Method for predicting coke strength and method for producing coke

Abstract

This invention provides a method for predicting coke strength and a method for producing coke, which enable simple and highly accurate prediction of coke strength. [Solution] A method for predicting coke strength, which predicts the strength of coke produced from blended coal containing two or more coals based on δtot defined by a predetermined formula, wherein the prediction is performed using a prediction formula in which the explanatory variable is δtot and the dependent variable is the coke strength.

Description

[Technical Field]

[0001] This invention relates to a method for predicting coke strength and a method for producing coke. [Background technology]

[0002] Coke is produced by crushing coal to a predetermined particle size and then heating it in a carbonization furnace under oxygen-free conditions. To stabilize the quality of coke, a blend of two or more types of coal is used.

[0003] Furthermore, coke functions as a reducing agent, carburizing source, and heat source for iron ore within the blast furnace. In this process, the porous structure of coke ensures the permeability and liquid permeability of the blast furnace. Therefore, coke needs to have sufficient strength to prevent collapse or pulverization during the transport and blast furnace loading processes.

[0004] Furthermore, the properties of the coal used as a raw material greatly influence the strength of coke.

[0005] Therefore, various methods are being considered to predict the strength of coke obtained by carbon distillation of the blended coal based on the physical properties of the coal used in the blend.

[0006] Conventional techniques include using the average maximum reflectance of coal vitrinite (hereinafter sometimes referred to as Ro) or the maximum fluidity (hereinafter sometimes referred to as MF) measured by the Gieseler plastometer method. It is empirically known that these physical properties of coal are related to the coke strength after carbonization. Therefore, attempts have been made to predict coke strength by creating a regression equation using Ro and MF for each coal brand selected as a raw material for coke, as well as accumulated operational data.

[0007] Furthermore, Patent Document 1 describes a method for determining the surface tension of semi-coke obtained by heat-treating coal and evaluating the adhesion between coals based on the difference in surface tension between two types of coal. [Prior art documents]

Patent Document

[0008]

Patent Document 1

Non-Patent Document

[0009]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0010] When attempting to predict the coke strength using the Ro or MF of each coal blended as a raw material for coke, it has been known that the actual coke strength often deviates from the prediction.

[0011] Also, attempts have been made to evaluate the adhesiveness between coals from the surface tension by the method of Patent Document 1 and predict the coke strength based on the adhesiveness. However, this method has problems such as complex experimental operations and long measurement time.

[0012] The present invention has been made in view of such circumstances, and an object thereof is to provide a method for predicting coke strength and a method for producing coke that enable simple and highly accurate prediction of coke strength.

Means for Solving the Problems

[0013] The gist of the present invention for solving the above problems is as follows.

[0014] 1. A method for predicting the strength of coke produced from blended coal containing two or more coals, based on δtot defined by the following formula (1): The prediction of the coke strength is performed using a prediction formula in which the δtot is included in the explanatory variables and the coke strength is the objective variable. δtot=(α×δD g 2 +β×δP g 2 +γ×δH g 2 ) 1 / 2 ······(1) Here, in formula (1), δD g : The centroid of the dispersion force term of the Hansen solubility parameters of the two or more coals δP g : The centroid of the polar term of the Hansen solubility parameters of the two or more coals δH g : The centroid of the hydrogen bond term of the Hansen solubility parameters of the two or more coals α, β, γ: Constants satisfying 1 or more and 10 or less for α / β and 1 or more and 10 or less for α / γ is.

[0015] 2. Based on the δtot described in 1 above, determine the blending of two or more coals, Based on the determined blending, produce coke from the blended coal in which the two or more coals are blended. A method for producing coke.

[0016] 3. Based on the coke strength predicted using the method for predicting coke strength described in 1 above, determine the blending of two or more coals, Based on the determined blending, produce coke from the blended coal in which the two or more coals are blended. A method for producing coke.

Advantages of the Invention

[0017] According to the present invention, it is possible to provide a method for predicting coke strength and a method for producing coke that enable simple and highly accurate prediction of coke strength.

Brief Description of the Drawings

[0018] [Figure 1]This diagram shows the relationship between crushing strength and δtot. [Figure 2] This diagram shows the relationship between crushing strength and Ro (Rotary). [Figure 3] This diagram shows the relationship between the Drum exponent and δtot. [Modes for carrying out the invention]

[0019] The following describes specific examples of embodiments of the present invention. Note that the following description is illustrative of embodiments of the present invention, and the present invention is not limited in any way to the following embodiments.

[0020] (δtot) As mentioned above, coke is obtained by carbonizing coal. In addition, a blend of two or more types of coal is generally used in the production of coke. In order to achieve high-strength coke, it is necessary to appropriately select the types of coal to be blended and to appropriately determine the blending ratio. Therefore, in the present invention, the prediction of coke strength or the determination of coal blending is performed based on δtot defined by the above formula (1).

[0021] As shown in equation (1) above, the centroids of each term and the constants α, β, and γ of the Hansen solubility parameters (hereinafter sometimes referred to as HSP) of two or more coals constituting the blended coal are used to calculate δtot.

[0022] HSP is a solubility parameter composed of a dispersion force term (δD), a polarization term (δP), and a hydrogen bonding term (δH). Solubility parameters are indicators of the surface state that can be calculated from the molecular structure and surface energy, and can be represented by a one-dimensional numerical value or a combination of multiple numerical values. In particular, HSP can be represented as a combination of the dispersion force term, the polarization term, and the hydrogen bonding term, that is, as a point in a three-dimensional space with each term as an axis.

[0023] The inventors conceived of using HSP to predict coke strength. Compared to other solubility parameters, the database for HSP is more extensive. By using this database, for example, by using a solvent with a known HSP as a reference substance, the solubility parameters of coal can be easily derived. Furthermore, the HSP of coal can be derived more easily than the indices conventionally used to predict coke strength. Moreover, HSP adequately reflects the surface state of coal molecules that affects coke strength, making it a suitable index for predicting coke strength. In other words, when each term of HSP has a large value, the intermolecular interactions, ionic bonds, and hydrogen bonds are strong, respectively. Therefore, coal with larger HSP terms has stronger intermolecular bonds and a more stable aggregated state. In carbonization, coal becomes softened and molten, and then the softened and molten coal re-solidifies with foaming. Considering that coke is produced through this process, the stronger the intermolecular bonds of coal molecules, the easier it is for the chemical structure to grow in the produced coke. And coke strength changes depending on the state of the molecules in the coke. For example, Non-Patent Document 1 shows that lamellar tissue has lower hardness compared to isotropic and mosaic tissue. Thus, the higher the anisotropy, i.e., the more the layered structure grows, the weaker the substrate strength of coke becomes. Therefore, by using HSP of coal, the chemical structure of coke, such as the degree of spread of the intramolecular carbon network structure and the degree of growth of the intermolecular layered structure, can be estimated, and the differences in coke strength due to differences in chemical structure can be predicted.

[0024] Furthermore, coke production generally uses blended coal, which is made by mixing two or more types of coal. Therefore, in this invention, coke strength is predicted using the centroid of each term of the HSP calculated from the HSP of two or more types of coal that make up the blended coal. In the following explanation, the centroid of the HSP may be referred to as the HSP of the blended coal.

[0025] The centroid of HSP can be calculated by using the proportion of coal used in the mixture, for example, the weight ratio, as the weight. The centroid of each term of HSP can be calculated from the following equations (2) to (4).

number

[0026] As shown in equation (1) above, constants α, β, and γ are used to calculate δtot. Here, since coke is mainly composed of carbon and has a prominent layered structure between molecules, it is presumed that the intermolecular forces between layers, i.e., dispersion forces, have a significant effect on the coke strength. Therefore, from the viewpoint of emphasizing the effect of the dispersion force term in HSP, α / β is set to 1 or more and α / γ is set to 1 or more. α / β is preferably 2 or more, more preferably 3 or more. α / γ is preferably 2 or more, more preferably 3 or more. On the other hand, the polarization term and hydrogen bonding term are also considered to have some effect on the coke strength. Therefore, α / β is set to 10 or less and α / γ is set to 10 or less. More preferably, α / β=4 and α / γ=4.

[0027] The method for determining the constants α, β, and γ is not particularly limited, but for multiple blended coals, the HSP of the blended coal and the strength of the coke produced from the blended coal can be determined, and the constants α, β, and γ can be determined using the HSP and coke strength. For example, the constants α, β, and γ can be determined based on the coefficient of determination when the relationship between the coke strength and δtot obtained by equation (1) above is approximated by a straight line. In this case, the combination of α, β, and γ that yields the highest coefficient of determination can be selected by regression analysis. Alternatively, the optimal combination of α, β, and γ can be selected by comparing the coefficients of determination when the values ​​of α, β, and γ are discretely varied while imposing restrictions on α, β, and γ (for example, the restriction that the constants α, β, and γ are all integers). In this case, a high coefficient of determination (for example, R) can be selected.2 From among several candidates that yield a coefficient of determination greater than 0.5, a combination of α, β, and γ may be selected using a different criterion. Furthermore, since dispersion forces arise from induced dipole-induced dipole interactions, while polarization forces and hydrogen bonding forces both arise from permanent dipole-permanent dipole interactions, the α, β, and γ that yield the highest coefficient of determination under the restriction β=γ may be searched for. In addition, a restriction may be imposed, for example, that α is an integer and β=γ=1.

[0028] [Method for predicting coke strength] In a coke strength prediction method according to one embodiment of the present invention, the strength of coke produced from blended coal containing two or more types of coal is predicted based on δtot. This makes it possible to predict coke strength with high accuracy. This is thought to be because the chemical structure of coke, which was not taken into consideration in conventional coke strength predictions, is reflected in δtot.

[0029] For example, by blending newly arrived coal and predicting coke strength based on the δtot when the combination and blending ratio of coal used are changed, it is possible to appropriately design coal combinations and blending ratios that take into account the variation in quality from lot to lot.

[0030] Blended coal is coal made by blending two or more types of coal. The number of types of coal blended is not particularly limited, but three or more is common, and it may be around 10 to 15. The blending ratio of coal in blended coal is also not particularly limited. The two or more types of coal that make up the blended coal are not particularly limited, but for example, they may be multiple types of coal of different brands, or multiple types of coal of different lots.

[0031] In this embodiment, to predict coke strength based on δtot, a prediction formula is used in which the objective variable is coke strength and the explanatory variable is δtot. The prediction formula may be a prediction formula that adds a term with δtot as a variable to a conventionally used prediction formula. Alternatively, a regression formula may be used in which the objective variable is coke strength and the explanatory variable is δtot. By substituting the value of δtot calculated from the HSP of the blended coal into a pre-prepared prediction formula, the strength of the coke produced from the blended coal can be predicted.

[0032] Examples of coke strengths that can be predicted include crushing strength and drum strength. Here, when comparing under conditions where the weighted average value of Ro in the blended coal is approximately the same, a decrease in δtot calculated based on the HSP of the blended coal tends to decrease the drum strength, while the crushing strength tends to increase. This is thought to be because the crushing test and the drum test evaluate different failure modes.

[0033] [Method of producing coke] In a coke manufacturing method according to one embodiment of the present invention, the blend of two or more coals is determined, and coke is manufactured from the blended coal containing the two or more coals based on the determined blend. In other words, the coke manufacturing method includes the steps of determining the blend of two or more coals and manufacturing coke from the blended coal containing the two or more coals based on the determined blend. Here, the blend of two or more coals is determined based on δtot or based on the coke strength predicted using the coke strength prediction method. In the step of determining the coal blend, by considering δtot or the predicted coke strength, it is possible to determine the coal blend that will yield the target coke strength, i.e., the combination of coal types and the blending ratio, or both.

[0034] The specific method for determining the coal blend is not particularly limited, but as an example, the type of coal to be blended and the blending ratio may be determined from candidate coal types for coke raw materials. In this case, rules may be established so that δtot or the predicted coke strength is within a predetermined range (for example, the coke strength is above or above a certain value), and the coal blend may be determined in accordance with these rules. If the rules are not met, the type of coal and / or the blending ratio may be changed, and the evaluation of δtot or the prediction of coke strength may be repeated. This makes it possible to stably produce high-strength coke.

[0035] As another example, a coal blend may be changed from one using a specific brand to one that does not. That is, the δtot evaluation or coke strength prediction should be performed on candidate blends using the specific brand and those not using the specific brand using the method described above, and the indicators for each blend should be compared. Then, the blend in which the δtot or predicted coke strength is close to that of the blend using the specific brand should be determined as the coal blend after the change in brand. In other words, when selecting a substitute coal for the specific brand, the substitute coal may be selected so that the δtot or predicted coke strength value is close. This minimizes the change in coke quality due to the change in brand.

[0036] (Acquisition of HSP for coal) In the above-described method for predicting coke strength and manufacturing coke, the HSP (Heat Score Quantity) of two or more coals constituting the blended coal may be obtained. Here, the HSP may be obtained separately for each coal or simultaneously. The procedure for obtaining the HSP of coal will be described below.

[0037] This procedure includes, for example, the following operations: Procedure (A): Determine the affinity between coal and the reference material. Procedure (B): Derive the HSP of coal based on the affinity and the HSP of the reference material.

[0038] [Procedure (A): Procedure for determining affinity] This procedure determines the affinity between coal and a reference material using a unified standard.

[0039] In this invention, a solvent is used as the reference substance. The type of solvent used is not limited, but a low-molecular-weight pure solvent is preferable, given the existence of a database of HSPs for solvents.

[0040] The solvents are preferably of multiple types, more preferably 10 or more types, and even more preferably 15 or more types. Selecting a larger number of solvents increases the accuracy of deriving the HSP from coal.

[0041] Furthermore, it is preferable to select the aforementioned multiple types of solvents so that they consist of solvents with various physical properties. For example, it is preferable to select a wide range of solvents, such as water and aqueous solutions that have hydrogen bonds, nonpolar organic solvents, and polar organic solvents. Examples of nonpolar organic solvents include hydrocarbon organic solvents. Examples of polar organic solvents include organic solvents having functional groups such as formyl groups, carbonyl groups, hydroxyl groups, or amino groups. This allows for the evaluation of the affinity of coal with solvents whose HSPs differ from each other, thereby improving the accuracy of deriving the HSP of coal. For example, since the values ​​of δP and δH differ greatly depending on the solvent, these values ​​can be dispersed by selecting solvents with various physical properties.

[0042] More specifically, multiple types of solvents can be used, selected to include at least one selected from the group consisting of (a), (b), and (c) below. From the perspective of using solvents with various physical properties, it is preferable to select solvents that include at least one of all of (a), (b), and (c) below. (a) Water or aqueous solution (b) Nonpolar organic solvents (c) Polar organic solvents Furthermore, one or more mixed solvents may be used as the solvent, which are obtained by mixing two or more miscible solvents in any proportion. In this case, the values ​​of each HSP term of the mixed solvent can be determined as a weighted average calculated from the values ​​of the corresponding HSP terms of the mixed solvents and the mixing ratio. Since the HSP of the mixed solvent can be adjusted by adjusting the mixing ratio, using a mixed solvent makes it easy to disperse the HSP distribution of the solvent.

[0043] Furthermore, it is preferable to select the solvent such that the HSPs are appropriately dispersed in three-dimensional space. This allows for more precise extraction of HSPs from coal using methods such as the fusion sphere method described later.

[0044] In particular, it is advisable to select solvents such that the δH of each solvent is evenly distributed within and around the expected numerical range for coal's δH. This is for the following reasons: First, since δH is a component derived from hydrogen bonding, it is thought to be related to functional groups such as hydroxyl and carboxyl groups at the molecular ends in coal. Furthermore, since these functional groups often undergo condensation and elimination due to changes in the carbon skeleton structure caused by carbonization, δH is considered to be a term that particularly influences the molecular structure of the coal being measured.

[0045] Generally, when determining the affinity between a substance and a solvent, the determination is made by whether or not the substance in question dissolves in the various solvents. However, when determining the affinity between coal and the aforementioned solvent, it is difficult to determine the affinity based on whether or not coal dissolves, since coal is generally insoluble in various solvents. Therefore, the infiltration time method described later can be used as a specific method for procedure (A). In addition to the infiltration time method, methods can also be used to determine whether or not the solvent has wettability to coal using values ​​such as the wetting area or contact angle, and to determine the affinity based on the wettability.

[0046] [Infusion Time Method] This method involves dropping a solvent onto a tablet formed from coal and determining the affinity between the coal and the solvent based on the length of time required for the solvent to penetrate. Advantages of this method include its simple experimental procedure and short time requirement. Furthermore, because the experimental procedure is simple, it does not require the experimenter to possess advanced skills, and anyone can perform accurate measurements. For example, when determining surface tension using the method described in Patent Document 1 and then evaluating the adhesion between coal particles to predict coke strength, the experimental procedure becomes complex. In particular, when measuring surface tension using the film flotation method, the operation of dropping coal particles onto the liquid surface must be performed accurately, resulting in a significant complexity of the experimental procedure and a long time due to the large number of steps. In contrast, the method of determining affinity using the penetration time method is simple in its experimental procedure. Furthermore, using the penetration time method, the measurement time can sometimes be reduced to within 1-2 minutes, making it possible to shorten the measurement time compared to other methods for determining affinity. The specific procedure of this method is described below.

[0047] (Crush) When molding coal, it is preferable to crush the coal. Although crushing is optional, crushing makes the coal particles finer, resulting in a more uniform distribution of gaps when the tablets are molded. This allows for more accurate measurement of the penetration time.

[0048] (molding) Next, the coal is molded to produce tablets.

[0049] The particle size of the coal used for molding is not particularly limited. However, from the viewpoint of eliminating the dependence of penetration time on coal particle size, the particle size of the coal is preferably 150 μm or less, and more preferably 50 μm or less. A coal particle size of X μm or less means that all coal particles pass through a sieve with a mesh size of X μm, and a coal particle size greater than Y μm means that all coal particles remain on the sieve with a mesh size of Y μm.

[0050] Any molding method can be used, but a preferred molding method involves filling a mold with coal and molding it under pressure to produce tablets. The tablet shape can be cylindrical or rectangular, for example. Here, the tablet shape is preferably one with a flat surface for dropping. Furthermore, a cylindrical shape is more preferable from the viewpoint of allowing for more uniform pressure application during molding.

[0051] There are no particular restrictions on the molding conditions, but it is preferable that the molding pressure be 100 MPa or higher in order to make the density distribution more uniform and improve the accuracy of the measurement. For the same reason, it is preferable that the height of the tablet be 5 mm or more and 15 mm or less. Also for the same reason, it is preferable that the tablet be cylindrical and the diameter of the molded body be 10 mm or more and 20 mm or less. Furthermore, it is preferable that the mass of the tablet be 0.5 g or more and 2.0 g or less.

[0052] (Solvent osmosis) Next, the molded tablets are permeated with the solvent and the permeation time is measured. The method for permeating the tablets with the solvent is not particularly limited, but it can be done by dropping the solvent onto the tablets. By increasing the amount of solvent dropped, the time required for permeation to be completed is extended, and the affinity between coal and the solvent can be accurately determined, so it is preferable to drop 2 μL or more of solvent. On the other hand, in order to prevent variations in permeation time due to the effects of wetting and spreading, it is preferable to drop 10 μL or less of solvent.

[0053] The method for measuring penetration time is not particularly limited, but the time it takes for the solvent to disappear from the surface of the tablet can be observed with the naked eye.

[0054] (Affinity determination) Finally, the affinity between the coal and the solvent is determined based on the measured penetration time. The method for expressing the result of the affinity determination between coal and the solvent is not limited. That is, the affinity may be determined in multiple stages (for example, two stages: good or bad), or it may be determined by determining a parameter that represents the affinity. To perform a more accurate evaluation, it is preferable to determine the affinity by determining a parameter that represents the affinity. As the parameter that represents the affinity, a value that can be directly obtained from the measured penetration time may be used, but it is more preferable to correct it using the evaporation time of the solvent, and more specifically, it is more preferable to use the value obtained by dividing the evaporation time of the solvent by the penetration time. This makes it possible to remove the effect of solvent evaporation from the measured penetration time. Specifically, the evaporation time of the solvent can be determined by dropping an amount of solvent equivalent to the amount dropped onto the coal-molded tablet onto a material where penetration does not occur, such as a Teflon plate, and measuring the time required for evaporation. The larger the value obtained by dividing the evaporation time of the solvent by the penetration time, the higher the affinity between the coal and the solvent is judged to be.

[0055] [Procedure (B): Procedure for deriving the HSP of coal] In this procedure, the HSP of coal is derived based on the affinity between coal and a reference substance determined in procedure (A), and the HSP of the reference substance. Generally, HSP can be calculated from the molecular structure. However, since the molecular structure of coal is amorphous, it is impossible to directly determine the HSP. Therefore, the HSP of coal can be indirectly derived by using the HSP of the reference substance.

[0056] The method for obtaining the HSP of a reference substance is not particularly limited. Preferred methods include calculating it from its molecular structure and obtaining it by referring to a database. However, the HSPs of reference substances listed in databases are often corrected in various ways to reflect the actual system, and even for a specific reference substance, the HSP may differ depending on the source of the reference. Therefore, using two or more databases simultaneously can cause errors in the derived HSP of coal. For this reason, when obtaining the HSP of a reference substance by referring to a database, it is preferable to obtain the HSP of all reference substances using the same database.

[0057] Generally, the distance between the HSP of coal and the HSP of a reference material with good affinity is short, and the distance between the HSP of a reference material with poor affinity is long. The method for deriving the HSP of coal is not particularly limited, but for example, a method in which the center of gravity of the HSP of the reference material is used as the HSP of coal can be suitably employed. The fusion sphere method can also be suitably employed.

[0058] First, we will explain the method of using the centroid of the reference substance's HSP as the HSP of coal. This method allows for precise reflection of the affinity measurement results between coal and the solvent into the coal's HSP, thus enabling accurate determination of the coal's HSP. Here, the weighted average of each term in the reference substance's HSP is calculated using parameters representing the affinity between coal and the reference substance as weights, and this average is then used as the coal's HSP. The centroid of the reference substance's HSP can be calculated from the following equations (5) to (8).

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[0059] Next, we will explain the fusion sphere method. By using the fusion sphere method, it becomes possible to indirectly derive the HSP of coal through geometrical analysis.

[0060] When using the fusion sphere method, the affinity determination in step (A) is made in two stages: good affinity or bad affinity. Then, in this step (B), first, an inscribed sphere is drawn in three-dimensional space that includes the points corresponding to the HSP of the reference material determined to have good affinity, but does not include the points corresponding to the HSP of the reference material determined to have poor affinity. The coordinates of the center of this inscribed sphere are then set as the HSP of the coal.

[0061] The method for constructing an inscribed sphere and the method for deriving the coordinates of its center are not particularly limited. Preferred methods include methods using manual calculations and methods using software.

[0062] The procedure for obtaining the HSP of coal has been explained above, but there is no limit to the timing of obtaining the HSP of coal when calculating δtot. In other words, it is not necessary to derive the HSP of coal every time; if the HSP of one or more of the coals that make up the blend has been obtained in advance, it can be used to calculate δtot.

[0063] (Heat treatment) In a preferred embodiment of the present invention, the coal may be heat-treated prior to the procedure for obtaining HSP from the coal. In other words, each of the two or more types of coal used to obtain HSP may be coal that has been heat-treated before obtaining HSP (semi-coke).

[0064] Heat treatment can be performed as needed. However, the process in which the molecular structure changes most significantly when coal becomes coke is the softening and melting process. By heat treating the coal, it can be brought closer to a softened and melted state, thereby improving the accuracy of predicting coke strength. For this reason, it is preferable that the coal be heat treated before obtaining HSP (High Stress Protection).

[0065] From the viewpoint of bringing the coal closer to a softened and molten state, the heat treatment is preferably carried out in an oxygen-free atmosphere. Also, for the same reason, the temperature of the heat treatment is preferably 350 to 500°C. Coal that has undergone the above heat treatment in an oxygen-free atmosphere and at a temperature of 350 to 500°C is called semi-coke. Furthermore, it is more preferable that the two or more types of coal have been converted to semi-coke before obtaining HSP.

[0066] The steps after the heat treatment can be the same as the procedure for obtaining the HSP of coal described above. In procedure (A) above, coal obtained by heat treatment can be used instead of coal. In procedure (B) above, the HSP can be derived based on the affinity and the HSP of the reference substance, and this can be adopted as the HSP of the coal before heat treatment or the HSP of the corresponding coal brand. [Examples]

[0067] The application methods of the present invention will be described below based on an example of the following embodiment. However, the present invention is not limited to this embodiment.

[0068] The coals used were coals A through W, as listed in Table 1. The common logarithms of Ro and MF (hereinafter sometimes referred to as LogMF) for each coal were measured, and the values ​​listed in Table 1 were obtained. Ro was determined according to the method compliant with JIS M 8816. LogMF was determined according to the method compliant with JIS M 8801. In addition, the temperature at which the fluidity of each coal was maximized when measuring MF (hereinafter sometimes referred to as MFT) was also determined. For all coals, the MFT was between 350°C and 500°C.

[0069] [Table 1]

[0070] (Example 1) In Example 1, the affinity between coal and solvent was determined using the infiltration time method, and the HSP of each coal was determined based on the determination results and the HSP of each solvent.

[0071] First, coals A through O listed in Table 1 were air-dried, crushed, and then classified into particles smaller than 200 μm. The moisture content was then adjusted to 9 wt%, and the coal was loaded into a carbonization furnace at a density of 0.73 g / cc. After loading, the furnace was heated at 3°C / min until the medium-fast furnace (MFT) was reached. Heating was then stopped, and the furnace was cooled to obtain semi-coke. The obtained semi-coke was crushed and classified into particles smaller than 212 μm. The classified semi-coke was molded into cylindrical pellets with a diameter of 32 mm. The molding method was compaction molding at 50 tons for 3 minutes. 2 μL of each solvent listed in Table 2 was added dropwise to the resulting pellets, and the penetration time for each solvent was measured. The HSP values ​​for each solvent listed in Table 2 were based on the description in HSPiP 5th Edition 5.4.08. Similarly, the solvents were dropped onto a Teflon plate, and the evaporation time was measured.

[0072] [Table 2]

[0073] The parameter m, which represents the affinity between coal l and solvent k, is obtained by dividing the evaporation time of each solvent by the infiltration time.kl This was calculated as follows. Next, the centroid of the HSP of each solvent was determined according to the above equations (5) to (8), and this was used as the HSP of each coal. The obtained HSPs of each coal are shown in Table 1.

[0074] Next, the blending patterns I to X in Table 3 were determined. Table 3 shows the weighted average value of Ro for each coal used in the blend (Ro of the blended coal).

[0075] Of the coals listed in Table 1, coals A through O were air-dried, crushed, and then classified to a size of 200 μm or less. The coals were then blended according to the blending pattern described above. The blending ratio was based on the weight of the air-dried coal. The coal was then adjusted to a moisture content of 9 wt% and charged into the carbonization furnace at a density of 0.73 g / cc. After charging, the furnace was heated at 3°C / min, and carbonization was performed by holding the furnace at 900°C for 20 minutes. The furnace was then cooled to produce coke. The carbonization was carried out under a nitrogen atmosphere.

[0076] [Table 3]

[0077] The obtained coke was crushed to approximately 3 mm, and its crushing strength was measured using a Kiya-type hardness tester. Since hardness measurements exhibit considerable variability, a large number of measurements are necessary. Therefore, preliminary measurements were performed with 50 samples and 100 samples, and no difference in hardness distribution was observed. Consequently, the hardness of 50 samples per blend pattern was measured, and the average value of the obtained hardness was calculated to determine the strength of the coke produced from each blend.

[0078] Next, the constants α, β, and γ in equation (1) above were determined. In determining them, the constraint was imposed that the constants α, β, and γ must all be integers, and regression analysis was performed by varying α, β, and γ so that the conditions α / β is between 1 and 10 and α / γ is between 1 and 10 were satisfied. The coefficient of determination R 2 We sought combinations of α, β, and γ that yielded fitting results greater than 0.5. 2Combinations where the value exceeds 0.5 include (α,β,γ)=(4,1,1), (10,7,3), and (10,3,2). Of these, those that satisfy the condition β=γ=1 were selected, and (α,β,γ)=(4,1,1) was found to be the combination that satisfies this condition, so the constant combination was determined to be (α,β,γ)=(4,1,1). For each coal blend, the centroid of the HSP was calculated using the weight ratio of coal according to equations (2) to (4) above, and δtot for each coal blend was calculated according to equation (1) above. The values ​​of δtot are shown in Table 3.

[0079] Figure 1 shows the relationship between crushing strength and δtot. Crushing strength and δtot showed a good correlation. For comparison, Figure 2 shows the relationship between crushing strength and Ro. A similar correlation was confirmed between crushing strength and Ro. However, some blended coals deviated significantly from the regression line showing the relationship between crushing strength and Ro. For example, in the case of blended coal with blending pattern X (shown as a black square in the figure), the error in the crushing strength predicted using the regression equation in Figure 2 was 48.9%. In contrast, the error in the crushing strength predicted using the regression equation in Figure 1 was small at 5.0%, and there were no other blended coals that deviated significantly from the regression line in Figure 1. Thus, the coke strength prediction method of the present invention can reduce cases where the predicted value deviates significantly, thereby improving prediction accuracy.

[0080] (Example 2) In Example 2, the HSP of each coal was determined using the molten sphere method.

[0081] First, coal samples P through W from Table 1 were air-dried, crushed, and then classified into particles smaller than 212 μm. They were then carbonized at 500°C to produce semi-coke (heat treatment). The resulting semi-coke was crushed and classified again into particles smaller than 212 μm. Next, 0.5 g of each classified semi-coke was taken. Then, coal samples P through W were added to test containers containing 10 ml of each solvent listed in Table 2, and the coal was dispersed. After 30 minutes, the dispersion of the coal was visually evaluated in two stages. Score 1: Coal is dispersed throughout the solvent. Score 0: More than 10% of the solvent is transparent from the top. The above evaluations were performed for each type of coal using all the solvents listed in Table 2.

[0082] Next, for each coal, the dispersion state score for each solvent and the solvent's HSP were input as a dataset into the HSPiP software (5th Edition 5.4.08) to calculate the coal's HSP (δH, δP, δD). Specifically, an inscribed sphere was constructed in 3D space that included points corresponding to the HSP of solvents judged to have good affinity (score 1) and excluded points corresponding to the HSP of solvents judged to have poor affinity (score 0). The coordinates of the center of this inscribed sphere were taken as the coal's HSP. The obtained HSPs for each coal are shown in Table 1.

[0083] Next, the blending patterns I to III in Table 4 were determined. In these blending patterns, the weighted average value of Ro from each coal used in the blend (Ro of the blended coal) was kept approximately constant. The Ro of the blended coal is shown in Table 4.

[0084] [Table 4]

[0085] (Drum test) Coals P through W listed in Table 1 were crushed to a size of 3 mm or less, and the coals were blended according to the blending patterns listed in Table 4. The resulting blended coal was carbonized at 1,000°C to produce coke. A drum test was performed on the obtained coke according to JIS K2151 to obtain the drum index.

[0086] Next, the constants α, β, and γ in equation (1) above were determined. Similar to Example 1, regression analysis was performed by varying α, β, and γ while imposing the constraint that the constants α, β, and γ must all be integers, and satisfying the conditions that α / β is between 1 and 10 and α / γ is between 1 and 10. The coefficient of determination R 2We sought combinations of α, β, and γ that yielded fitting results exceeding 0.5. From the obtained combinations, we determined α, β, and γ to be (α,β,γ)=(10,7,3). Following equations (1) to (4) above, we calculated the δtot of coal for each blending pattern. The δtot values ​​are shown in Table 4.

[0087] Figure 3 shows the relationship between the Drum exponent and δtot. The coefficient of determination R 2 The value was 0.685, indicating a good correlation. Furthermore, since Ro was almost constant in each blending pattern, if strength could be predicted using Ro, the drum index should also be constant. However, the drum index showed different values ​​for each blending pattern. Thus, even when the accuracy of predicting coke strength is poor when using commonly used coal properties such as Ro, the accuracy of prediction can be improved by considering the compatibility between coals evaluated by the method of the present invention.

Claims

1. A method for predicting coke strength, which predicts the strength of coke produced from blended coal containing two or more types of coal, based on δtot defined by the following equation (1), The above prediction is a method for predicting coke strength, wherein the prediction is performed using a prediction formula in which the explanatory variable is the δtot and the dependent variable is the coke strength. δtot=(α×δD ｇ ２ +β×δP ｇ ２ +γ×δH ｇ ２ ) １／２ ・・・・・・(1) Here, in equation (1), δD ｇ : Centroid of the dispersion force term of the Hansen solubility parameter of the two or more coals mentioned above. δP ｇ : The centroid of the polar term of the Hansen solubility parameter of the above two or more coals δH ｇ : Centroid of the hydrogen bonding term in the Hansen solubility parameters of the two or more coals mentioned above α, β, γ: Constants satisfying that α / β is between 1 and 10 and α / γ is between 1 and 10. That is the case.

2. Based on the δtot described in claim 1, the blend of two or more coals is determined. A method for producing coke, comprising producing coke from a blended coal mixture containing two or more coals based on the determined blend.

3. Based on the coke strength predicted using the coke strength prediction method described in claim 1, the blend of two or more coals is determined. A method for producing coke, comprising producing coke from a blended coal mixture containing two or more coals based on the determined blend.

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