A method and apparatus for characterizing and evaluating the uniformity of fiber pulp dispersion

Abstract

This invention provides a method and apparatus for characterizing and evaluating the uniformity of fiber pulp dispersion. The method includes: obtaining the actual dimensions of a pulping device and constructing a three-dimensional geometric model based on the actual dimensions; determining the flow physics model, boundary conditions, and initial conditions of the fluid within the three-dimensional geometric model based on the actual operating conditions of the pulping device; then performing flow field simulation to obtain flow field parameters; constructing filling units based on the actual operating conditions and determining the target size of the particles used to simulate fibers; the number of particles of the target size included in the filling unit is used to characterize the fiber concentration; performing simulation calculations based on the flow field parameters and the particles in the filling unit to obtain a converged solution; and extracting and analyzing the converged solution to obtain the coefficient of variation used to characterize the uniformity of fiber dispersion under actual operating conditions. The fiber pulp dispersion uniformity characterization and evaluation method provided by this solution is applicable to engineering-scale applications and is more universal and reliable.

Description

Technical Field

[0001] This invention relates to the field of wet fiber production technology, and in particular to a method and apparatus for characterizing and evaluating the uniformity of fiber slurry dispersion. Background Technology

[0002] The dispersion performance of fibers during suspension flow directly affects the final properties of wet-processed products. Wet-process production typically uses hydraulic disintegration to break down raw materials into individual fibers. The evaluation of fiber dispersion uniformity usually employs laboratory-scale optical experiments or indirect evaluation by forming sheets from the slurry after hydraulic disintegration. However, optical experiments have limitations and are not suitable for practical production; while indirect evaluation using sheets involves additional steps and has a larger margin of error. Therefore, a universally applicable method for characterizing and evaluating the dispersion uniformity of fiber slurry, suitable for engineering-scale applications, is needed. Summary of the Invention

[0003] This invention provides a method and apparatus for characterizing and evaluating the uniformity of fiber slurry dispersion. This method has higher versatility and is suitable for engineering-scale applications. It has high evaluation accuracy and high reliability.

[0004] In a first aspect, embodiments of the present invention provide a method for characterizing and evaluating the uniformity of fiber pulp dispersion, comprising:

[0005] Obtain the actual dimensions of the pulping equipment and construct a three-dimensional geometric model based on the actual dimensions;

[0006] Based on the actual working conditions of the pulping equipment, determine the flow physical model, boundary conditions, and initial conditions of the fluid within the three-dimensional geometric model;

[0007] The flow field parameters are obtained by simulating and solving the flow field based on the flow physics model, the boundary conditions, and the initial conditions.

[0008] Based on the actual working conditions, a filling unit is constructed and the target size of the particles used to simulate fibers is determined; wherein, the number of particles of the target size included in the filling unit is used to characterize the fiber concentration;

[0009] Based on the flow field parameters and the particles in the filling unit, a convergent solution is obtained through simulation calculation.

[0010] The convergent solution is extracted and analyzed to obtain the coefficient of variation, which characterizes the degree of fiber dispersion uniformity under the actual working conditions.

[0011] Optionally, constructing a three-dimensional geometric model based on the actual dimensions includes:

[0012] Construct a three-dimensional geometric model proportionally to the actual dimensions;

[0013] Based on the pulping equipment, the flow region of the fluid is determined in the three-dimensional geometric model, and the three-dimensional geometric model is meshed.

[0014] Optionally, determining the flow physical model, boundary conditions, and initial conditions of the fluid within the three-dimensional geometric model based on the actual operating conditions of the pulping equipment includes:

[0015] The flow physics model adopts a moving mesh model, and the boundary conditions are determined according to the actual working conditions.

[0016] Determine the initial conditions in the actual working condition; wherein the initial conditions include fluid volume and flow field velocity.

[0017] Optionally, the step of simulating and solving the flow field based on the flow physics model, the boundary conditions, and the initial conditions to obtain the flow field parameters includes:

[0018] The flow field was simulated using the Euler method. By solving the continuity equation and the momentum equation, flow field parameters, including the flow field distribution and pressure distribution, were obtained.

[0019] Optionally, the step of constructing the filling unit and determining the target size of the particles used to simulate the fiber based on the actual working conditions includes:

[0020] Determine the actual size of the fiber based on the actual working conditions described;

[0021] Based on the flow field parameters, the initial motion trajectory of the fiber is determined;

[0022] The actual size of the fiber is enlarged according to a preset magnification ratio to obtain several magnified sizes;

[0023] Based on the flow field parameters, the motion trajectory of each of the magnified dimensions is determined;

[0024] Determine whether there exists a motion trajectory with the same magnified size as the initial motion trajectory;

[0025] If it exists, obtain the magnification ratio of the motion trajectory of the magnified size, and determine the maximum magnification ratio from the magnification ratio;

[0026] The actual size of the fiber is magnified using the maximum magnification ratio to obtain the target size.

[0027] Optionally, the filling unit is used to load the particles; wherein the fiber concentration in the filling unit is the same as the fiber concentration in the actual working conditions.

[0028] Optionally, the step of extracting and analyzing the converged solution to obtain the coefficient of variation used to characterize the fiber dispersion uniformity under the actual working conditions includes:

[0029] The converged solution is extracted and analyzed to obtain the positional distribution information of the particles;

[0030] The flow region of the fluid in the three-dimensional geometric model is divided into several region units;

[0031] Based on the location distribution information, the number of particles in each region unit is determined;

[0032] The coefficient of variation is calculated based on the number of particles in each of the said regional units.

[0033] Optionally, the area units are all the same size.

[0034] Optionally, the calculation of the coefficient of variation includes:

[0035] The average number of particles in the said region unit is calculated by taking the average value to obtain the average number of particles under the actual working conditions.

[0036] The standard deviation is calculated by performing a standard deviation calculation on the number of particles within the said region unit;

[0037] The ratio of the standard deviation to the average number of particles is used as the coefficient of variation.

[0038] Secondly, embodiments of the present invention also provide a device for characterizing and evaluating the uniformity of fiber pulp dispersion, comprising:

[0039] The preprocessing module is used to obtain the actual dimensions of the pulping equipment and construct a three-dimensional geometric model based on the actual dimensions;

[0040] The determination module is used to determine the flow physical model, boundary conditions, and initial conditions of the fluid within the three-dimensional geometric model based on the actual operating conditions of the pulping equipment.

[0041] The flow field simulation module is used to perform flow field simulation and solution based on the flow physical model, the boundary conditions and the initial conditions, and obtain the flow field parameters.

[0042] The particle simulation module is used to construct a filling unit and determine the target size of the particles used to simulate fibers based on the actual working conditions; wherein, the number of particles of the target size included in the filling unit is used to characterize the fiber concentration;

[0043] The coupling module is used to perform simulation calculations based on the flow field parameters and the particles in the filling unit to obtain a converged solution.

[0044] The analysis module is used to extract and analyze the converged solution to obtain the coefficient of variation, which characterizes the fiber dispersion uniformity under the actual working conditions.

[0045] Thirdly, embodiments of the present invention also provide a computing device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the fiber slurry dispersion uniformity characterization and evaluation method described in any of the above claims.

[0046] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to perform the fiber slurry dispersion uniformity characterization and evaluation method described in any of the above claims.

[0047] This invention provides a method and apparatus for characterizing and evaluating the uniformity of fiber pulp dispersion. The method constructs a three-dimensional geometric model based on the actual dimensions of the pulping equipment. Based on actual operating conditions, it determines the flow physics model, boundary conditions, and initial conditions within this three-dimensional geometric model to perform flow field simulation and determine flow field parameters. Then, based on actual operating conditions, it simulates the fibers using particles. Particles are loaded into the flow field according to the flow field parameters, coupling particle motion with flow field motion and performing simulation calculations until a convergent solution is obtained. The coefficient of variation is then obtained based on the convergent solution. Thus, this invention directly evaluates the uniformity of fiber dispersion after pulping simulation calculations using the above numerical simulation method. This method is not only scientifically reliable, highly operable, and saves experimental time, but also applicable to large-scale engineering applications, exhibiting greater universality. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart of a method for characterizing and evaluating the uniformity of fiber pulp dispersion according to an embodiment of the present invention;

[0050] Figure 2 This is a distribution diagram of the motion trajectories of particles of different sizes in particle size independence detection provided by an embodiment of the present invention;

[0051] Figure 3 This is a schematic diagram of the pulping equipment provided in this invention for the layering and separation of fiber pulp;

[0052] Figure 4These are line graphs showing the variation of CV values ​​under different fiber concentrations provided in an embodiment and a comparative example of the present invention.

[0053] Figure 5 This is a hardware architecture diagram of a computing device provided in an embodiment of the present invention;

[0054] Figure 6 This is a structural diagram of a fiber pulp dispersion uniformity characterization and evaluation device provided in an embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0056] like Figure 1 As shown in the figure, this invention provides a method for characterizing and evaluating the uniformity of fiber pulp dispersion. The method includes:

[0057] Step 100: Obtain the actual dimensions of the pulping equipment and construct a three-dimensional geometric model based on the actual dimensions;

[0058] Step 102: Based on the actual working conditions of the pulping equipment, determine the flow physical model, boundary conditions, and initial conditions of the fluid within the three-dimensional geometric model;

[0059] Step 104: Perform flow field simulation and solution based on the flow physics model, boundary conditions, and initial conditions to obtain flow field parameters;

[0060] Step 106: Based on actual working conditions, construct a filling unit and determine the target size of the particles used to simulate fibers; wherein, the number of particles of the target size included in the filling unit is used to characterize the fiber concentration.

[0061] Step 108: Perform simulation calculations based on the flow field parameters and the particles in the filling unit to obtain a converged solution;

[0062] Step 110: Extract and analyze the converged solution to obtain the coefficient of variation used to characterize the uniformity of fiber dispersion under actual working conditions.

[0063] In this embodiment of the invention, a three-dimensional geometric model is constructed based on the actual dimensions of the pulping equipment. The flow physics model, boundary conditions, and initial conditions within this three-dimensional geometric model are determined based on actual operating conditions to facilitate flow field simulation and determine flow field parameters. Then, based on actual operating conditions, particles are used to simulate the fibers. Particles are loaded into the flow field according to the flow field parameters, and the particle motion is coupled with the flow field motion and simulated until a convergent solution is obtained. The coefficient of variation is then obtained based on the convergent solution. Thus, this invention directly evaluates the uniformity of fiber dispersion after pulping simulation calculation using the above numerical simulation method. This method is not only scientifically reliable, highly operable, and saves experimental time, but is also applicable to large-scale engineering applications, exhibiting greater versatility.

[0064] It should be noted that choosing slender particles is more effective in describing fiber morphology.

[0065] The following description Figure 1 The execution method for each step is shown.

[0066] First, for step 100, construct a three-dimensional geometric model based on the actual dimensions, including:

[0067] Construct a three-dimensional geometric model proportionally to the actual dimensions;

[0068] Based on the pulping equipment, the flow region of the fluid is determined in the three-dimensional geometric model, and the three-dimensional geometric model is meshed.

[0069] It should be noted that the fluid flow region is the simulation computation domain; the mesh generation can be set and divided according to actual needs, which can improve mesh quality and make the fluid simulation more accurate and convergent.

[0070] In this invention, a three-dimensional geometric model is constructed proportionally based on the actual dimensions of the pulping equipment, which is beneficial for accurately simulating the actual flow process within the pulping equipment, thereby improving the accuracy and reliability of the subsequent evaluation of the uniformity of fiber dispersion.

[0071] For step 102, based on the actual operating conditions of the pulping equipment, determine the flow physical model, boundary conditions, and initial conditions of the fluid within the three-dimensional geometric model, including:

[0072] The flow physics model adopts a moving mesh model, and the boundary conditions are determined according to the actual working conditions;

[0073] Determine the initial conditions in the actual working conditions; the initial conditions include fluid volume and flow field velocity.

[0074] In this invention, a moving mesh model is used to describe the circulation of slurry inside the equipment driven by the rotor rotation during the hydraulic pulping process, and boundary conditions are set according to actual working conditions. Then, based on the amount of white water required for the actual pulping process, the fluid volume is loaded into the computational domain of the three-dimensional geometric model, while the flow velocity of the flow field is initialized to zero. It should be noted that, during the hydraulic pulping process, the fluid volume is the required amount of white water.

[0075] In step 104, the flow field is simulated and solved based on the flow physics model, boundary conditions, and initial conditions to obtain the flow field parameters, including:

[0076] The flow field was simulated using the Euler method. By solving the continuity equation and the momentum equation, flow field parameters, including the flow field distribution and pressure distribution, were obtained.

[0077] In this invention, step 104 involves solving the flow field by using the Euler method to simulate the gas-water interface. By solving the continuity equation and momentum equation, the flow field velocity and pressure field without solid fibers are obtained; the flow field distribution includes the flow field velocity.

[0078] In a preferred embodiment, the Euler method employs a fluid volume model (VOF).

[0079] In step 106, based on actual working conditions, the filling unit is constructed and the target size of the particles used to simulate the fiber is determined, including:

[0080] Determine the actual size of the fiber based on the actual working conditions;

[0081] Based on the flow field parameters, the initial motion trajectory of the fiber is determined;

[0082] The actual size of the fiber is enlarged according to a preset magnification ratio to obtain several magnified sizes;

[0083] Based on the flow field parameters, the motion trajectory of each magnified dimension is determined;

[0084] Determine whether a motion trajectory with the same magnified size as the initial motion trajectory exists;

[0085] If it exists, obtain the magnification ratio of the motion trajectory of that magnified size, and determine the maximum magnification ratio from the magnification ratio;

[0086] The actual size of the fiber is magnified using the maximum magnification ratio to obtain the target size.

[0087] It should be noted that the target size is larger than the actual size of the fiber.

[0088] Because glass microfibers have small diameters (0.1 μm to 5 μm), the number of fibers contained in fiber suspensions based on glass microfiber raw materials, even in laboratory-scale slurries, is astonishing. Simulating particle motion directly based on the actual fiber size would be extremely costly. To reduce computational costs while ensuring the reliability of simulation results, particle size independence calculations were used to determine target-size particles with the same motion trajectory as the actual fiber size. This transforms small-sized fibers into large-sized particles, reducing computational costs while ensuring simulation reliability through identical motion trajectories.

[0089] For example, such as Figure 2 The distribution of motion trajectories of particles of different sizes is shown, where the preset magnification ratios are 1x, 10x, and 10x. 2 times, 10 3 times, 10 4 times, 10 5 times, 10 6 times, by Figure 2 It can be seen that the trajectory of the particle magnified 10 times basically coincides with the initial trajectory (i.e., the particle magnified 1 time). Therefore, the size of the 10x magnified particle is taken as the target size. It should be noted that... Figure 2 In this invention, two motion trajectories with a 90% overlap rate are considered to be basically coincident; however, depending on the actual application requirements, the overlap rate can be greater than 90% (e.g., 91%, 92%, 95%, etc.).

[0090] In step 106, a filling unit is used to load the particles; wherein the fiber concentration in the filling unit is the same as the fiber concentration in the actual working conditions.

[0091] To further reduce the computational cost of the simulation process, the fiber quantity needs to be simplified. In this invention, a cell-filling method is used to ensure that the fiber concentration within the filled cell (i.e., the small cubic cell) is consistent with the actual fiber concentration under actual working conditions. When simulating working conditions with different concentrations, the number of fibers within the filled cell is changed accordingly.

[0092] Next, in step 108, simulation calculations are performed based on the flow field parameters and the particles in the filling unit, that is, the particle motion is coupled with the flow field motion until a convergent solution is obtained.

[0093] It should be noted that in this invention, the simulation calculation ends when the convergent solution is obtained, and the particle motion within the three-dimensional geometric model reaches stability. Therefore, the position distribution information and motion velocity of the fiber particles obtained based on this convergent solution are more accurate and reliable, which is beneficial to further improve the accuracy of the evaluation of the fiber dispersion uniformity.

[0094] For step 110, the converged solution is extracted analytically to obtain the coefficient of variation used to characterize the fiber dispersion uniformity under actual working conditions, including:

[0095] The convergent solution is analyzed to obtain the particle location distribution information;

[0096] The flow region of the fluid in the three-dimensional geometric model is divided into several regions of the same size;

[0097] Based on the location distribution information, determine the number of particles in each regional unit;

[0098] The coefficient of variation is calculated based on the number of particles in each regional unit.

[0099] While numerical simulations can reveal the positional distribution of fibers during suspension flow, characterizing fiber dispersion performance remains a challenge. When comparing the dispersion of two sets of data, if the measurement scales differ significantly or the data dimensions are different, directly using the standard deviation for comparison is inappropriate. In such cases, the influence of measurement scale and dimensions should be eliminated, and the coefficient of variation (CV) can achieve this, as it is the ratio of the standard deviation of the original data to the mean of the original data. Therefore, in this invention, the CV value can effectively characterize the dispersion of particle positions and accurately evaluate the fiber dispersion effect after decomposition.

[0100] In this invention, based on the obtained information on the positional distribution of particles used to characterize the fiber, the coefficient of variation (CV) in the three-dimensional geometric model is calculated by statistically analyzing the number of particles in each regional unit. The smaller the CV value, the better the fiber dispersion performance.

[0101] In a preferred embodiment, step 110 calculates the coefficient of variation, including:

[0102] The average number of particles in the region unit is calculated by taking the average value to obtain the average number of particles under actual working conditions.

[0103] The standard deviation of the number of particles within a region unit is calculated to obtain the standard deviation.

[0104] The ratio of the standard deviation to the average number of particles is used as the coefficient of variation.

[0105] Specifically, the coefficient of variation is obtained using the following formula:

[0106] CV = SD / M * 100%

[0107] Wherein, CV is used to characterize the coefficient of variation, SD is used to characterize the standard deviation, and M is used to characterize the average number of particles.

[0108] To further verify the reliability of the fiber pulp dispersion uniformity characterization and evaluation method of the present invention, CV values ​​were obtained for fiber pulps with different fiber concentrations of 0.3%, 0.55%, 0.8%, 1.05%, and 1.3% using the examples of the present application and the following comparative examples, and the reliability of the evaluation method of the present application was verified by comparing the CV values ​​at the same concentration.

[0109] Specifically, in the embodiments of this application, following the previous example, based on the VOF model and employing... Figure 2 The calculated CV values ​​for different fiber concentrations at a given target size are as follows: Figure 4 As shown. The comparative example, after the same dispersion time as the above embodiment, releases slurry in five layers through the discharge port at the bottom of the pulping equipment, with each layer sampled at a height as shown. Figure 3 As shown, the same volume of slurry collected from each layer was then sheeted, dried, and weighed. The average value from multiple experiments was taken as the sample weight of that layer. Then, based on the sample type obtained from each layer, the CV value of the five layers of samples was calculated (e.g., ...). Figure 4 (As shown). It should be noted that the pulping equipment used in the embodiments and comparative examples are the same, the actual working conditions are the same, the dispersion time is the same, and the fiber pulp at the same concentration is also the same.

[0110] Depend on Figure 4 It can be seen that the comparative method of indirectly evaluating the slurry by preparing it into a sheet form, and the method of evaluating it by conducting simulation calculations based on the experimental equipment structure and parameters in the embodiment, both yield results that are consistent with the general rule, indicating the reliability and accuracy of the characterization and evaluation method of this application.

[0111] like Figure 5 , Figure 6 As shown, this invention provides a device for characterizing and evaluating the uniformity of fiber slurry dispersion. The device can be implemented via software, hardware, or a combination of both. From a hardware perspective, as... Figure 5 The diagram shown is a hardware architecture diagram of a computing device used for characterizing and evaluating the uniformity of fiber slurry dispersion, as provided in an embodiment of the present invention. (Except for...) Figure 5 In addition to the processor, memory, network interface, and non-volatile memory shown, the computing device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing packets. Taking software implementation as an example, such as... Figure 6As shown, as a logical device, it is formed by the CPU of its computing device reading the corresponding computer program from the non-volatile memory into the memory for execution. This embodiment provides a fiber slurry dispersion uniformity characterization and evaluation device, including: a preprocessing module 600, a determination module 602, a flow field simulation module 604, a particle simulation module 606, a coupling module 608, and an analysis module 610;

[0112] The preprocessing module 600 is used to obtain the actual dimensions of the pulping equipment and construct a three-dimensional geometric model based on the actual dimensions;

[0113] The determination module 602 is used to determine the flow physical model, boundary conditions and initial conditions of the fluid within the three-dimensional geometric model based on the actual working conditions of the pulping equipment.

[0114] The flow field simulation module 604 is used to perform flow field simulation and solution based on the flow physics model, boundary conditions and initial conditions, and obtain flow field parameters.

[0115] The particle simulation module 606 is used to construct filling units and determine the target size of particles used to simulate fibers based on actual working conditions; wherein, the number of particles of the target size included in the filling unit is used to characterize the fiber concentration.

[0116] The coupling module 608 is used to perform simulation calculations based on the flow field parameters and the particles in the filling unit to obtain a converged solution.

[0117] The analytical module 610 is used to extract and analyze the converged solution to obtain the coefficient of variation, which characterizes the degree of fiber dispersion uniformity under actual working conditions.

[0118] In some specific implementations, the preprocessing module 600 can be used to perform step 100, the determination module 602 can be used to perform step 102, the flow field simulation module 604 can be used to perform step 104, the particle simulation module 606 can be used to perform step 106, the coupling module 608 can be used to perform step 108, and the parsing module 610 can be used to perform step 110.

[0119] In some specific implementations, the preprocessing module 600 is also used to perform the following operations:

[0120] Construct a three-dimensional geometric model proportionally to the actual dimensions;

[0121] Based on the pulping equipment, the flow region of the fluid is determined in the three-dimensional geometric model, and the three-dimensional geometric model is meshed.

[0122] In some specific implementations, the determining module 602 is also used to perform the following operations:

[0123] The flow physics model adopts a moving mesh model, and the boundary conditions are determined according to the actual working conditions;

[0124] Determine the initial conditions in the actual working conditions; the initial conditions include fluid volume and flow field velocity.

[0125] In some specific implementations, the flow field simulation module 604 is also used to perform the following operations:

[0126] The flow field was simulated using the Euler method. By solving the continuity equation and the momentum equation, flow field parameters, including the flow field distribution and pressure distribution, were obtained.

[0127] In some specific implementations, the particle simulation module 606 is also used to perform the following operations:

[0128] Determine the actual size of the fiber based on the actual working conditions;

[0129] Based on the flow field parameters, the initial motion trajectory of the fiber is determined;

[0130] The actual size of the fiber is enlarged according to a preset magnification ratio to obtain several magnified sizes;

[0131] Based on the flow field parameters, the motion trajectory of each magnified dimension is determined;

[0132] Determine whether a motion trajectory with the same magnified size as the initial motion trajectory exists;

[0133] If it exists, obtain the magnification ratio of the motion trajectory of that magnified size, and determine the maximum magnification ratio from the magnification ratio;

[0134] The actual size of the fiber is magnified using the maximum magnification ratio to obtain the target size.

[0135] In some specific implementations, the particle simulation module 606 is also used to perform the following operations:

[0136] Particle loading is performed using filling units; the fiber concentration within the filling units is the same as the fiber concentration under actual working conditions.

[0137] In some specific implementations, the parsing module 610 is also used to perform the following operations:

[0138] The convergent solution is analyzed to obtain the particle location distribution information;

[0139] The flow region of the fluid in the three-dimensional geometric model is divided into several region units of the same size;

[0140] Based on the location distribution information, determine the number of particles in each regional unit;

[0141] The average number of particles in the region unit is calculated by taking the average value to obtain the average number of particles under actual working conditions.

[0142] The standard deviation of the number of particles within a region unit is calculated to obtain the standard deviation.

[0143] The ratio of the standard deviation to the average number of particles is used as the coefficient of variation.

[0144] It is understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on a fiber slurry dispersion uniformity characterization and evaluation device. In other embodiments of the present invention, a fiber slurry dispersion uniformity characterization and evaluation device may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0145] The information interaction and execution process between the modules in the above-mentioned device are based on the same concept as the method embodiment of the present invention, and the specific details can be found in the description of the method embodiment of the present invention, and will not be repeated here.

[0146] This invention also provides a computing device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements a method for characterizing and evaluating the uniformity of fiber slurry dispersion according to any embodiment of this invention.

[0147] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program causes the processor to perform a method for characterizing and evaluating the uniformity of fiber slurry dispersion according to any embodiment of this invention.

[0148] Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the embodiments described above is stored, and the computer (or CPU or MPU) of the system or apparatus may read and execute the program code stored in the storage medium.

[0149] In this case, the program code read from the storage medium can itself implement the function of any of the above embodiments, and therefore the program code and the storage medium storing the program code constitute part of the present invention.

[0150] Examples of storage media used to provide program code include floppy disks, hard disks, magneto-optical disks, optical disks (such as CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, program code can be downloaded from a server computer via a communication network.

[0151] Furthermore, it should be clear that not only can the program code read by the computer be executed, but also the operating system or other components operating on the computer can be instructed based on the program code to perform some or all of the actual operations, thereby realizing the function of any of the embodiments described above.

[0152] Furthermore, it is understood that the program code read from the storage medium is written to the memory set in the expansion board inserted into the computer or to the memory set in the expansion module connected to the computer. Then, based on the instructions of the program code, the CPU or other components installed on the expansion board or expansion module execute some and all of the actual operations, thereby realizing the function of any of the above embodiments.

[0153] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0154] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the degree of uniformity of dispersion of a fiber slurry, characterized by, The method comprises the following steps: acquiring actual dimensions of a pulping device, and constructing a three-dimensional geometric model according to the actual dimensions; determining a flow physical model, boundary conditions and initial conditions of fluid in the three-dimensional geometric model according to actual working conditions of the pulping device; performing flow field simulation solving according to the flow physical model, the boundary conditions and the initial conditions to obtain flow field parameters; constructing a filling unit and determining target sizes of particles for simulating fibers according to the actual working conditions; wherein the number of particles of the target sizes included in the filling unit is used to represent fiber concentration; performing simulation calculation according to the flow field parameters and the particles in the filling unit to obtain a converged solution; wherein the simulation calculation ends when the converged solution is obtained by loading the particles in the flow field according to the flow field parameters, coupling the motion of the particles with the flow motion to perform simulation calculation, and the motion of the particles in the three-dimensional geometric model reaches stability; extracting and analyzing the converged solution to obtain a coefficient of variation for representing the uniformity of fiber dispersion under the actual working conditions; wherein the steps include: extracting and analyzing the converged solution to obtain position distribution information of the particles; dividing the flow region of fluid in the three-dimensional geometric model into a plurality of regional units; determining the number of particles in each regional unit according to the position distribution information; and calculating the coefficient of variation according to the number of particles in each regional unit. The calculation of the coefficient of variation comprises: performing mean value calculation on the number of particles in the regional unit to obtain the average number of particles under the actual working conditions; performing standard deviation calculation on the number of particles in the regional unit to obtain a standard deviation; taking the ratio of the standard deviation to the average number of particles as the coefficient of variation.

2. The method of claim 1, wherein, The construction of the three-dimensional geometric model according to the actual dimensions comprises: constructing a three-dimensional geometric model in proportion to the actual dimensions; determining a flow region of fluid in the three-dimensional geometric model according to the pulping device, and performing mesh division on the three-dimensional geometric model.

3. The method of claim 1, wherein, The determination of the flow physical model, the boundary conditions and the initial conditions of fluid in the three-dimensional geometric model according to the actual working conditions of the pulping device comprises: the flow physical model adopts a moving mesh model, and the boundary conditions are determined according to the actual working conditions; determining the initial conditions in the actual working conditions; wherein the initial conditions include fluid volume and flow field velocity.

4. The method of claim 1, wherein, The flow field simulation solving according to the flow physical model, the boundary conditions and the initial conditions to obtain flow field parameters comprises: performing flow field simulation by Euler method to obtain flow field parameters including flow field distribution and pressure distribution by solving continuity equation and momentum equation.

5. The method of claim 1, wherein, The construction of the filling unit and the determination of the target sizes of particles for simulating fibers according to the actual working conditions comprise: determining the actual size of the fibers according to the actual working conditions; determining the initial motion trajectory of the fibers based on the flow field parameters; enlarging the actual size of the fibers according to a preset enlargement ratio to obtain a plurality of enlarged sizes; determining the motion trajectory of each enlarged size based on the flow field parameters; determining whether there is a same initial motion trajectory of the enlarged size; if there is, obtaining an enlarged ratio of the motion trajectory of the enlarged size, and determining a maximum enlarged ratio from the enlarged ratio; enlarging the actual size of the fiber by the maximum enlarged ratio to obtain the target size.

6. The method of claim 1, wherein, loading the particles by using the filling unit; wherein the fiber concentration in the filling unit is the same as the fiber concentration in the actual working condition.

7. An apparatus for evaluating the uniformity of dispersion of a fiber slurry, characterized by A computer program product for implementing the method of any one of claims 1 to 6, comprising: a preprocessing module configured to obtain an actual size of a pulping device, and construct a three-dimensional geometric model according to the actual size; a determining module configured to determine a flow physical model, boundary conditions and initial conditions of a fluid in the three-dimensional geometric model according to an actual working condition of the pulping device; a flow field simulation module configured to perform flow field simulation solving according to the flow physical model, the boundary conditions and the initial conditions, and obtain flow field parameters; a particle simulation module configured to construct a filling unit and determine a target size of a particle for simulating a fiber according to the actual working condition; wherein the number of the particles of the target size included in the filling unit is used to represent a fiber concentration; a coupling module configured to perform simulation calculation according to the flow field parameters and the particles in the filling unit, and obtain a converged solution; an analysis module configured to extract and analyze the converged solution, and obtain a coefficient of variation for representing a fiber dispersion uniformity in the actual working condition.

8. A computing device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method of any one of claims 1 to 6.

9. A computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed in a computer, causes the computer to perform the method of any one of claims 1 to 6.

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