JP6282958B2 - Evaluation method, evaluation apparatus, and program - Google Patents

Description

  The present invention relates to an evaluation method, an evaluation apparatus, and a program.

  A stirring vessel may be used to stir a plurality of particles. In this case, the stirring state of the particles inside the stirring container may be evaluated. Patent Document 1 describes that the agitation state of particles is simulated based on the discrete element method (DEM: Discrete Element Method). In Patent Literature 1, the degree of mixing of particles at an arbitrary position is calculated based on the result of simulation. This degree of mixing is determined by the ratio of the number of sampled particles to the number of specific types of particles in the sampled particles. Non-Patent Document 1 also describes that the stirring state of particles is simulated based on DEM.

JP 2000-214134 A

Brenda Remy, Johannes G. Khinast, Benjamin J. Glasser, Chem. Eng. Sci., 66 (2011) 1811-1824.

  The present inventors examined an index for judging the mixing state of particles stirred in a stirring vessel.

According to the present invention,
Computer
Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
The data set, wherein each particle, and the moving amount corresponding to the particles, a step of causing display on the display unit in the associated format,
An evaluation method for performing is provided.
According to the present invention,
Computer
Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
Displaying the data set on a display unit in a format in which the movement amount of each particle and the frequency corresponding to the movement amount are associated with each other;
An evaluation method for performing is provided.
According to the present invention,
Computer
Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
Displaying the data set on a display in a statistically processed format;
Run
The amount of movement of each particle is the distance that the particle has moved in a projected locus obtained by orthogonally projecting the locus of the particle from the first time to the second time on a predetermined plane or a predetermined straight line. A method is provided.

According to the present invention,
A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display unit for displaying the data set in a format in which each particle and the movement amount corresponding to the particle are associated with each other;
An evaluation device is provided.
According to the present invention,
A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display unit for displaying the data set in a format in which the amount of movement of each particle and the frequency corresponding to the amount of movement are associated with each other;
An evaluation device is provided.
According to the present invention,
A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display for displaying the data set in a statistically processed format;
Including
The amount of movement of each particle is the distance that the particle has moved in a projected locus obtained by orthogonally projecting the locus of the particle from the first time to the second time on a predetermined plane or a predetermined straight line. An apparatus is provided.

According to the present invention,
A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a format in which each particle and the movement amount corresponding to the particle are associated with each other;
A program for providing
According to the present invention,
A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a format in which the movement amount of each particle and the frequency corresponding to the movement amount are associated with each other;
A program for providing
According to the present invention,
A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a statistically processed format;
Hold
The moving amount of each particle is a distance that the particle has moved in a projected locus obtained by orthogonally projecting a locus traced from the first time to the second time on a predetermined plane or a straight line. Is provided.

  According to the present invention, an index for determining the mixing state of particles in a stirring vessel is provided.

It is a flowchart which shows the evaluation method which concerns on 1st Embodiment. It is a block diagram which shows the structure of the evaluation apparatus used for the evaluation method of FIG. It is a conceptual diagram of the contact force model of two particles. It is a figure which shows the 1st example of the data set displayed by step S40 which concerns on 1st Embodiment. It is a figure which shows the 2nd example of the data set displayed by step S40 which concerns on 1st Embodiment. It is a figure which shows the 3rd example of the data set displayed by step S40 which concerns on 1st Embodiment. It is a figure showing the 4th example of a data set displayed at Step S40 concerning a 1st embodiment. It is a figure for demonstrating a projection locus | trajectory. (A) is a top view which shows an example of a stirring container, (b) is sectional drawing in AA 'of (a). It is a block diagram which shows the structure of the evaluation apparatus which concerns on 3rd Embodiment. It is a block diagram which shows the structure of the evaluation part shown in FIG. It is a figure for demonstrating an example of the evaluation method of the similarity of the distribution of particle | grain movement amount, and the dispersion degree of distribution of particle | grain movement amount.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same reference numerals are given to the same components, and the description will be omitted as appropriate.

  In the following description, each component of each device is not a hardware unit configuration but a functional unit block. Each component of each device includes a CPU, memory, a program that realizes the components shown in the figure loaded in the memory, a storage medium such as a hard disk for storing the program, and a network connection interface. It is realized by any combination of software and software. There are various modifications of the implementation method and apparatus.

(First embodiment)
FIG. 1 is a flowchart showing an evaluation method according to the first embodiment. This evaluation method includes the following steps. First, a state in which a plurality of types of particles are stirred inside the stirring vessel is simulated (step S10). Next, the amount of movement of each simulated particle from the first time to the second time is calculated (step S20). Next, a predetermined data set is generated (step S30). The data set includes each particle and the movement amount corresponding to the particle in association with each other. Next, the data set is displayed in a statistically processed format (step S40).

The data set displayed in the statistically processed format in step S40 can be handled as mixed state information. That is, the mixed state information refers to information indicating a mixed state of a plurality of types of particles, for example, the following information.
(I) Information indicating how uniformly a plurality of types of particles are mixed (uniformity of mixing of a plurality of types of particles) (ii) After mixing, a plurality of particles are unevenly distributed in the system In the case, information indicating how each particle is distributed (distribution state of each particle) (iii) how a plurality of types of particles are distributed for each type (for each type of particles) Information)

  In the present embodiment, the mixed state of a plurality of types of particles can be evaluated based on the above mixed state information. Thus, in this embodiment, an index for determining the mixing state of particles in the stirring vessel is provided.

  Next, the evaluation apparatus 100 of this embodiment is demonstrated using FIG. The evaluation apparatus 100 executes the evaluation method shown in FIG. FIG. 2 is a block diagram showing the configuration of the evaluation apparatus 100. The evaluation apparatus 100 includes an input unit 102, a simulation unit 104, a movement amount calculation unit 106, a data set generation unit 108, a display unit 110, and a storage unit 112. The input unit 102 sends a signal indicating an instruction of the user of the evaluation apparatus 100 to the simulation unit 104, the movement amount calculation unit 106, the data set generation unit 108, and the display unit 110. The simulation unit 104 simulates the stirring state of the particles (Step S10). The movement amount calculation unit 106 calculates the movement amount (step S20). The data set generation unit 108 generates a data set (step S30). The display unit 110 displays the data set in a statistically processed format (step S40). The storage unit 112 stores information from the simulation unit 104, the movement amount calculation unit 106, the data set generation unit 108, and the display unit 110. Details of the evaluation apparatus 100 are as follows.

  The simulation unit 104 will be described. The simulation unit 104 simulates a state in which a plurality of types of particles are stirred inside the stirring vessel. In the present embodiment, the simulation unit 104 simulates a state in which a plurality of types of particles are agitated inside the agitation vessel based on a discrete element method (DEM: Discrete Element Method). In another example, the simulation unit 104 may simulate a state in which a plurality of types of particles are agitated inside the agitation vessel using a method different from the DEM (for example, an embedded boundary method).

  The simulation unit 104 models a stirring container and particles in the DEM. The structure and shape of the stirring vessel to be modeled is not limited to a specific structure and shape. The shape of the modeled particle is not limited to a specific shape. In addition, the particle modeled in this embodiment is a solid particle.

The modeled particles will be described with reference to FIG. FIG. 3 is a conceptual diagram of a contact force model of two particles i and j. FIG. 3A shows a contact force model in the normal direction of the contact point between the particle i and the particle j. FIG. 3B shows a contact force model in the tangential direction of the contact point between the particle i and the particle j. In the present embodiment, the particles have a spherical shape. In DEM, the force acting in the normal direction of the contact points between the particles i and particle j in contact with each other, as shown in FIG. 3 (a), the dashpot spring and damping coefficient eta _n of the spring constant k _n Modeled. On the other hand, as shown in FIG. 3B, the force acting in the tangential direction of the contact point between the particle i and the particle j that are in contact with each other includes a spring having a spring constant k _t , a dashpot having a damping coefficient η _t , and a dynamic friction coefficient. It is modeled by friction slider mu _f. The user may input appropriate values as the spring constants k _n and k _t , the damping coefficients η _n and η _t and the dynamic friction coefficient μ _f to the simulation unit 104 through the input unit 102. In this case, the simulation unit 104 models particles based on the input parameters.

ただし、ｍ_ｉ、Ｉ_ｉ、ｖ_ｉ、ω_ｉ、Ｒ_ｉは、それぞれ、粒子ｉの質量、慣性モーメント、速度、角速度、半径である。Ｆ_ｉｊ ^ＮおよびＦ_ｉｊ ^Ｔは、それぞれ、粒子ｉと粒子ｊとの接触によって生じる、法線方向および接線方向の力である。ｇは、重力加速度である。τ_ｒｉｊは、粒子ｉと粒子ｊとの接触によって生じるトルクである。式（１）では、シミュレーション部１０４は、重力加速度を考慮して並進運動の方程式を立てている。重力加速度が考慮されない場合、ｍ_ｉｇの項が式（１）の右辺から除去されてもよい。式（１）および（２）と同様の式が、粒子ｉ以外の各粒子にも立てられる。本実施形態では、シミュレーション部１０４がこれらの運動方程式を解く。シミュレーション部１０４は、差分法を用いた数値解析により運動方程式を解いてもよい。このようにしてシミュレーション部１０４は、粒子の攪拌状態をシミュレートする（ステップＳ１０）。 In DEM, equations of translational motion and rotational motion of each particle are established based on the models shown in FIGS. 3 (a) and 3 (b). The equations for translational motion and rotational motion in the particle i are as shown in the following formulas (1) and (2), respectively. The simulation unit 104 establishes the equations of motion shown in the equations (1) and (2) based on the models shown in FIGS. 3 (a) and 3 (b).

However, m _i , I _i , v _i , ω _i , and R _i are the mass, moment of inertia, velocity, angular velocity, and radius of the particle i, respectively. F _ij ^N and F _ij ^T are normal and tangential forces generated by the contact between the particle i and the particle j, respectively. g is a gravitational acceleration. τ _rij is a torque generated by the contact between the particle i and the particle j. In Expression (1), the simulation unit 104 sets up an equation for translational motion in consideration of gravitational acceleration. If the gravitational acceleration is not taken into account, term of m i _g may be removed from the right hand side of equation (1). Expressions similar to Expressions (1) and (2) are established for each particle other than the particle i. In the present embodiment, the simulation unit 104 solves these equations of motion. The simulation unit 104 may solve the equation of motion by numerical analysis using a difference method. Thus, the simulation part 104 simulates the stirring state of particle | grains (step S10).

  The simulation unit 104 outputs the simulation result to the storage unit 112. The storage unit 112 stores simulation results. The result of the simulation shows information on the coordinates of each particle at a predetermined time. After the simulation is finished, the simulation unit 104 sends a simulation end signal indicating that the simulation is finished to the movement amount calculation unit 106.

  Next, the movement amount calculation unit 106 will be described. The movement amount calculation unit 106 receives a simulation end signal from the simulation unit 104. Next, the movement amount calculation unit 106 accesses the storage unit 112. Then, the movement amount calculation unit 106 reads the simulation result stored in the storage unit 112. Next, the movement amount calculation unit 106 calculates the movement amount of each simulated particle from the first time to the second time (step S20). In the present embodiment, the movement amount of each particle is the distance that the particle has moved inside the stirring vessel from the first time to the second time. The first time and the second time are arbitrary times. The first time may be, for example, the time when stirring starts. For example, the second time may be a time at which stirring is completed.

  In the present embodiment, the movement amount calculation unit 106 calculates the distance that each particle has moved within the stirring vessel from the first time to the second time. In this case, the movement amount calculation unit 106 may calculate the distance based on the solution of Expression (1). Equation (1) gives the coordinates of each particle at a given time. The movement amount calculation unit 106 can calculate the distance that each particle has moved within the stirring vessel from the first time to the second time by tracing the coordinates of each particle at a predetermined time.

  The movement amount calculation unit 106 outputs the movement distance of each particle to the storage unit 112. The storage unit 112 stores the movement distance of each particle. After completing the calculation of the movement amount, the movement amount calculation unit 106 sends a movement amount calculation end signal indicating that the calculation of the movement amount has ended to the data set generation unit 108.

  Next, the data set generation unit 108 will be described. The data set generation unit 108 receives a movement amount calculation end signal from the movement amount calculation unit 106. Next, the data set generation unit 108 accesses the storage unit 112. Then, the data set generation unit 108 reads the movement amount of each particle stored in the storage unit 112. Next, the data set generation unit 108 generates a data set (step S30). The data set includes each particle and the movement amount corresponding to the particle in association with each other.

  The data set generation unit 108 outputs the data set to the storage unit 112. The storage unit 112 stores a data set. After the generation of the data set is completed, the data set generation unit 108 sends a data set end signal indicating that the generation of the data set has ended to the display unit 110.

  Next, the display unit 110 will be described. The display unit 110 receives a data set generation end signal from the data set generation unit 108. Next, the display unit 110 accesses the storage unit 112. The display unit 110 reads the data set stored in the storage unit 112. Next, the display unit 110 statistically processes the data set. Next, the display unit 110 displays the data set in a statistically processed format to the user of the evaluation device 100 (step S40). In the present embodiment, the display unit 110 displays the data set on the display. A data set displayed in a statistically processed format can be handled as the above-described mixed state information.

  Next, details of step S40 will be described with reference to FIGS.

FIG. 4 is a diagram illustrating a first example of the data set displayed in step S40. In step S40, as shown in FIG. 4, the data set is statistically processed and displayed in a table format. In the table of FIG. 4, each particle is associated with the amount of movement corresponding to the particle. Further, in FIG. 4, cells (for example, “particle A2” and “D _A2 ” cells in FIG. 4) indicating each particle and the movement amount corresponding to the particle are provided for each type of particle (particle group). It is classified. The display unit 110 displays the table shown in FIG. 4 to the user of the evaluation apparatus 100. The user of the evaluation apparatus 100 can grasp the movement distance of each particle from a bird's-eye view using the table of FIG. In this way, the user of the evaluation apparatus 100 evaluates the particle mixing state based on the table of FIG.

FIG. 5 is a diagram illustrating a second example of the data set displayed in step S40. In step S40, as shown in FIG. 5, the data set is statistically processed and displayed in a table format. In the table of FIG. 5, a frequency distribution table in which each particle is classified based on the movement amount is displayed. In the frequency distribution table of FIG. 5, for example, the frequency of particles that fall within the range of the moving distance from d1 [cm] to d2 [cm] is f _A1 [%] (first row of particle group A in FIG. 5). Means. In FIG. 5, a frequency distribution table is generated for each type (particle group) of particles. In another example, a frequency distribution table may be generated for each of a plurality of types of particle groups, or a frequency distribution table including all types of particles may be generated. The display unit 110 displays the table shown in FIG. 5 to the user of the evaluation apparatus 100. The user of the evaluation apparatus 100 can grasp the movement distance of each particle from a bird's-eye view using the table of FIG. In this way, the user of the evaluation apparatus 100 evaluates the particle mixing state based on the table of FIG.

  FIG. 6 is a diagram illustrating a third example of the data set displayed in step S40. In step S40, the data set is statistically processed and displayed in a graphical format, as shown in FIG. In the graph of FIG. 6, each particle is associated with a movement amount corresponding to the particle. Further, in FIG. 6, plots indicating each particle (for example, a white square plot indicating the particle A <b> 2 in FIG. 6) are classified for each particle type (particle group). The display unit 110 displays the graph shown in FIG. 6 to the user of the evaluation device 100. The user of the evaluation apparatus 100 can grasp the movement distance of each particle from a bird's-eye view with the graph of FIG. In this way, the user of the evaluation apparatus 100 evaluates the particle mixing state based on the graph of FIG.

  FIG. 7 is a diagram illustrating a fourth example of the data set displayed in step S40. In step S40, as shown in FIG. 7, the data set is statistically processed and displayed in a graphical format. In the graph of FIG. 7, a histogram in which each particle is classified based on the amount of movement is displayed. In FIG. 7, a histogram is generated for each type of particle (particle group). In another example, a histogram may be generated for each of a plurality of types of particle groups, or a histogram including all types of particles may be generated. The display unit 110 displays the graph shown in FIG. 7 to the user of the evaluation apparatus 100. The user of the evaluation apparatus 100 can grasp the moving distance of each particle from a bird's-eye view with the graph of FIG. In this way, the user of the evaluation apparatus 100 evaluates the particle mixing state based on the graph of FIG.

  In the present embodiment, the data set displayed in the statistically processed format as described above can be handled as mixed state information. Thus, in this embodiment, an index for determining the mixing state of particles in the stirring vessel is provided.

  As mentioned above, although embodiment of this invention was described, not only said embodiment but various deformation | transformation are possible. That is, in the present embodiment, mixing of particles in a fluid (for example, in a gas atmosphere and a liquid) can be handled. For example, in the present embodiment, the mixing of particles in a gas phase (for example, air) has been described as an example, but the mixing field is not limited to the gas phase, and may be a liquid phase. For example, it can be applied to mixing particles in a solvent. In this case, a simulation method may be employed in consideration of viscosity and the like as the physical properties of the liquid serving as the solvent.

(Second Embodiment)
In the first embodiment, the amount of movement of the particles is the amount of movement along the actual trajectory in the three-dimensional space. However, in this embodiment, the distance traveled by the particles in the projected locus is the amount of movement. Specifically, the movement amount is calculated based on a trajectory obtained by orthogonally projecting a trajectory that each particle traces from the first time to the second time on a predetermined plane or a predetermined straight line.

  The projection locus will be described with reference to FIG. FIG. 8 is a diagram for explaining the projected trajectory. In FIG. 8, the particles follow a predetermined locus from the first time to the second time in the xyz rectangular coordinate system. In the first example, the projected trajectory is a trajectory that is orthogonally projected on the xy plane. In the second example, the projected trajectory is a trajectory orthogonally projected on the z axis. In addition, the coordinate which shows the particle | grains of FIG. In this way, the particles move in the direction in which z increases after moving in the direction in which z decreases in the locus orthogonally projected on the z axis. When the movement amount of each particle is the distance traveled by the particle in the projected locus, the movement amount calculation unit 106 applies the coordinate system shown in FIG. 8 to the simulation result. Then, the movement amount calculation unit 106 calculates the distance that each particle has moved in the projected locus.

  The direction of the xyz coordinate system shown in FIG. 8 may be determined in relation to the stirring vessel. A specific example will be described with reference to FIG. FIG. 9A is a plan view showing an example of the stirring container (stirring container 200). FIG. 9B is a cross-sectional view taken along the line AA ′ of FIG.

  The stirring container 200 includes a blade 202. In the stirring vessel 200, the blade 202 rotates in a direction orthogonal to the gravitational acceleration g. The simulation unit 104 defines the x-axis direction, the y-axis direction, and the z-axis direction as shown in FIGS. 9A and 9B in modeling the stirring vessel 200. 9A and 9B, the z-axis direction is along the rotation axis direction of the blade 202. On the other hand, the x-axis and y-axis directions are along the rotation surface direction of the blade 202. The movement amount calculation unit 106 calculates the distance that each particle has moved in the projected locus in the coordinate system.

  The data set generation unit 108 and the display unit 110 of the present embodiment operate in the same manner as the data set generation unit 108 and the display unit 110 of the first embodiment. The data set generation unit 108 of the present embodiment generates a data set in the same manner as the data set generation unit 108 of the first embodiment. The data set includes each particle and the movement amount corresponding to the particle in association with each other. Similar to the display unit 110 of the first embodiment, the display unit 110 of the present embodiment displays the mixed state information obtained by statistically processing the data set to the user of the evaluation apparatus 100. However, the present embodiment is different from the first embodiment in that the amount of movement of each particle is the distance traveled by the particle in the projected locus.

  In the present embodiment, the xyz orthogonal coordinate system is adopted and the projection locus is obtained. However, the present invention is not limited thereto, and the polar locus system may be adopted to obtain the projection locus.

(Third embodiment)
FIG. 10 is a block diagram illustrating a configuration of the evaluation apparatus 100 according to the third embodiment, and corresponds to FIG. 2 of the first embodiment. The evaluation apparatus 100 according to the present embodiment has the same configuration as that of the evaluation apparatus 100 according to the first embodiment, except that an evaluation unit 114 is provided instead of the display unit 110. As will be described in detail later, the evaluation unit 114 is used to evaluate the mixed state of particles.

  FIG. 11 is a block diagram illustrating a configuration of the evaluation unit 114 illustrated in FIG. As shown in the figure, the evaluation unit 114 includes a similarity evaluation unit 116 and a distribution degree evaluation unit 118.

  The similarity evaluation unit 116 and the dispersion degree evaluation unit 118 receive the above-described data set from the data set generation unit 108 or the storage unit 112. In this case, the data set includes information indicating the distribution of movement amounts of one type of particles and information indicating the distribution of movement amounts of other types of particles (for example, FIG. 7).

  The similarity evaluation unit 116 evaluates the similarity between the movement amount distribution of one type of particles and the movement amount distribution of other types of particles. The distribution degree evaluation unit 118 evaluates the distribution degree of the distribution of the movement amount of one type of particles and the distribution degree of the distribution of the movement amount of other types of particles.

  The evaluation unit 114 evaluates the mixed state of one type of particles and other types of particles based on the above-described similarity. Furthermore, the evaluation unit 114 evaluates the above-described mixed state in consideration of the above-described spreading degree. Specifically, the evaluation unit 114 evaluates the above-described mixed state when each of the above-described spreading degree of one type of particles and the above-described spreading degree of other types of particles is equal to or less than a reference value.

  As a result of examination by the present inventors, it is clear that the uniformity of mixing of one type of particles and other types of particles is highly likely to have the following relationship with the above-mentioned similarity and the above-mentioned degree of dispersion. became.

  First, it is clear that the above-mentioned similarity and the above-mentioned uniformity have a strong correlation when both the above-mentioned degree of dispersion of one kind of particles and the above-mentioned degree of dispersion of other kinds of particles are low. It became. In other words, in this case, the higher the similarity is, the higher the uniformity is.

  As a result of the study by the present inventors, as a reason for the above-described correlation, it was mentioned that any one type of particles and any other type of particles may move substantially the same distance. When the above-mentioned degree of dispersion is low, all the particles are moving the same distance in one kind of particles. Similarly, in the other types of particles, all of the particles move approximately the same distance. Further, when the above-described similarity is high, the overlap between one type of the above-described distribution and another type of the above-described distribution is large. In other words, one type of particle and another type of particle are moving approximately the same distance. In such a case, the above-described uniformity is likely to be high.

  Second, when one or both of the above-described degree of dispersion of one kind of particles and the above-mentioned degree of dispersion of other kinds of particles are high, the correlation between the above-described similarity and the above-described uniformity is weakened. It became clear. In other words, in this case, the above-described uniformity is often not increased even when the above-described similarity is increased.

  As a result of the study by the present inventors, the reason for the above-described correlation was listed as the possibility that the variation in the moving distance of the particles affects the above-described uniformity. When the above-described similarity is high, the center of one type of the above-described distribution and the center of the other type of the above-described distribution are substantially at the same position. Even in this case, when the above-described degree of dispersion of one kind of particles is high, the one kind of particles contains particles having a certain amount of movement from the center described above. And it is highly possible that such particles have lowered the above-described uniformity.

  According to the above, when each of the above-mentioned distribution degree of one kind of particles and the above-mentioned degree of dispersion of other kinds of particles is equal to or less than a reference value, the above-described uniformity is accurately based on the above-described similarity degree. It can be said that it can be evaluated.

  FIG. 12 is a diagram for explaining an example of a method for evaluating the degree of similarity of the distribution of particle movement amounts and the degree of distribution of the distribution of particle movement amounts. This figure (a) has shown the distribution (probability density) of the movement distance of one kind of particle | grains (particle group A), and the distribution (probability density) of the movement distance of another kind of particle | grains (particle group B). . This figure (b) has shown the cumulative probability of the above-mentioned distribution of the particle group A, and the cumulative probability of the above-mentioned distribution of the particle group B. FIG. The cumulative probability of the particle group A is given by the integral of the probability density of the particle group A. Similarly, the cumulative probability of the particle group B is given by the integral of the probability density of the particle group B.

  As shown in FIG. 4B, the similarity between the above-described distribution of the particle group A and the above-described distribution of the particle group B compares the above-described cumulative probability of the particle group A with the above-described cumulative probability of the particle group B. This can be evaluated. Specifically, the difference between the cumulative probability of the particle group A and the cumulative probability of the particle group B is calculated for each moving distance. Then, the degree of similarity is evaluated based on the maximum absolute value of the difference (D value of Kolmogorov-Smirnov test). In this case, it can be said that the smaller the maximum value is, the higher the degree of similarity between the above distribution of the particle group A and the above distribution of the particle group B is. Thereby, the mixed state of the particle group A and the particle group B can be evaluated by determining whether or not the above-described maximum value is equal to or less than a predetermined reference value.

  However, the method for evaluating the similarity between the above-described distribution of the particle group A and the above-described distribution of the particle group B is not limited to the above-described example. For example, in the example shown in FIG. 5B, an average value of the difference between the cumulative probability of the particle group A and the cumulative probability of the particle group B may be calculated. In this case, the mixed state of the particle group A and the particle group B can be evaluated by determining whether or not the above average value is equal to or less than a predetermined reference value.

  As shown in FIG. 5B, the distribution degree of the distribution of the particle group A can be evaluated based on the slope of the cumulative probability of the particle group A described above. In this case, for example, the distribution degree can be evaluated based on the average value of the slopes of the cumulative probabilities in the range where the cumulative probability is greater than or equal to the first value and less than or equal to the second value. The first value and the second value are, for example, a value (for example, 25%) less than the median value (50%) and a value (for example, 75%) greater than the median value (50%), respectively. As another example, the distribution degree can be evaluated based on the slope of the cumulative probability at a position where the cumulative probability is the reference probability value. In this case, the reference probability value is, for example, the value of the cumulative probability at the position where the slope of the cumulative probability (the value of the first derivative of the cumulative probability) takes the maximum value, or an appropriate specific value (for example, 50%). It is. The distribution degree of the particle group B distribution can also be evaluated in the same manner as described above.

  However, the evaluation method of the distribution degree of the particle group A and the distribution degree of the particle group B described above is not limited to the above example. For example, as shown in FIG. 5A, the distribution degree may be evaluated based on the standard deviation of the distribution.

  As mentioned above, although embodiment of this invention was described with reference to drawings, these are the illustrations of this invention, Various structures other than the above are also employable.

Hereinafter, examples of the reference form will be added.
1. Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Evaluating the similarity between the movement amount distribution of the first type of the plurality of types of particles and the movement amount distribution of the second type of the plurality of types of particles;
Evaluating a mixed state of the first type particles and the second type particles based on the similarity;
Evaluation method including
2.1. In the evaluation method described in
In the step of evaluating the similarity,
An evaluation method for evaluating the similarity by comparing a cumulative probability of the distribution of the movement amount of the first type of particles with a cumulative probability of the distribution of the movement amount of the second type of particles.
3.1. Or 2. In the evaluation method described in
Further comprising the step of evaluating the distribution degree of the movement amount distribution of the first type particles and the distribution degree of the movement amount distribution of the second type particles,
The mixing state of the first-type particles and the second-type particles is evaluated when each of the first-type particles and the second-type particles is less than a reference value. Evaluation method.
4). A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A similarity evaluation unit that evaluates the similarity between the movement amount distribution of the first type of the plurality of types of particles and the movement amount distribution of the second type of the plurality of types of particles;
An evaluation unit that evaluates a mixed state of the first type particles and the second type particles based on the similarity;
Evaluation device including
5. A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of evaluating the similarity between the movement amount distribution of the first type of particles of the plurality of types and the movement amount distribution of the second type of particles of the plurality of types;
A function of evaluating a mixed state of the first type particles and the second type particles based on the similarity;
A program to give
Hereinafter, examples of the reference form will be additionally described.
1. Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
Displaying the data set in a statistically processed format;
Evaluation method including
2. 1. The evaluation method described in
In the step of displaying the data set in a statistically processed format, the evaluation method wherein the data set is statistically processed and displayed in a graphical format.
3. 2. The evaluation method described in
In the step of displaying the data set in a statistically processed format, an evaluation method in which a graph in which each particle is associated with the amount of movement corresponding to the particle is displayed.
4). 3. The evaluation method described in
In the graph, an evaluation method in which plots indicating the respective particles are classified for each type of the particles.
5. 2. The evaluation method described in
In the step of displaying the data set in a statistically processed format, an evaluation method in which a histogram in which each particle is classified based on the amount of movement is displayed.
6). 1. The evaluation method described in
In the step of displaying the data set in a statistically processed format, the evaluation method wherein the data set is statistically processed and displayed in a table format.
7). 6). The evaluation method described in
In the step of displaying the data set in a statistically processed format, an evaluation method in which a table in which each particle is associated with the amount of movement corresponding to the particle is displayed.
8). 7). The evaluation method described in
In the table, an evaluation method in which cells indicating the respective particles and the movement amount corresponding to the particles are classified for each type of the particles.
9. 6). The evaluation method described in
In the step of displaying the data set in a statistically processed format, an evaluation method in which a frequency distribution table in which the particles are classified based on the amount of movement is displayed.
10. 1. The evaluation method according to any one of 1 to 9,
The amount of movement of each particle is an evaluation method that is the distance that the particle has moved inside the stirring vessel from the first time to the second time.
11. 1. The evaluation method according to any one of 1 to 9,
The amount of movement of each particle is the distance that the particle has moved in a projected locus obtained by orthogonally projecting the locus of the particle from the first time to the second time on a predetermined plane or a predetermined straight line. Method.
12 A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display for displaying the data set in a statistically processed format;
Evaluation device including
13. A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a statistically processed format;
A program to give

DESCRIPTION OF SYMBOLS 100 Evaluation apparatus 102 Input part 104 Simulation part 106 Movement amount calculation part 108 Data set production | generation part 110 Mixed state information display part 112 Storage part 114 Evaluation part 116 Similarity evaluation part 118 Scatter degree evaluation part

Claims (18)

Computer
Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
The data set, wherein each particle, and the moving amount corresponding to the particles, a step of causing display on the display unit in the associated format,
Evaluation method to perform . The evaluation method according to claim 1,
Wherein in the data set table Shimesuru the process, evaluation process that the data set is displayed in a statistically processed by graphically. The evaluation method according to claim 2,
Wherein in the data set table Shimesuru said step, said each particle, the evaluation methods and the moving amount corresponding to the particles, the graph associated is displayed. The evaluation method according to claim 3, wherein
In the graph, an evaluation method in which plots indicating the respective particles are classified for each type of the particles. The evaluation method according to claim 2,
Wherein in the data set table Shimesuru the process, evaluation process wherein each particle histograms are classified on the basis of the movement amount is displayed. The evaluation method according to claim 1,
Wherein in the data set table Shimesuru the process, evaluation process that the data set is displayed in a statistically processed by table format. The evaluation method according to claim 6, wherein
Wherein in the data set table Shimesuru said step, said each particle, the evaluation methods and the moving amount corresponding to the particles, there is associated table is displayed. The evaluation method according to claim 7,
In the table, an evaluation method in which cells indicating the respective particles and the movement amount corresponding to the particles are classified for each type of the particles. Computer
Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
The data set, and the moving amount of each of the particles, the frequency corresponding to the movement amount, a step of causing display on the display unit in the associated format,
Evaluation method to perform . The evaluation method according to claim 9 , comprising:
Wherein in the data set table Shimesuru the process, the evaluation method of each particle frequency distribution table are classified on the basis of the movement amount is displayed. The evaluation method according to any one of claims 1 to 9, wherein
The amount of movement of each particle is an evaluation method that is the distance that the particle has moved inside the stirring vessel from the first time to the second time. Computer
Simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
Calculating the amount of movement of each simulated particle from a first time to a second time;
Generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
Displaying the data set on a display in a statistically processed format;
Run
The movement amount of each particle is an evaluation of the distance traveled by the particle in a projected locus in which the locus traced from the first time to the second time is orthogonally projected onto a predetermined plane or a predetermined straight line. Method. A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display unit for displaying the data set in a format in which each particle and the movement amount corresponding to the particle are associated with each other;
Evaluation device including A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display unit for displaying the data set in a format in which the amount of movement of each particle and the frequency corresponding to the amount of movement are associated with each other;
Evaluation device including A simulation unit that simulates a state in which a plurality of types of particles are stirred inside the stirring vessel;
A movement amount calculation unit that calculates a movement amount of each simulated particle from the first time to the second time;
A data set generation unit for generating a data set including each particle and the movement amount corresponding to the particle in association with each other;
A display for displaying the data set in a statistically processed format;
Only including,
The amount of movement of each particle is the distance that the particle has moved in a projected locus obtained by orthogonally projecting the locus of the particle from the first time to the second time on a predetermined plane or a predetermined straight line. apparatus. A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a format in which each particle and the movement amount corresponding to the particle are associated with each other;
A program to give A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a format in which the movement amount of each particle and the frequency corresponding to the movement amount are associated with each other;
A program to give A program for causing a computer to function as an evaluation device,
In the computer,
A function of simulating a state in which a plurality of types of particles are stirred inside the stirring vessel;
A function of calculating the amount of movement of each simulated particle from the first time to the second time;
A function of generating a data set including each particle and the amount of movement corresponding to the particle in association with each other;
A function of displaying the data set in a statistically processed format;
It was given,
The moving amount of each particle is a distance that the particle has moved in a projected locus obtained by orthogonally projecting a locus traced from the first time to the second time on a predetermined plane or a straight line. .

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