing loss was integrated by the number of expansion treatments to calculate the integrated amount of packing loss. Figure 2 shows the integrated amount of packing loss when using powder coal of coarse coal + agglomerated coal (moisture 4 mass%). The hatched area in Figure 2 corresponds to the integrated amount of packing loss. The integrated amount of packing loss was used as an index of the amount of voids around the molded coal.

As shown in Figure 2, in void evaluation using the cumulative filling reduction amount as an index, when the expansion process is performed more than a certain number of times (8 times in Figure 2), the variation in the filling reduction amount due to the number of expansion processes almost disappears, and therefore it can be seen that good evaluation results can be obtained by performing the expansion process more than a certain number of times.

Figure 4 shows X-ray CT images of examples using powdered coal at levels 1 to 4. Comparing the CT images of levels 1 and 2, which have different moisture contents, it was found that level 1, which has less moisture, had smaller voids than level 2, which has more moisture. In addition, comparing the CT images of levels 1, 3, and 4, which have different particle size structures, it was found that voids were smaller in granulated coal (level 3) than in pulverized coal (level 1), coarse coal, and agglomerated coal (level 4).

Figures 5 to 8 show the relationship between the number of expansion treatments and the cumulative amount of charge reduction in Example 1, using each of the powdered coal levels 1 to 4.

[Conventional Example 1]
Using the same blended coal as in Example 1, the width of the voids around the molded coal was evaluated in the following manner according to the method described in Patent Document 1 (particularly paragraphs 0020 to 0026).
The molded coal portion extracted by binarization was used as the selected region, and the molded coal portion was expanded n times with a unit width a (mm) = 0.488 mm. The density BDp,n of the powder coal portion excluding the region separated from the edge of the molded coal by a width Xn (= a × n) (mm) was obtained, and Xn when the change in BDp,n+1-BDp,n with respect to Xn converged to a specified range was defined as the width of the gap around the molded coal.

Figures 9 to 12 show the relationship between the distance X from the molded coal using each of the powdered coals of levels 1 to 4 in Conventional Example 1 and the amount of change in bulk density at each expansion treatment.

The analysis results of the cumulative packing reduction amount around the briquettes (Example 1) and the analysis results of the maximum width of the gap around the briquettes (Conventional Example 1), obtained from the results shown in Figures 5 to 12, are shown in Table 1.

In the evaluation of the maximum width of the voids in Conventional Example 1, the void width of pulverized coal (Level 1) was smaller than that of granulated coal (Level 3). In contrast, in the evaluation of the cumulative packing reduction amount in Example 1, the void value of pulverized coal (Level 1) was larger than that of granulated coal (Level 3), which was the opposite result to Conventional Example 1. It is believed that the method in Conventional Example 1 was unable to correctly distinguish between the powdered coal portion and the voids. The analysis results based on the cumulative packing reduction amount in Example 1 are in good agreement with the CT image shown in Figure 4, and the cumulative packing reduction amount was the smallest under the granulated coal condition (Level 3) among levels 1 to 4. From the above, it can be seen that the analysis method in Example 1 is superior to the analysis method in Conventional Example 1.

We investigated whether the cumulative packing drop amount around the briquettes would change when multiple briquettes were used. As a method of investigation, a coal blend consisting of 70% crushed coal by mass and 30% briquettes by mass of level 2 was prepared and mixed thoroughly in advance. The mixed coal blend was filled into a test vessel by gravity using a test device, and a cross-sectional image of the inside of the test vessel was taken by X-ray CT. The above steps S12 to S18 were carried out to analyze the captured cross-sectional image. The number of briquettes in the analysis region was calculated by dividing the volume of the briquettes by the volume of one briquettes, and was found to be approximately 11.2. The absolute value of the cumulative packing drop amount when multiple briquettes were used was calculated to be 6.83 g (0.61 g per briquettes), and it was confirmed that this value was close to the cumulative packing drop amount of 0.68 g for level 2 shown in Table 1 for Example 1.

[Example 2]
<Estimation of void volume around briquettes>
In Example 2, a method for estimating the amount of voids around the briquettes using factors that affect the voids around the briquettes without image analysis was examined. From the results of FIG. 4 and Table 1, it can be seen that the size of the voids around the briquettes is affected by the particle size composition of the powdered coal (more specifically, the proportion of coarse particles) and the moisture content of the powdered coal. In this example, as the particle size composition of the powdered coal, attention was paid to the mass proportion of the powdered coal on a 3 mm sieve, the mass proportion of the powdered coal on a 6 mm sieve, and the mass average diameter. All of these are indicators of the proportion of coarse particles in the powdered coal. In addition, the moisture content of the powdered coal is thought to affect the fluidity of the powdered coal, and therefore to affect the cumulative packing reduction amount. Note that factors that affect the cumulative packing reduction amount are not limited to the particle size composition and moisture content of the powdered coal, but in this example, the estimation was performed by focusing on the particle size composition and moisture content, which are the main factors that have a large influence on the cumulative packing reduction amount. In the Examples and Reference Examples, for the sake of convenience, sieves having mesh sizes of 2.8 mm and 5.6 mm conforming to JIS Z 8801-1 are referred to as 3 mm sieves and 6 mm sieves, respectively.

(1) Examples 2-1 to 2-3: Combination of simple regression analysis In this example, simple regression analysis was performed with the particle size composition and moisture content of the powder coal as explanatory variables and the cumulative packing loss as the objective variable. Using the obtained regression coefficients, a relationship between the particle size composition and moisture content and the cumulative packing loss was obtained. As the particle size composition, one was selected from the mass fraction of the powder coal on a 3 mm sieve, the mass fraction of the powder coal on a 6 mm sieve, and the mass average diameter of the powder coal.

(Coal used)
For the estimation, powdered coal of levels 1 to 4 shown in Table 1 and molded coal without defects, etc., similar to those used in Example 1, were used.

(Estimation Procedure)
For each of the combinations of the powdered coal and the molded coal, the cumulative packing loss was determined in the same manner as in Example 1, and plotted as shown in Figures 13 to 16. Figure 13 is a diagram showing the relationship between the mass ratio on a 3 mm sieve and the cumulative packing loss, Figure 14 is a diagram showing the relationship between the mass ratio on a 6 mm sieve and the cumulative packing loss, Figure 15 is a diagram showing the relationship between the mass mean diameter and the cumulative packing loss, and Figure 16 is a diagram showing the relationship between the moisture content and the cumulative packing loss. As shown in Figures 13 to 16, a simple regression was performed by linear regression using the least squares method from the plotted values to obtain a regression equation. Using the regression coefficient, which is the slope of each regression equation, a relationship equation (I) between the particle size composition and moisture content and the cumulative packing loss was derived.

(Example 2-1)
The 3 mm sieve mass fraction and moisture content were each used as explanatory variables, the cumulative filling reduction amount was used as an objective function, and the regression coefficient (=0.0222) of the simple regression equation shown in FIG. 13 and the regression coefficient (=0.0539) of the simple regression equation shown in FIG. 16 were used to obtain the following relational equation (2-1) as relational equation (I).
Accumulative filling reduction amount = [3 mm sieve mass ratio of powder coal (mass%)] × 0.0222 + [moisture content of powder coal (mass%)] × 0.0539 (2-1)
Figure 17 shows the relationship between the estimated cumulative loading reduction amount calculated by substituting the 3 mm sieve mass fraction and moisture content of each powdered coal into the above formula, and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

(Example 2-2)
The 6 mm sieve mass fraction and moisture content were each used as explanatory variables, the cumulative filling reduction amount was used as an objective function, and the regression coefficient (=0.0395) of the simple regression equation shown in FIG. 14 and the regression coefficient (=0.0539) of the simple regression equation shown in FIG. 16 were used to obtain the following relational equation (2-2) as relational equation (I).
Accumulative filling reduction amount = [6 mm sieve mass ratio of powder coal (mass%)] × 0.0395 + [moisture content of powder coal (mass%)] × 0.0539 (2-2)
Figure 18 shows the relationship between the estimated cumulative loading reduction amount calculated by substituting the 6 mm sieve mass fraction and moisture content of each powdered coal into the above formula, and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

(Example 2-3)
The mass mean diameter and the moisture content were each used as explanatory variables, the cumulative filling reduction amount was used as an objective function, and the regression coefficient (=0.3347) of the simple regression equation shown in FIG. 15 and the regression coefficient (=0.0539) of the simple regression equation shown in FIG. 16 were used to obtain the following relational equation (2-3) as relational equation (I).
Accumulative packing reduction amount = [mass average diameter of powder coal (mm)] × 0.3347 + [moisture content of powder coal (mass%)] × 0.0539 (2-3)
Figure 19 is a diagram showing the relationship between the estimated cumulative loading reduction amount calculated by substituting the mass mean diameter and moisture content of each powdered coal into the above formula and the cumulative loading reduction amount obtained for each powdered coal by the procedure of Example 1.

The results shown in Figures 17 to 19 show that the cumulative packing reduction amount can be estimated by any of the methods of Examples 2-1 to 2-3 above. In other words, for a coal blend that is a combination of powdered coal to be used in coke production and arbitrarily selected molded coal for analysis, the particle size composition and moisture content of the powdered coal to be used are substituted into any of the above relational expressions (2-1) to (2-3) as relational expression (I) of the present disclosure to calculate an estimated cumulative packing reduction amount, and the estimated cumulative packing reduction amount is used as an index of the void amount around the molded coal, making it possible to accurately estimate the void amount around the molded coal in the above coal blend.

[Reference Example 1]
Using only the mass ratio on the 3 mm sieve as a variable and the regression coefficient (=0.0222) of the simple regression equation shown in FIG. 13, the cumulative filling reduction amount was calculated according to the following relational expression (A).
Accumulative filling reduction amount = [mass ratio of powder coal on 3 mm sieve (mass%)] x 0.0222 (A)
Figure 20 shows the relationship between the estimated cumulative loading reduction amount calculated by substituting the 3 mm sieve mass fraction of each powdered coal into the above formula and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

[Reference Example 2]
Using only the 6 mm sieve mass ratio as a variable and the regression coefficient (=0.0395) of the simple regression equation shown in FIG. 14, the cumulative filling reduction amount was calculated according to the following relational expression (B).
Accumulative filling reduction amount = [6 mm sieve mass ratio of powder coal (mass%)] x 0.0395 (B)
Figure 21 shows the relationship between the estimated cumulative loading reduction amount calculated by substituting the 6 mm sieve mass fraction value of each powdered coal into the above formula and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

[Reference Example 3]
Using only the mass mean diameter as a variable and the regression coefficient (=0.3347) of the simple regression equation shown in FIG. 15, the accumulated filling reduction amount was calculated according to the following relational expression (C).
Accumulative filling reduction amount = [mass average diameter of powder coal (mm)] x 0.3347 (C)
Figure 22 is a diagram showing the relationship between the estimated cumulative loading reduction amount calculated by substituting the mass mean diameter value of each powder coal into the above formula and the cumulative loading reduction amount obtained for each powder coal by the procedure of Example 1.

[Reference Example 4]
Using only the moisture content as a variable and the regression coefficient (=0.0539) of the simple regression equation shown in FIG. 16, the accumulated filling reduction amount was calculated according to the following relational expression (D).
Accumulative filling reduction amount = [moisture content of powder coal (mass%)] x 0.0539 (D)
Figure 23 is a diagram showing the relationship between the estimated cumulative loading reduction amount calculated by substituting the moisture content value of each powdered coal into the above formula and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

The results shown in Figures 20 to 23 show that in Reference Examples 1 to 4, the cumulative filling loss calculated using each of the relational expressions (A) to (D) largely deviates from the cumulative filling loss calculated using the procedure of Example 1; that is, when only one of the particle size composition and moisture content is used as a variable, the cumulative filling loss cannot be estimated with high accuracy.

(2) Examples 2-4 to 2-6: Multiple regression analysis In this example, both the particle size composition and moisture content of the powder coal were used as explanatory variables, and the cumulative packing loss was used as the objective variable, and multiple regression analysis was performed using linear regression by the least squares method. Using the regression coefficient, which is the slope of the obtained regression equation, a relationship equation (I) between the particle size composition and moisture content and the cumulative packing loss was derived. As the particle size composition, one was selected from the mass fraction of the powder coal on a 3 mm sieve, the mass fraction of the powder coal on a 6 mm sieve, and the mass average diameter of the powder coal.

It was previously confirmed by the following method that there was no strong correlation between the particle size distribution used as the explanatory variable and the moisture content.
In the graph showing the relationship between particle size distribution and moisture content, a simple regression was performed using linear regression by the least squares method from the plotted values to obtain the coefficient of determination (R2 value) of the regression equation, and it was confirmed that the tolerance (=1-R2 value) was greater than 0.1.

(Coal used)
For the estimation, pulverized coal of levels 1 to 7 shown in Table 2 and the same molded coal as in Example 1 were used. The pulverized coal of levels 1 to 4 shown in Table 2 are the same as the pulverized coal of levels 1 to 4 shown in Table 1. In this example, in addition to levels 1 to 4, coarse-grained coal (level 5) in which fine powder less than 0.3 mm in particle size was removed, pulverized coal (level 6) with a 3 mm undersieve mass ratio of 100%, and granulated coal + agglomerated coal (level 7) in which granulated coal of level 3 was blended with agglomerated coal were used. In other words, by using seven types of pulverized coal relating to levels 1 to 7, the number of samples required for appropriate multiple regression analysis was ensured.

(Estimation Procedure)
For each of the combinations of the powdered coal and the molded coal, the cumulative packing reduction amount was obtained by cross-sectional image analysis in the same manner as in Example 1. Table 2 shows the cumulative packing reduction amount under each condition. Based on the results of levels 1 to 7, a multiple regression analysis was performed using the combination of the 3 mm sieve mass fraction and moisture content of the powdered coal (for Example 2-4), the combination of the 6 mm sieve mass fraction and moisture content of the powdered coal (for Example 2-5), or the combination of the mass average diameter and moisture content of the powdered coal (for Example 2-6) as explanatory variables, and the cumulative packing reduction amount as the objective variable. At this time, 5%, which is common in multiple regression analysis, was adopted as the significance level.

(Example 2-4)
A multiple regression analysis was performed using the 3 mm sieve mass fraction and moisture content as explanatory variables. Using the regression coefficients (=0.01956, 0.03984) of the obtained regression equation, the following relational formula (2-4) was obtained as relational formula (I).
Accumulative filling loss amount = [mass ratio of powder coal on 3 mm sieve (mass%)] x 0.01956 + [moisture content of powder coal (mass%)] x 0.03984 (2-4)
In this example, when multiple regression analysis was performed assuming that the intercept was significantly different from 0, the P value of the intercept exceeded the significance level, so multiple regression analysis was performed again assuming that the intercept was not significantly different from 0 (i.e., intercept = 0), and the obtained results were adopted.
Figure 24 shows the relationship between the estimated cumulative loading reduction amount calculated by substituting the 3 mm sieve mass fraction and moisture content of each powdered coal into the above formula, and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

The above multiple regression analysis was judged to be meaningful because the upper probability (significance F) of the ratio of variances in the two groups, the cumulative filling reduction amount calculated according to the relational expression (2-4) and the cumulative filling reduction amount (i.e., the actual measured value) obtained by the procedure of Example 1, was 0.00030, which is smaller than 0.05. In addition, the P values, which are the probability that the regression coefficients of the 3 mm sieve mass fraction of powdered coal and the moisture content of powdered coal will be extreme values, were 0.00124 and 0.00788, respectively, both of which were smaller than 0.05, so each regression coefficient was judged to be a significant coefficient.

(Example 2-5)
A multiple regression analysis was performed using the 6 mm sieve mass fraction and moisture content as explanatory variables. Using the regression coefficients (=0.03366, 0.05159) of the obtained regression equation, the following relational formula (2-5) was obtained as relational formula (I).
Accumulative filling reduction amount = [6 mm sieve mass ratio of powder coal (mass%)] × 0.03366 + [moisture content of powder coal (mass%)] × 0.05159 (2-5)
In this example, when multiple regression analysis was performed assuming that the intercept was significantly different from 0, the P value of the intercept exceeded the significance level, so multiple regression analysis was performed again assuming that the intercept was not significantly different from 0 (i.e., intercept = 0), and the obtained results were adopted.
Figure 25 shows the relationship between the estimated cumulative loading reduction amount calculated by substituting the 6 mm sieve mass fraction and moisture content of each powdered coal into the above formula, and the cumulative loading reduction amount obtained for each powdered coal using the procedure of Example 1.

The above multiple regression analysis was deemed meaningful because the significance F of the analysis of variance was 0.00023, which is less than 0.05. In addition, the P values for the mass fraction of pulverized coal on the 6 mm sieve and the moisture content of pulverized coal were 0.00093 and 0.00107, respectively, both of which were less than 0.05, so each regression coefficient was deemed significant.

(Example 2-6)
A multiple regression analysis was performed using the mass average particle size and the moisture content as explanatory variables. Using the regression coefficients (=0.02924, 0.06227) and the constant term (=-0.3472) of the obtained regression equation, the following relational formula (2-6) was obtained as relational formula (I).
Accumulative filling reduction amount = [mass average diameter of powder coal (mm)] × 0.02924 + [moisture content of powder coal (mass%)] × 0.06227 - 0.3472 (2-6)
In this example, when multiple regression analysis was performed assuming that the intercept was significantly different from 0, the P value of the intercept did not exceed the significance level, so the result of the multiple regression analysis was used as is.
Figure 26 is a diagram showing the relationship between the estimated cumulative loading reduction amount calculated by substituting the mass mean diameter and moisture content of each powdered coal into the above formula and the cumulative loading reduction amount obtained for each powdered coal by the procedure of Example 1.

The above multiple regression analysis was deemed meaningful because the significance F of the analysis of variance was 0.00456, which is less than 0.05. In addition, the P values of the mass mean diameter of powdered coal, the moisture content of powdered coal, and the intercept were 0.00256, 0.01276, and 0.03849, respectively, all of which were less than 0.05, so each regression coefficient was deemed significant.

It was shown that the cumulative packing reduction amount can be estimated by any of the above methods (Example 2-4) to (Example 2-6), and that the moisture content of the powdered coal can be used as an index of the fluidity of the powdered coal. In other words, for a coal blend that is a combination of powdered coal to be used in coke production and arbitrarily selected briquettes for analysis, the particle size composition and moisture content of the powdered coal to be used are substituted into any of the above relational expressions (2-4) to (2-6) as relational expression (I) of the present disclosure to calculate an estimated cumulative packing reduction amount, and the estimated cumulative packing reduction amount is used as an index of the void amount around the briquettes, making it possible to accurately estimate the void amount around the briquettes of the above coal blend.

[Evaluation Example 1]
<Evaluation of the lower limit of SV of molded coal by carbonization test using a test coke oven>
(Coal used)
Next, for a coal blend obtained by blending powder coal with briquettes at a moisture content of 4 mass % or 10 mass %, the lower limit value of the SV of the briquettes was evaluated by a carbonization test using a test coke oven.

Table 3 shows the properties of each coal, and Tables 4 and 5 show the blending conditions for the powder coal portion of the blended coal using the coals in Table 3. Blending condition 1 was granulated coal with a particle size of 0.3 to 3 mm (moisture content: 4% by mass), blending condition 2 was pulverized coal with a 3 mm undersieve ratio of 85% (moisture content: 4% by mass), and blending condition 3 was pulverized coal with a 3 mm undersieve ratio of 85% (moisture content: 10% by mass). The mass proportion of 3 mm undersieve as the pulverized particle size was 92.5%, 85%, and 85% for blending conditions 1, 2, and 3, respectively. A tar-based binder was used as the liquid binder, and asphalt pitch (ASP) was used as the solid binder.

Table 6 shows the blending ratio of the molded coal. Powdered coal with a crushed particle size of 3 mm and a mass ratio of 90% under the sieve was molded in blends 1 to 23 using a molding machine (BMS II manufactured by Shinto Kogyo Co., Ltd.) to produce molded coal. The molded coal was a pillow type with a particle size of about 40 mm. A tar-based binder was used as the liquid binder, and asphalt pitch (ASP) was used as the solid binder. Of the three series of blends 1 to 8, 9 to 15, and 16 to 23, blends 1 to 8 and 9 to 15 were made to have almost the same ΣVM value in order to evaluate the effect of the molded coal SV, but the molded coal SV was made different. The granulated coal used in levels 1 to 8 had a powdered coal SV x BD = 1.13. SV x BD is called the void filling ratio and indicates the ratio of space that can be filled by expanded coal in a unit volume.

(Measurement of SV of molded coal by carbonization test using a dilatometer)
A carbonization test was carried out using a dilatometer. The molded coals of each blending condition shown in Table 6 were pulverized and adjusted to a particle size of 100% by mass fraction under 3 mm sieve, and then molded into a bulk density of 1.10 g/cm ³ (dry basis) and a height of 60 mm using a molding machine for a dilatometer. The molded coals were then heated at a heating rate of 3° C./min to carry out a carbonization test, and the SV of the molded coals was measured. The results are shown in Table 6.

(Measurement of coke strength by drum test)
Coal blends obtained by blending powder coal and briquettes under the conditions of levels 1 to 23 shown in Table 7 were carbonized in a test coke oven to obtain cokes, and drum tests were carried out at rotation speeds of 30 and 150 rpm, N=3. The results are shown in Table 7. For levels 1 to 8, the relationship between briquettes SV and DI ¹⁵⁰ ₆ is shown in Figure 27, and the relationship between briquettes SV and DI ¹⁵⁰ ₁₅ is shown in Figure 28.

From the briquette SV measured in the carbonization test using a dilatometer and the coke strength measured in the drum test, the lower limit of the briquette SV, which is the limit at which the coke strength is maintained constant, was determined. From the results shown in Fig. 27, it can be seen that the coke strength DI ¹⁵⁰ ₆ of the entire coal blend is almost the same when the briquette SV is in the range of more than 1.0 cm ³ /g, but when the briquette SV is lowered to 0.93 cm ³ /g or further to 0.9 cm ³ /g, the coke strength DI ¹⁵⁰ ₆ is significantly reduced. The lower limit of the briquette SV was determined as the intersection point between the straight line connecting the plots with the briquette SV of 0.9 cm ³ /g and 0.93 cm ³ /g and the straight line showing the average value of the DI ¹⁵⁰ ₆ of the other plots, and was found to be 0.97 cm ³ /g. Similarly, when ^the lower limit _of the briquette SV was calculated for the relationship between ^the briquette SV and DI ¹⁵⁰ ₁₅ shown in FIG.

Similarly, the lower limit of the molded coal part SV obtained from Figure 29, which shows the relationship between the molded coal part SV and DI ¹⁵⁰ ₆ for levels 9 to 15 (i.e., blends containing pulverized coal with a moisture content of 4 mass%, which is blending condition 2), was 1.10 cm ³ /g, and the lower limit of the molded coal part SV obtained from Figure 30, which shows the relationship between the molded coal part SV and DI ¹⁵⁰ ₆ for levels 16 to 23 (i.e., blends containing pulverized coal with a moisture content of 10 mass%, which is blending condition 3), was 1.50 cm ³ /g.The lower limit of the molded coal part SV obtained from the coal blends using pulverized coal was higher than that of the coal blends using granulated coal.

[Comparative Evaluation Example 1]
From the maximum width of the voids around the briquettes obtained by the method according to Conventional Example 1, the following formula (1) described in Patent Document 1 (JP 2014-224242 A):
Δr = r {(SV × ρ) ^1/3 - 1} (1)
(where r is the circle equivalent radius (mm) before expansion, SV is the expansion specific volume of the briquettes (cm ³ /g), and ρ is the density of the briquettes (g/cm ³ ).)
The lower limit of the briquette part SV, which is the limit at which the coke strength DI ¹⁵⁰ is kept constant _{at 15} , was determined using the above formula. The following process was carried out to determine this lower limit.

The maximum width of the gap around the coal briquette in Conventional Example 1 shown in Table 1 is the maximum width of the gap around one coal briquette, and is different from the maximum width of the gap around multiple coal briquette pieces as described in Patent Document 1. When the number of coal briquette pieces increases, low density areas will be combined when the coal briquette pieces are close to each other, so the maximum width of the gap around the coal briquette pieces is thought to be calculated as a larger value when there are multiple coal briquette pieces compared to when there is one coal briquette. Therefore, when calculating the coal briquette part SV, the maximum width of the gap around the coal briquette pieces in the example using level 2 powder coal shown in Table 1 was corrected by multiplying it by about 3.1 so that the value of the maximum width of the gap around the coal briquette pieces in the example using level 2 powder coal shown in Table 1 matches the 5.37 mm described in paragraph 0044 of the example in Patent Document 1.

In Patent Document 1, the range of the briquette SV in which the coke strength DI ¹⁵⁰ ₁₅ of the entire coal blend is maintained constant is examined under blending conditions in which the briquette SV and ΣVM are changed, and therefore the briquette SV in which the coke strength DI ¹⁵⁰ ₆ is maintained constant is different from the briquette SV in which the coke strength DI ¹⁵⁰ ₁₅ is maintained constant. Patent Document 1 does not disclose evaluation conditions that can determine the range of the briquette SV in which the DI ¹⁵⁰ ₆ is maintained constant.

Therefore, in this comparative evaluation example, when the maximum width of the gap around the molded coal at level 2 in Table 1 is 5.37 mm, the change in sphere equivalent radius Δr before and after the expansion of the molded coal was calculated as Δr = w × 0.75 (where w is the maximum width of the gap around the molded coal) so that the lower limit SV of the molded coal part obtained from the above formula (1) described in Patent Document 1 would be ^{1.50 cm3} /g.

[Evaluation results]
The relationship between the lower limit of the briquette SV calculated in Comparative Evaluation Example 1 and the lower limit of the briquette SV calculated based on the briquette SV obtained in the carbonization test is shown in Table 8 and Figure 31. In particular, in Level 3 (sizing coal conditions), the lower limit of the briquette SV of 1.40 ^cm3 /g based on Comparative Evaluation Example 1 was significantly different from the lower limit of the briquette SV of 0.97 ^cm3 /g based on the carbonization test. This is thought to be because the method of analyzing the amount of voids around the briquette based on the maximum void width according to Conventional Example 1 was unable to correctly distinguish between the powder coal part and the voids under the sizing coal conditions, in which the particle size composition of the powder coal part is different from that of the conventional method.

On the other hand, when the relationship between the cumulative packing reduction amount around the briquettes shown in Table 1 and the lower limit SV of the briquettes, which is the limit at which the coke strength DI ¹⁵⁰ ₆ is maintained constant as shown in Figures 27, 29, and 30, was summarized (Figure 32), a strong correlation was obtained. The lower limit SV of the briquettes, which is the limit at which the coke strength DI ¹⁵⁰ ₆ is maintained constant, was obtained using the correlation equation obtained from Figure 32 as the relational equation (II) of the present disclosure, and the results were 0.95 cm ³ /g under blending condition 1 (sizing coal condition), 1.12 cm ³ /g under blending condition 2 (crushed coal condition, moisture content 4 mass%), and 1.49 cm ³ /g under blending condition 3 (crushed coal condition, moisture content 10 mass%). In particular, the lower limit value of the SV of the molded coal part under the granulated coal conditions was closer to the value of 0.97 ^cm3 /g under the granulated coal conditions in the carbonization test than comparative evaluation example 1, which shows that the method of analyzing the void volume around the molded coal based on the cumulative filling reduction amount in Example 1 has higher analytical accuracy than the analysis method in Conventional Example 1.
Similarly, a strong correlation was also obtained in the relationship between the cumulative packing decrease amount around the briquettes and the lower limit of the briquettes SV, which is the limit at which the coke strength DI ¹⁵⁰ ₁₅ is maintained constant (FIG. 33). Therefore, the lower limit of the briquettes SV of a coal blend can be accurately predicted based on the relationship between the cumulative packing decrease amount around the briquettes and the lower limit of the briquettes SV, which is the limit at which the coke strength is maintained constant. By producing briquettes with a low SV at a limit that does not fall below the lower limit of the briquettes SV and using the briquettes in coke production, it becomes possible to produce inexpensive, high-strength coke.

In addition, when the relationship between the estimated cumulative packing reduction amount (x-axis) calculated according to the relational expression (2-5) in Example 2-5 and the lower limit value of the molded coal part SV (y-axis), which is the limit at which the coke strength DI ¹⁵⁰ ₆ is maintained constant, is summarized as in FIG. 34, it was confirmed that a strong correlation was obtained, as in FIG. 32 in which the cumulative packing reduction amount obtained by the procedure of Example 1 is on the x-axis.

Claims (3)

A method for analyzing a volume of voids around briquettes that occurs when a coal blend containing briquettes and powdered coal is packed into a container, comprising:
Using a test device, the briquettes and powdered coal are loaded into a test vessel by gravity.
A cross-sectional image of the inside of the test vessel is taken using X-ray CT.
The amount of voids around the molded coal is calculated by 3D analysis of the obtained cross-sectional image.
In the 3D analysis,
A high density portion having a density exceeding a predetermined value and a low density portion having a density equal to or lower than the predetermined value are defined,
filtering the densified portion with predetermined shape parameters to define a briquette portion;
Optionally, a region of the high density part other than the molded coal part and having a volume exceeding a predetermined value is defined as an agglomerated coal part, and the agglomerated coal part is excluded from the analysis target by treating it as having no pixel data;
An expansion process is performed (n+1) times or more in which one unit volume is expanded from the periphery of the molded coal part in a shape similar to the molded coal part each time, where n is a natural number;
The (n+1) is a number at which the average density of the region whose volume has increased by the (n+1)th expansion process is substantially equal to the average density of the region whose volume has increased by the nth expansion process,
The average density of the area whose volume has increased by the nth or subsequent expansion process is set as a threshold value.
Regarding the region whose volume has increased in each expansion treatment, the region whose density exceeds the threshold value is defined as a powder coal portion, and the region whose density is equal to or less than the threshold value is defined as a void portion,
Calculate the difference between the average density of the powder coal portion and the average density of the void portion for the area whose volume has increased in each expansion treatment,
calculating a filling reduction amount by multiplying the volume of the area that has increased in volume in each expansion process by the difference value;
The amount of packing decrease is integrated over the total number of expansion processes to calculate an integrated amount of packing decrease, and the integrated amount of packing decrease is used as an index of the amount of voids around the molded coal.
A method for analyzing the amount of voids around molded coal. A method for estimating a volume of voids around briquettes that occurs when a coal blend containing briquettes and powdered coal is filled into a container, comprising:
A plurality of blended coal samples are prepared by combining each of a plurality of powdered coal samples selected to include different levels of particle size composition and different levels of moisture content with an arbitrarily selected molded coal sample;
For each coal blend sample, an integrated sample packing reduction amount is obtained according to the method for analyzing the void volume around the coal briquettes described in claim 1;
Based on the relationship between the particle size composition and moisture content of the powder coal sample and the cumulative loading reduction amount of the sample, a relationship formula (I) between the particle size composition and moisture content of the powder coal sample and the cumulative loading reduction amount is obtained;
For a blended coal which is a combination of powdered coal to be used in coke production and arbitrarily selected briquettes for analysis, a particle size composition and a moisture content of the powdered coal to be used are substituted into the relational formula (I) to calculate an estimated cumulative packing reduction amount, and the estimated cumulative packing reduction amount is used as an index of the amount of voids around the briquettes.
A method for estimating the amount of voids around briquettes. A method for producing coke using a blended coal containing molded coal and powdered coal,
For a coal blend sample selected for testing, a relational expression (II) between an accumulated packing reduction amount calculated by the method for analyzing the void volume around the coal briquette according to claim 1 and a lower limit value of the coal briquette SV, which is a lower limit of the range of the coal briquette SV in which the coke strength is constant even if the coal briquette SV is changed, is previously obtained;
For a blended coal which is a combination of powder coal to be used in coke production and arbitrarily selected coal briquettes for analysis, an integrated packing reduction amount is calculated according to the analysis method for the void volume around the coal briquettes as described in claim 1, or an estimated integrated packing reduction amount is calculated according to the estimation method for the void volume around the coal briquettes as described in claim 2,
The integrated filling reduction amount or the estimated integrated filling reduction amount is substituted into the relational expression (II) to obtain a lower limit value of the briquette coal part SV;
Produce briquettes having an actual SV value equal to or greater than the lower limit SV value of the briquettes,
The blended coal composed of the powdered coal to be used and the produced molded coal is subjected to coke production.
Coke manufacturing method.

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