Rock crushing lumpiness statistical method and system based on particle flow simulation

Abstract

The invention provides a particle flow simulation-based rock crushing lumpiness statistical method and system, and particularly relates to the technical field of open bench blasting. The method comprises the following steps: selecting a set of blasting scheme in an engineering project, introducing a blasting parameter table and constructing a model size of a test; obtaining an engineering sample according to surveying and mapping exploration data, pouring the test piece in combination with a similar material mixing ratio, and performing a static test to obtain mechanical properties of the test piece; blasting effects submitted to a solver under different explosive unit consumptions are simulated through particle flow, the particle volume is calculated, and meanwhile the blasting effect under an analogue simulation test is compared with the rock breaking effect of a field prototype test; a distribution model is established through numerical model simulation, and a lumpiness statistical fitting curve under different unit consumptions is obtained; programming is facilitated to further optimize the algorithm, and the crushing lumpiness can be better counted. According to the method, blasting lumpiness prediction of unit consumption of different explosives under surface blasting is completed before blasting construction, the engineering risk is reduced, and the engineering efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of open-air bench blasting, and particularly relates to a rock broken block size statistical method and system based on particle flow simulation. BACKGROUND

[0002] Currently, mainstream algorithms are Lagrange algorithm, Euler algorithm, Arbitrary Lagrange-Euler (ALE) fluid-structure coupling algorithm, and Smoothed Particle Hydrodynamics (SPH) algorithm. When the Arbitrary Lagrange-Euler (ALE) fluid-structure coupling algorithm is used, in the traditional numerical simulation method, the mesh division process is not only high in modeling complexity, but also prone to grid distortion when dealing with material large deformation, breaking and scattering and other nonlinear problems, resulting in a decrease in calculation accuracy or even a calculation interruption. Especially when facing engineering problems involving complex broken forms such as rock blasting and metal impact breaking, the traditional finite element method often needs to repeatedly perform mesh redivision, which not only significantly increases the calculation time, but also introduces additional numerical errors. Therefore, it is of great significance to improve the engineering production efficiency by statistically analyzing the block size of the open-air blasting and the broken block size. In the construction of the blasting block size model, the Harries theoretical model is a typical representative. The model believes that dynamic strain action induces rock rupture, and the distance between adjacent cracks constitutes the linear size reference of the blasting rock block. However, when the broken particle group is statistically analyzed by the traditional numerical simulation method, it generally faces problems such as low artificial statistical efficiency and limited data scale.

[0003] Prior art one, China patent, application number: 202510392976.6 discloses a counter-inclined slope pre-splitting blasting structure and method, including pre-splitting hole and empty hole; the pre-splitting hole is arranged in a row on the designed boundary slope line, and the empty hole is arranged between adjacent pre-splitting holes; the pre-splitting hole is filled with explosive, and the empty hole is not filled with explosive. Although, the pre-splitting surface is avoided from being uneven, it is ensured that it is easier to form a smooth wall surface after pre-splitting blasting, the problems of great blasting vibration hazards, difficult slope management, large rock crushing size and other problems causing slope instability are solved, the production task can be completed more safely and efficiently, the technology is simple, easy to implement, low in cost, good in pre-splitting effect, low in slope management investment, not only a large amount of capital investment can be saved, but also the long-term supply problem of mining caused by boundary suppression to expose the lower ore body is solved; the problem of easy damage to the reserved slope surface in traditional pre-splitting blasting is maximized, especially suitable for slope pre-splitting blasting of counter-inclined rock stratum in open-pit mining; however, particle flow simulation involves a large number of particle damage evolution calculations, especially in three-dimensional models, the number of particles is large, and the operation of explicit solver takes a long time, which is difficult to quickly respond to the dynamic optimization demand of blasting scheme in engineering.

[0004] Prior art two, China patent, application number: 202411064596.1 discloses a research method for sandstone damage under the coupling action of saturation and initial damage, belonging to the technical field of rock mass mechanics research method. The technical scheme is: using the improved SHPB system + DIC non-contact test system, impact test is carried out on sandstone under different damage degrees and water content, the images of rock at each time stage under dynamic load are better recorded, the damage evolution and crack propagation law of rock are effectively studied; the soil sieve is used to screen and statistically analyze the broken sandstone fragments after impact load, and combined with low-field nuclear magnetic technology, the influence of initial damage and saturation rate on the mechanical properties of sandstone is analyzed, and the relationship between the distribution of mesoscopic pores and the macroscopic mechanical properties is studied. Although, a new path is proposed for the research on the damage characteristics of sandstone under the coupling action of saturation and initial damage, which can provide theoretical analysis for the failure and instability mechanism of sandstone with initial damage after disturbance in mine exploitation and tunnel engineering construction; however, although the static mechanical parameters are obtained through similar material test pieces, the composition and structure of similar materials are difficult to completely reproduce the heterogeneity, crack distribution and other characteristics of real rock mass, resulting in deviation of the parameters input into the finite element software, affecting the authenticity of the simulation results.

[0005] The prior art three, Chinese patent, application number: 202410658333.7 provides a tunnel mixed emulsion explosive blasting excavation construction method, belongs to the technical field of tunnel blasting, the method comprises the following steps: drilling construction is carried out on the tunnel; the preparation of on-site mixed emulsion explosive is carried out; the processing and charging of detonating agent; the design of underground or tunnel mixed explosive construction technology; on-site quality technical detection and control, and the completion of construction. Although the mixed explosive vehicle is used to mix the emulsion matrix and the sensitized liquid in a certain proportion to generate gel-like mixed explosive, and then the mixed explosive is filled into the blast hole in the form of injection, the problems of poor drilling quality in deep mining, hole jamming, blockage and refusal of packaged explosive into the hole, and waste of explosive charge due to uncoupling are solved, the charging efficiency is improved, the blind shot rate is reduced, the safety of underground blasting construction is ensured, the utilization rate of drilling is effectively improved, and the size of rock broken block is reduced, and the efficiency of excavation and loading is improved; however, when the volume cube root is used as the equivalent block size, the simplification may underestimate or overestimate the size of the block based on the assumption of a cube, and the randomness of the cross section position may lead to distortion of the statistical results of damaged and undamaged particles when the cross section is selected as the functional counting particle.

[0006] At present, the prior art one, the prior art two and the prior art three have the problems of limited matching degree of model parameters and actual rock mass, simplification error of block size statistical method and low matching degree of calculation efficiency and engineering demand. In order to solve the above problems, the present application provides a rock broken block size statistical method and system based on particle flow simulation; the inherent defects of the traditional continuous medium mechanics modeling method in simulating the breaking process of blocky materials are innovatively improved; in order to solve the technical problems, the present application creatively introduces the meshless particle method of smoothed particle hydrodynamics (SPH), which fundamentally avoids the limitations of grid method in dealing with material breaking problems. The open step blasting numerical simulation is used as a backup means when field test cannot be carried out, and its powerful function and wide application range are recognized by many scholars. Rock block size is an important indicator to evaluate the blasting effect, and the blasting efficiency is improved and the construction cost is reduced through suitable blasting parameters; the present application innovatively proposes a rock broken block size automatic statistical method based on particle flow numerical simulation technology, and realizes intelligent identification of broken body geometric characteristics and automatic calculation of particle size distribution through development of special algorithm module. SUMMARY

[0007] The main purpose of the present application is to provide a rock broken block size statistical method and system based on particle flow simulation, to solve the problems of limited matching degree of model parameters and actual rock mass, simplification error of block size statistical method and low matching degree of calculation efficiency and engineering demand.

[0008] To achieve the above object, the present application provides the following technical solutions.

[0009] A rock fragmentation statistical method based on particle flow simulation, the rock fragmentation statistical method comprising the following steps:

[0010] The blasting parameters and static mechanical performance parameters are proportionally scaled and input into a finite element analysis software, and a blasting fragmentation model is established according to the proportion; the cross-section selection function of the finite element analysis software is used to count the damaged particles and undamaged particles, so that the number of particles in each block after blasting is obtained; the number of particles in each block is multiplied by the mass of a single particle to obtain the mass of the block, and the volume of the block is calculated according to the density of concrete; the equivalent length is used to represent the fragmentation, and the cube root of the volume is used as the equivalent rock fragmentation.

[0011] As a further improvement of the present application, the process of using the cube root of the volume as the equivalent rock fragmentation comprises the following steps:

[0012] The proportionally scaled blasting parameters and static mechanical performance parameters are placed into the finite element analysis software environment to construct a blasting fragmentation model containing the rock mass and explosive material; after the simulation of the blasting process is completed, the state of all particles in the blasting fragmentation model is identified by means of the cross-section analysis function in the finite element analysis software, and the undamaged particles and damaged particles are distinguished;

[0013] For the damaged area, the damaged particle sets that are connected to each other and jointly constitute an independent fragment are identified according to the spatial topological correlation between the particles; each damaged particle set is defined as a particle aggregation unit, representing a rock block formed after blasting; the total number of particles contained in each particle aggregation unit is counted, and the total number of particles is multiplied by the mass of a single particle calibrated in advance to obtain the total mass of the particle aggregation unit; and then the theoretical volume of the fragment is inversely calculated according to the known density of the rock mass material through the mass-density relationship;

[0014] The volume of each fragment is subjected to cube root operation to convert it into a geometrically representative linear dimension, and the linear dimension is the equivalent rock fragmentation of the fragment.

[0015] As a further improvement of the present application, the process of identifying the damaged particle sets that are connected to each other and jointly constitute an independent fragment comprises the following steps:

[0016] The spatial coordinate data of the damaged particles in the damaged area are processed to establish a spatial relationship criterion based on the proximity criterion, so as to judge whether any two particles have a direct spatial correlation;

[0017] The space relationship criterion is applied to compare all damaged particles with each other; when any two particles satisfy the space relationship criterion, a virtual connecting link is established between the two particles, indicating that the two particles belong to the same potential space aggregate; after traversing all particle pairs, the virtual connecting link links some or all damaged particles to each other, forming a complex and discontinuous space connecting network;

[0018] The space connecting network is analyzed, and the target is to decompose the space connecting network into a plurality of maximum connected sub-networks which are independent of each other and internally connected; all particles in each maximum connected sub-network are associated with each other through direct or indirect virtual connecting links, and the maximum connected sub-network has no connection relationship with other parts in the space connecting network; the macroscopic space connecting network is deconstructed into a plurality of microscopic independent connected components.

[0019] As a further improvement of the present application, the process of analyzing the space connecting network comprises the following steps:

[0020] A uniform unvisited state flag is created for all damaged particles in the space connecting network, which is used to track the access state of each particle in subsequent processing;

[0021] An unvisited damaged particle in the space connecting network is selected as a starting point of the current exploration; a local connectivity exploration process is started; all other damaged particles directly or indirectly associated with the current starting point are searched and marked through all virtual connecting links; all marked particles form a temporary particle group, and all particles in the temporary particle group are connected to each other and have no path to particles outside the group formed by virtual connecting links;

[0022] The temporary particle group is confirmed and recorded as an independent maximum connected sub-network; at the same time, the access state of all particles in the maximum connected sub-network is updated to have been visited; another unvisited damaged particle is selected as a new starting point outside the marked temporary particle group, and the local connectivity exploration and marking process is repeated to identify and record the next independent maximum connected sub-network;

[0023] The cycle is repeated to access and process each unvisited damaged particle in the space connecting network, and each cycle starts with an unvisited particle as a starting point to generate an independent maximum connected sub-network; when there is no unvisited damaged particle in the space connecting network, the cycle is terminated.

[0024] As a further improvement of the present application, the process of starting a local connectivity exploration process comprises the following steps:

[0025] Create a dynamic list named current probe sequence and add the starting particle as the first element of the current probe sequence; meanwhile, create an empty set named temporary association set to temporarily store all the discovered associated particles;

[0026] Enter an iterative processing loop, in each iteration, take the first particle in the current probe sequence as the current core particle; perform a key operation on the current core particle;

[0027] Filter the acquired adjacent particles; all the adjacent particles that meet the conditions are marked as newly discovered associated particles;

[0028] Process the newly discovered associated particles in two places: add all the newly discovered associated particles to the temporary association set; append the newly discovered associated particles to the end of the current probe sequence as the current core particle to be processed in the subsequent iteration; update the access state of the newly discovered associated particles to visited; after completing the processing of all the adjacent particles of the current core particle, the iteration ends; the processed current core particle in the current probe sequence is removed, and the subsequent particles in the current probe sequence are waiting to be processed.

[0029] As a further improvement of the present application, the process of processing the newly discovered associated particles in two places includes the following steps:

[0030] Perform the first processing operation on the newly discovered associated particles: integrate the newly discovered associated particles into a container named temporary association set; and continue to exist throughout the local connectivity exploration process, gathering all the associated particles traced back from the current starting particle;

[0031] Perform the second parallel processing operation: sequentially append the same batch of newly discovered associated particles to the tail of a dynamic list named current probe sequence according to the order in which they are discovered; the current probe sequence plans the order of particles to be explored next;

[0032] After the two processes, the newly discovered associated particles are given as components of the temporary association set and as members waiting in line in the current probe sequence; achieve the output of the updated temporary association set containing more particles and the updated current probe sequence containing more particles to be explored.

[0033] As a further improvement of the present application, the process of sequentially appending to the tail of a dynamic list named current probe sequence includes the following steps:

[0034] Get the inherent order of the newly discovered associated particles; when the current core particle queries its virtual connection link, the acquired adjacent particles form an initial, original sequence based on the spatial query result;

[0035] Create a temporary ordered list named the particle group to be queued, and put the newly discovered associated particles into the particle group to be queued in the order of their original sequence without any changes; and link the ordered list of the particle group to be queued to the end of the existing content of the current probe sequence dynamic list;

[0036] After the linking is completed, the particle group to be queued is dissolved, and its content has become part of the current probe sequence; the length of the current probe sequence is extended, and the newly added tail content provides new particle objects to be probed for the iteration process.

[0037] As a further improvement of the present application, the blasting parameters of one set of blasting scheme in the engineering project are obtained, and the size of the blasting block size model is determined according to the blasting parameters; at the same time, different rock mass occurrences are sampled, and similar material mix proportions are used to cast test pieces of different rock properties, and static mechanics tests are performed to obtain the static mechanics performance parameters of the cast test pieces.

[0038] The blasting parameters include main blast hole arrangement and initiation delay selection, borehole diameter design, and explosive and detonator selection; the static mechanics performance parameters include density, uniaxial compressive strength, elastic modulus, and fracture toughness.

[0039] As a further improvement of the present application, the mass of a single particle is measured, and the rock block size of the existing incomplete damage particles is counted; the rock block size represented by adjacent completely damaged particles is counted, and the remaining completely damaged loose particles are considered to have a block size less than 20mm; the statistical results of the number of blasted particles under the explosive unit consumption are given; and the average broken block size of the rock mass under the corresponding explosive unit consumption in the actual engineering is predicted.

[0040] To achieve the above object, the present application also provides the following technical scheme:

[0041] A rock broken block size statistical system based on particle flow simulation is applied to the rock broken block size statistical method based on particle flow simulation, and the rock broken block size statistical system based on particle flow simulation comprises:

[0042] The blasting parameter acquisition module is used to obtain the blasting parameters of one set of blasting scheme in the engineering project, and the size of the blasting block size model is determined according to the blasting parameters; at the same time, different rock mass occurrences are sampled, and similar material mix proportions are used to cast test pieces of different rock properties, and static mechanics tests are performed to obtain the static mechanics performance parameters of the cast test pieces.

[0043] An equivalent rock block size module is derived for scaling the blasting parameters and static mechanical property parameters and inputting into a finite element analysis software to establish a blasting block size model in proportion; the cross section selection function of the finite element analysis software is used to count the damaged particles and undamaged particles to obtain how many particles in each block after blasting; the particle number of each block is multiplied by the mass of a single particle to obtain the mass of the block, and the volume of the block is calculated according to the density of the concrete; the equivalent length is used to represent the block size, and the cube root of the volume is used as the equivalent rock block size;

[0044] A rock mass average broken block size module is used for measuring the mass of a single particle and statistically obtaining the rock block size of the undamaged particles, the rock block size represented by the adjacent completely damaged particles, and the remaining completely damaged loose particles being regarded as the block size less than 20 mm, and giving the statistical results of the blasted heap particles under the specific explosive unit consumption; the rock mass average broken block size under the corresponding explosive unit consumption in the actual project is predicted.

[0045] The present application combines the blasting parameters (main blast hole arrangement, etc.) and the static mechanical parameters (density, etc.) of the rock mass, obtains the basic data through the static mechanical test of the similar material test piece, establishes the blasting block size model containing the rock mass and the explosive in the finite element software after scaling the parameters, adopts the particle counting method (statistically counting the damaged and undamaged particles) to calculate the mass and volume of the block, and uses the cube root of the volume as the equivalent block size; the block size of the particles in different damage states (including the loose particles less than 20 mm) is classified and counted, the statistical results of the blasted heap particles under the specific explosive unit consumption are obtained, and the average broken block size in the actual project is predicted. Through the combination of the test data and the finite element simulation, the quantitative analysis and accurate prediction of the blasting block size are realized, a reliable basis for the rock mass breaking effect corresponding to the explosive unit consumption in the actual project is provided, and the scientificity and accuracy of the blasting scheme optimization are improved. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 It is a step flowchart diagram of an embodiment of the rock broken block size statistical method based on the particle flow simulation of the present application;

[0047] Figure 2 It is a step flowchart diagram of obtaining the static mechanical property parameters of the cast test piece through the static mechanical test of an embodiment of the rock broken block size statistical method based on the particle flow simulation of the present application;

[0048] Figure 3 It is a step flowchart diagram of using the cube root of the volume as the equivalent rock block size of an embodiment of the rock broken block size statistical method based on the particle flow simulation of the present application;

[0049] Figure 4 It is a step flowchart diagram of predicting the rock mass average broken block size under the corresponding explosive unit consumption in the actual project of an embodiment of the rock broken block size statistical method based on the particle flow simulation of the present application;

[0050] Figure 5 A functional module schematic diagram of an embodiment of the rock fragmentation size statistical system based on particle flow simulation of the present application;

[0051] Figure 6 A step flow schematic diagram of the rock fragmentation size statistical method based on particle flow of the present application;

[0052] Figure 7 A three-dimensional size diagram of a model test is given in the present application;

[0053] Figure 8 According to different single-hole charge damage, a schematic diagram is given in the present application;

[0054] Figure 9 A single particle mass measurement diagram of a blast pile is given in the present application;

[0055] Figure 10 A particle number statistical diagram of a blast pile is given in the present application;

[0056] Figure 11 A rock blasting fragmentation fitting curve distribution diagram is given in the present application;

[0057] Figure 12 A structural schematic diagram of an embodiment of the electronic device of the present application is given;

[0058] Figure 13 A structural schematic diagram of an embodiment of the storage medium of the present application is given. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0060] The terms first, second, third, etc. are used only to describe various features and do not imply or suggest relative importance or a number of the features indicated. Thus, the features defined with first, second, third, etc. can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of multiple is at least two, for example, two, three, etc., unless otherwise explicitly and specifically limited. All directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present application are only used to explain the relative position relationship, movement condition, etc. between components in a certain posture (as shown in the drawings), and if the certain posture changes, the directional indications also change accordingly. In addition, the terms include and have as well as any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units not listed, or optionally also includes other steps or units inherent to the process, method, product or device.

[0061] Reference herein to an embodiment means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearance of the phrase in various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily independent or alternative embodiments to other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0062] As shown in Figure 1 The present embodiment provides an embodiment of a rock fragmentation size distribution statistical method based on particle flow simulation, which specifically includes the following steps:

[0063] Step S1: Obtain the blasting parameters of one set of blasting scheme in the engineering project, and determine the size of the blasting size distribution model according to the blasting parameters; at the same time, sample different rock mass occurrences, and cast test pieces with similar material mix proportions for different rock mass lithology, and perform statics test to obtain the static mechanical performance parameters of the cast test pieces;

[0064] The blasting parameters include main blast hole arrangement and initiation delay selection, borehole diameter design, and explosive and detonator selection; and the static mechanical performance parameters include density, uniaxial compressive strength, elastic modulus, and fracture toughness;

[0065] Step S2: scale the blasting parameters and static mechanical property parameters, and input them into the finite element analysis software to establish a blasting block size model according to the scale; use the cross section selection function of the finite element analysis software to count the damaged particles and undamaged particles to obtain how many particles in each block after blasting; multiply the number of particles in each block by the mass of a single particle to obtain the mass of the block, and calculate the volume of the block according to the density of the concrete; use the equivalent length to represent the block size, and take the cube root of the volume as the equivalent rock block size;

[0066] The blasting block size model comprises the rock mass and the explosive.

[0067] Step S3: measure the mass of a single particle and statistically obtain the rock block size of the undamaged particles, the rock block size represented by the adjacent completely damaged particles, and the remaining completely damaged loose particles are regarded as the block size less than 20 mm, and the statistical results of the blasted particles under the specific explosive unit consumption are given; the average broken block size of the rock mass under the corresponding explosive unit consumption in the actual project is predicted.

[0068] Preferably, the embodiment combines the blasting parameters (main blast hole arrangement, etc.) and the static mechanical parameters of the rock mass (density, etc.), obtains the basic data through the static mechanical test of the similar material test piece, scales the parameters, establishes the blasting block size model containing the rock mass and the explosive in the finite element software, adopts the particle counting method (counts the damaged and undamaged particles) to calculate the mass and volume of the block, and takes the cube root of the volume as the equivalent block size; classifies and statistically obtains the block size of the particles in different damage states (including the loose particles less than 20 mm), predicts the average broken block size in the actual project based on the statistical results of the blasted particles under the specific explosive unit consumption. Through the combination of the test data and the finite element simulation, the quantitative analysis and accurate prediction of the blasting block size are realized, a reliable basis for the broken effect of the rock mass corresponding to the explosive unit consumption in the actual project is provided, and the scientificity and accuracy of the optimization of the blasting scheme are improved.

[0069] Further, as shown in Figure 2 The process of performing the static mechanical test to obtain the static mechanical property parameters of the cast test piece in step S1 specifically includes the following steps:

[0070] Step S11: based on a set of blasting scheme selected in the engineering project, reference the blasting parameter table given by the engineering to construct the model size of the test, which includes determining the main blast hole arrangement and the initiation delay selection, the design of the borehole diameter, and the selection of the explosive and the detonator;

[0071] Step S12: according to the surveying and mapping exploration data, sample different rock mass occurrences, and cast test pieces with similar material mix proportions for different lithology to obtain the static mechanical property parameters of the test pieces through the static mechanical test;

[0072] The static mechanical property parameters include: density, uniaxial compressive strength, elastic modulus, and fracture toughness.

[0073] Step S13: The characteristic section view is given in AutoCAD; all dimensions are strictly scaled according to the proportion, and the similarity criterion is derived to analyze through the MLT dimension system, and the model test similarity ratio is inferred and corrected.

[0074] Preferably, the embodiment is based on the actual engineering project blasting scheme, and the engineering blasting parameter table (including main blast hole arrangement, delay time, blast hole diameter, and explosive detonator type) is cited to construct the test model size, so as to realize the correlation between the model and the engineering; according to the surveying and mapping exploration data, the different rock mass occurrences are sampled, the similar material mixing ratio is used to cast the test piece, the density, uniaxial compressive strength and other static mechanical parameters are obtained through the static mechanical test, and the rock mass characteristics are accurately matched; the section view of the blasting area is drawn in AutoCAD, the dimensions are strictly scaled according to the proportion, the similarity criterion is derived, the model test similarity ratio is inferred and corrected through the MLT dimension system analysis, and the model similarity is ensured. By correlating the actual engineering parameters and the rock mass sampling, it is ensured that the test model is close to the actual engineering, and the simulation authenticity is improved; the similar material test piece and the static mechanical test are combined to provide accurate mechanical parameter support for the model; the AutoCAD drawing and the similarity ratio correction mechanism ensure the scientificity of the model size proportion, reduce the similarity deviation, and thus improve the reliability of the blasting model test, and lay a precise and controllable test foundation for the subsequent blasting effect analysis and scheme optimization.

[0075] Further, as shown in Figure 3 , the process of taking the cube root of the volume as the equivalent rock block size in step S2 specifically includes the following steps:

[0076] Step S21: The scaled blasting parameters and static mechanical property parameters are placed into the finite element analysis software environment to construct a blasting block size model containing rock mass and explosive material; after the simulation of the blasting process is completed, the state of all particles in the blasting block size model is identified by means of the section analysis function in the finite element analysis software, and two types of particles are distinguished: one type is undamaged particles that maintain structural integrity, and the other type is damaged particles that have undergone fragmentation;

[0077] Step S22: For the damaged area, the damaged particle set that are connected to each other and jointly constitute an independent fragment are identified according to the spatial topological relation between the particles; each damaged particle set is defined as a particle aggregation unit, representing a rock block formed after blasting; the total number of particles contained in each particle aggregation unit is counted, and the total number of particles is multiplied by the mass of a single particle calibrated in advance to obtain the total mass of the particle aggregation unit; then, according to the known density of the rock mass material, the theoretical volume of the fragment is inversely calculated through the mass-density relationship;

[0078] Step S23: Cubing the volume of each fragment, which is converted into a geometric representative linear size, i.e., the equivalent rock block size of the fragment; the process establishes a mapping relationship from particle counting to spatial geometry.

[0079] Preferably, the present embodiment realizes the coherent quantification from the microscopic particle state to the macroscopic block index based on the identification of particle aggregation units, the step-by-step calculation of particle number-mass-volume, and the final conversion to the equivalent linear block size through volume mapping, providing basic data for subsequent block distribution statistics.

[0080] Further, the process of identifying the set of damaged particles that are connected to each other and collectively constitute an independent fragment in step S22 specifically includes the following steps:

[0081] Step S221: Process the spatial coordinate data of the damaged particles in the damaged area to establish a spatial relationship criterion based on proximity criteria to determine whether any two particles have a direct spatial association;

[0082] Step S222: Apply the spatial relationship criterion to compare all damaged particles pairwise; when any two particles satisfy the spatial relationship criterion, a virtual connection link is established between the two particles, indicating that the two particles belong to the same potential spatial aggregate; after traversing all particle pairs, the virtual connection links link some or all damaged particles to each other, forming a complex and discontinuous spatial connection network;

[0083] Step S223: Analyze the spatial connection network, the goal of which is to decompose it into several independent, internally connected maximum connected subnetworks; each maximum connected subnetwork has all its internal particles connected to each other through direct or indirect virtual connection links, while the maximum connected subnetwork has no connection with other parts of the spatial connection network; the entire macroscopic spatial connection network is deconstructed into multiple microscopic independent connected components;

[0084] Each independent connected component is defined as a particle aggregation unit, representing a set of damaged particles that are closely connected on the spatial connection network and cannot be further separated, corresponding to an independent rock fragment formed after blasting.

[0085] Preferably, the present embodiment completes the conversion from discrete damaged particles to a set of independent fragments with clear spatial topological boundaries by establishing particle interconnection criteria, constructing a global connection network, and analyzing the global connection network to identify independent maximum connected components.

[0086] Further, the process of analyzing the spatial connection network in step S223 includes the following steps:

[0087] Step S2231: Create a uniform unvisited state flag for all damaged particles in the spatial connection network, to track the access state of each particle in subsequent processing;

[0088] Step S2232: Arbitrarily select one damaged particle that has not been visited from the spatial connection network as the starting point of the current exploration; start a local connectivity exploration process with the starting point particle as the root; search and pass through all virtual connection links to find and mark all other damaged particles associated directly or indirectly from the current starting point; all marked particles form a temporary particle group, and all particles in the temporary particle group are connected to each other and have no path to particles outside the group formed by virtual connection links;

[0089] Step S2233: After completing the local connectivity exploration process, the temporary particle group is confirmed and recorded as an independent maximum connected sub-network; at the same time, the access state of all particles in the maximum connected sub-network is updated to visited; outside the marked temporary particle group in the spatial connection network, another damaged particle that has not been visited is selected as a new starting point, and the local connectivity exploration and marking process is repeated to identify and record the next independent maximum connected sub-network;

[0090] Step S2234: This cycle is repeated to access and process each unvisited damaged particle in the spatial connection network, and each cycle starts with an unvisited particle as the starting point to finally generate an independent maximum connected sub-network; when there is no longer any unvisited damaged particle in the spatial connection network, the cycle terminates.

[0091] Preferably, the embodiment converts the nonlinear network structure into a set of connected components that are not connected to each other through the cooperative action of state identification management and topology traversal algorithm, and each component corresponds to an independent material unit defined by virtual connection in two-dimensional plane or three-dimensional space; the time complexity of the algorithm is determined by the sparsity of network connection, and the space complexity is jointly affected by the original particle size and connection density; the final output result is a connected topological closure set with strict mathematical definition, which meets the topological integrity requirement of subsequent calculation of fragment geometric parameters.

[0092] Further, the process of starting a local connectivity exploration process in step S2232 includes the following steps:

[0093] Step S22321: Create a dynamic list named current exploration sequence and add the starting point particle as the first element of the current exploration sequence; at the same time, create an empty set named temporary association set for temporarily storing all discovered associated particles;

[0094] Step S22322: Enter an iterative processing loop, in each iteration, take the particle at the head of the current probe sequence, called the current core particle; perform a key operation on the current core particle: query all the virtual connection links established, and obtain all the adjacent particles that have direct spatial association with it;

[0095] Step S22323: Screen the obtained adjacent particles; the screening condition is: the adjacent particle is a damage particle, and its access state is still unvisited; all the adjacent particles that meet the condition are marked as newly discovered associated particles;

[0096] Step S22324: Process the newly discovered associated particles in two places: add all the newly discovered associated particles to the temporary association set; append the newly discovered associated particles to the end of the current probe sequence to become the current core particle to be processed in the subsequent iteration; at the same time, update the access state of the newly discovered associated particles to visited; after completing the processing of all the adjacent particles of the current core particle, the iteration ends; the processed current core particle in the current probe sequence is removed, and the subsequent particles in the current probe sequence are waiting to be processed.

[0097] Preferably, the iterative loop of the present embodiment continues to take particles from the current probe sequence, explore their adjacent particles, and include newly discovered unvisited damage particles into the sequence and set; so that the temporary association set expands like a snowball, until the current probe sequence is emptied. The current probe sequence being emptied marks a state: starting from the original starting point particle, all damage particles that can be associated through direct or indirect virtual connection links have been explored, and no new associated particles can be discovered. At this time, the loop terminates. All the particles contained in the temporary association set constitute the defined temporary particle group; the temporary particle group is the final output of the largest connected subnetwork connected to the starting point particle; the output will be sent to record and state confirmation.

[0098] Further, the process of processing the newly discovered associated particles in two places in step S22324 specifically includes the following steps:

[0099] Step S223241: Perform the first processing operation on the newly discovered associated particles: integrate the newly discovered associated particles into a container called the temporary association set; and continue to exist throughout the local connectivity exploration process, gathering all the associated particles traced back from the current starting point particle;

[0100] Step S223242: Perform a second parallel processing operation: sequentially append the newly discovered associated particles to the tail of a dynamic list named current probe sequence in the order of their discovery; the current probe sequence plans the order of particles to be probed next;

[0101] Step S223243: Through two processes, the newly discovered associated particles are endowed as components of the temporary association set and as members queued in the current probe sequence; achieve the output of the updated temporary association set containing more particles and the updated current probe sequence containing more particles to be probed.

[0102] Preferably, the temporary association set of the embodiment maintains a complete topological snapshot of the currently known maximum connected domain, the current probe sequence realizes a mixed breadth-first / depth-first traversal strategy through ordered scheduling, the atomic update of the dual data structure ensures the execution consistency of the topology expansion process, the separated storage design reduces the complexity of state management, and supports high-concurrency particle discovery scenarios; constitutes the core iteration engine in dynamic network topology analysis, and is suitable for real-time connectivity measurement and incremental path discovery of large-scale particle systems.

[0103] Further, the process of sequentially appending to the tail of a dynamic list named current probe sequence in step S223242 specifically includes the following steps:

[0104] Step S2232421: Obtain the inherent order of the newly discovered associated particles; when the current core particle queries its virtual connection link, the adjacent particles obtained will form an initial, original sequence based on the spatial query result;

[0105] Step S2232422: Create a temporary ordered list named to-be-enqueued particle group, and place the newly discovered associated particles in the to-be-enqueued particle group in the order of their original sequence without any changes; link the ordered list of the to-be-enqueued particle group to the end of the existing content of the current probe sequence dynamic list; specifically, the first particle in the to-be-enqueued particle group is arranged immediately after the last element in the current probe sequence list, and so on, until the last particle in the to-be-enqueued particle group becomes the new end of the list;

[0106] Step S2232423: After the linking is completed, the to-be-enqueued particle group is dissolved, and its content has become part of the current probe sequence; the length of the current probe sequence is extended, and its new tail content provides new particle objects to be probed for the iteration process.

[0107] Preferably, the embodiment realizes the purpose of orderly incorporating the newly discovered particle population into the processing queue through the series of operations from acquiring the original sequence, creating a temporary ordered group, to performing overall splicing. The output is an updated and expanded current exploration sequence, which is directly used to drive the next iteration, ensuring that the exploration process can continue in depth until all related particles are exhausted.

[0108] Further, as Figure 4 shown, the process of predicting the average broken rock size of the rock mass under the actual engineering corresponding to the unit consumption of explosives in step S3 specifically includes the following steps:

[0109] Step S31: Process all equivalent rock size data to generate a model size distribution spectrum based on the blasting size model, which describes the number or mass distribution of different size levels of broken blocks at the model scale;

[0110] Step S32: All geometric scale factors and material parameter scaling factors used in the scaling process are comprehensively deduced in reverse to condense into a comprehensive conversion coefficient that reversely maps the prediction results at the blasting size model scale back to the actual engineering scale; The model size distribution spectrum is converted in all directions and scaled to the actual engineering size according to the proportional relationship, and the statistical characteristics of the distribution spectrum are also adjusted. The converted result is the actual engineering size prediction spectrum;

[0111] Step S33: In the actual engineering size prediction spectrum, the particle population with a size less than 20mm is defined and separated; A weighted integration is performed, taking the median size of each predicted particle size section as the representative size and taking the mass percentage of the actual engineering size prediction spectrum as the weight, and performing a weighted average operation; The final value obtained by the weighted average operation is defined as the predicted average broken rock size of the actual engineering project under the condition of a specific unit consumption of explosives.

[0112] Preferably, the embodiment realizes the purpose of orderly incorporating the newly discovered particle population into the processing queue through the series of operations from acquiring the original sequence, creating a temporary ordered group, to performing overall splicing. The output is an updated and expanded current exploration sequence, which is directly used to drive the next iteration, ensuring that the exploration process can continue in depth until all related particles are exhausted.

[0113] As Figure 5 shown, the embodiment also provides a rock broken size statistical system based on particle flow simulation, which is applied to the above-mentioned rock broken size statistical method based on particle flow simulation. The rock broken size statistical system based on particle flow simulation includes:

[0114] The acquisition of blasting parameters module 1 is used to acquire the blasting parameters of one set of blasting scheme in the engineering project, and the size of the blasting block model is determined according to the blasting parameters; at the same time, by sampling different rock mass occurrences, the different lithology of the rock mass is poured into test pieces by using similar material mix proportion, and the static mechanical performance parameters of the test pieces are obtained by static test;

[0115] The blasting parameters include the arrangement of main blast holes, the selection of delay time, the design of blast hole diameter, the selection of explosives and detonator, etc.; the static mechanical performance parameters include density, uniaxial compressive strength, elastic modulus and fracture toughness, etc.

[0116] The equivalent rock block size module 2 is used to scale the blasting parameters and the static mechanical performance parameters, and input them into the finite element analysis software, and establish the blasting block model according to the scale; the cross section selection function of the finite element analysis software is used to count the damaged particles and the undamaged particles, and obtain how many particles in each block after blasting; the particle number of each block is multiplied by the mass of a single particle to obtain the mass of the block, and the volume of the block is calculated according to the density of concrete; the equivalent length is used to represent the block size, and the cube root of the volume is used as the equivalent rock block size;

[0117] The blasting block model includes rock mass and explosives.

[0118] The rock mass average broken block size module 3 is used to measure the mass of a single particle and to count the rock block size of the undamaged particles, to count the rock block size represented by the adjacent completely damaged particles, and to regard the remaining completely damaged loose particles as the block size less than 20mm, to give the statistical results of the blasting particles under the unit consumption of explosives; to predict the rock mass average broken block size under the corresponding unit consumption of explosives in the actual engineering.

[0119] Preferably, this embodiment specifically acquires engineering blasting parameters (including the layout of main blast holes, etc.) to determine the model size. Simultaneously, samples are taken from different rock masses, and specimens are cast using similar materials. Static mechanical parameters such as density and uniaxial compressive strength are obtained through static tests, thus establishing a correlation between data and engineering reality. The parameters are scaled and input into finite element software to establish a blasting block size model containing rock mass and explosives. The software's section selection function is used to count damaged and undamaged particles. The block mass and volume are calculated using the number of particles and the mass of a single particle. The cube root of the volume is used as the equivalent block size to quantify the block size. The mass of a single particle is measured, and the block size of incompletely damaged and adjacent completely damaged particles is classified and statistically analyzed. Remaining completely damaged loose particles are classified as less than 20mm. Based on the statistical results of blast pile particles under explosive consumption, the average fragmentation block size corresponding to the actual engineering consumption is predicted. Through targeted parameter acquisition and experimental data support, the model's foundation is ensured to closely resemble engineering reality. Parameter scaling modeling and particle quantization methods achieve accurate calculation and intuitive representation of block size. Classification statistics and correlation prediction with actual engineering provide a reliable basis for the correspondence between explosive consumption and block size. The combination of these three methods enhances the scientific rigor and accuracy of blasting block size analysis, provides precise guidance for optimizing engineering blasting schemes and selecting unit consumption, and strengthens the engineering practical value of simulation results.

[0120] This embodiment is based on a large open-pit mine. Static tests are conducted on samples taken from the blasting area to obtain lithological parameters. A blasting parameter table is provided using examples from engineering studies, and the dimensions of the experimental model are constructed. The prototype dimensions are calculated using similar material mix proportions, and the model dimensions are combined to provide a theoretical basis for subsequent model tests.

[0121] Particle flow was selected as the main algorithm for this invention from among many mainstream algorithms. This includes determining the layout of the main blast holes and the selection of the detonation delay (the inter-hole delay of the main blast holes is 3.4ms and the inter-row delay is 10ms). The blast hole diameter is designed to be 160mm, the hole spacing is 5.5m and the row spacing is 4m. In terms of explosives and detonators, two rows of main blast holes are selected in the establishment of the numerical model, taking into full consideration the experimental conditions and computational costs. The layout of pre-splitting holes and buffer holes is abandoned. The model is established according to the designed parameters. At the same time, in order to eliminate the influence of reflected stress waves caused by artificially truncated boundaries, except for the top and front surfaces which are free boundaries, all other surfaces are set with non-reflective boundaries.

[0122] When the single-hole charge was 17g, the solver showed a 45° tensile fracture along the xy plane, resulting in an L-shaped complete damage crack. The boundary conditions formed a connecting slip surface. It was found that when the single-hole charge was 5g, the model could withstand the stress wave and shock wave generated by the explosion well. The minimum resistance surface of the model was penetrated by the damage crack, and the edge of the blast cavity was continuous and regular.

[0123] After judging the blasting, the individual dispersed particles and connected particles are usually divided according to the space position, the particles are checked whether they are greater than the preset threshold, the rock mass center represents the undamaged blue and the rock mass edge represents the completely damaged red to judge the damage of the rock,

[0124] The SELPAR function is used to screen the explosive particles, only the rock particles are displayed, the number of particles in each block is counted, and the counted particles are marked;

[0125] The AREA in the MEASRE function in the LS-PREPOST software in the k file after modeling is used to count the damaged particles and the undamaged particles, the particle mass measured by the MEASRE function in the PREPOST software is 0.009175 kg, the particle number of each block is multiplied by the mass of a single particle to obtain the mass of the block, and the volume of the block can be calculated according to the density of concrete (2240 kg / m 3 ), and the equivalent length is usually used to represent the block degree, and the cubic root of the volume is used as the equivalent rock block degree under the assumption of a cubic block.

[0126] m 粒子 =ρ 粒子 V 粒子

[0127] In the formula, m 粒子 is the particle mass, ρ 粒子 is the density of concrete, and V 粒子 is the volume of the equivalent rock block degree.

[0128] According to the measurement of the mass of a single particle and the statistics of the rock block degree with the undamaged particles, the rock block degree represented by the adjacent completely damaged particles is counted, and the remaining completely damaged loose particles are considered as the block degree less than 20 mm. In this example, the number of particles under the unit consumption of 0.31 kg / m 3 is given.

[0129] Based on the gradient test method, a system screening is carried out on the target block degree interval, a plurality of comparative tests are carried out around the ±15% interval of the best adaptive explosive consumption (q value), and the explosive unit consumption of 0.23 kg / m 3 , 0.31 kg / m 3 , 0.39 kg / m 3 , 0.47 kg / m 3 , 0.55 kg / m 3 , 0.63 kg / m 3 , 0.71 kg / m 3 , 0.79 kg / m 3According to block size statistics, as the unit consumption increases, the proportion of small-sized rock blocks gradually fluctuates and increases, and the particle size distribution of the rock blocks is optimized and evenly distributed. By establishing a quantitative relationship model between the maximum block size and the unit consumption of explosives, and by using blasting block size screening and regression analysis, the optimized range of explosive unit consumption that meets different crushing requirements is determined.

[0130] The blasting block size model is divided into two types: the Rosin-Rammlar distribution function and the Gates-Gaudin-Schuman distribution function.

[0131] RR distribution function expression:

[0132] y i =1-exp(-(x) i / x0) n The GGS distribution function expression is as follows:

[0133] y i =(x i / x0) n

[0134] In the formula: y i For an equivalent length (block size) less than or equal to x i The cumulative mass ratio of rock blocks representing block size; x i x represents the rock block size at each level; x0 represents the maximum rock block size; n is the uniformity distribution parameter, the smaller the value, the more uniform the gradation.

[0135] Preferably, in this embodiment, the regression coefficient of the RR distribution function is relatively low, and R0 2 The coefficient of the GGS distribution function is 0.60, indicating a relatively high R value. 2 With a value of 0.95, the GGS distribution function in this example is more suitable for statistically analyzing the distribution of rock fragment size. Using geometric similarity ratio and material density similarity ratio, it can be quickly converted, predicting the unit consumption of explosives in actual engineering projects, and further predicting the average fragment size under the corresponding unit consumption. The prediction results are quite close to the average fragment size identified in the blast pile image scanned by actual CT scanning equipment, indicating that the statistical method and application of this invention based on particle flow for blasting rock fragment size has extremely high accuracy (see appendix for specific principles). Figure 6 Appendix Figure 7 Appendix Figure 8 Appendix Figure 9 Appendix Figure 10 and appendix Figure 11 ).

[0136] like Figure 12 As shown, this embodiment provides an embodiment of an electronic device 4, which includes a processor 41 and a memory 42 coupled to the processor 41.

[0137] The memory 42 stores program instructions for implementing the particle flow simulation based rock breaking block size statistics method of any of the above embodiments.

[0138] The processor 41 is configured to execute the program instructions stored in the memory 42 to perform the particle flow simulation based rock breaking block size statistics.

[0139] The processor 41 can also be referred to as a CPU (Central Processing Unit). The processor 41 can be an integrated circuit chip having a processing capability of signals. The processor 41 can also be a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0140] Further, Figure 13 For a structural diagram of the storage medium of an embodiment of the present application, the storage medium 5 of the embodiment of the present application stores program instructions 51 capable of implementing all the methods described above. The program instructions 51 can be stored in the storage medium in the form of a software product, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes a U disk, a mobile hard disk, a ROM (Read-Only Memory), a RAM (Random Access Memory), a magnetic disk or an optical disk, and various media capable of storing program codes, or a terminal device such as a computer, a server, a mobile phone, a tablet, etc.

[0141] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are merely schematic, for example, the division of units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or components shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0142] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit. The above is only an embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings, or directly or indirectly applied to other related technical fields, is also included in the patent protection scope of the present application.

[0143] The specific embodiments of the application have been described above, but they are only examples, and the application is not limited to the above-described specific embodiments. Any equivalent modification or substitution made to the application by those skilled in the art is also within the scope of the application, and therefore, equivalent transformations, modifications, improvements, etc. made without departing from the spirit and principle range of the application should be included in the scope of the application.

Claims

1. A rock breakage size distribution statistical method based on particle flow simulation, characterized in that, The rock fragmentation statistical method comprises the following steps: The blasting parameters and the static mechanical property parameters are proportionally scaled and input into the finite element analysis software to establish a blasting fragmentation model according to the proportion; the cross-section selection function of the finite element analysis software is used to count the damaged particles and the undamaged particles to obtain how many particles in each block after blasting; the particle number of each block is multiplied by the mass of a single particle to obtain the mass of the block, and the volume of the block is calculated according to the density of the concrete; the equivalent length is used to represent the block size, and the cube root of the volume is used as the equivalent rock block size.

2. The method of claim 1, wherein, The process of using the cube root of the volume as the equivalent rock block size comprises the following steps: The proportionally scaled blasting parameters and the static mechanical property parameters are placed into the finite element analysis software environment to construct a blasting fragmentation model containing the rock mass and explosive materials; after the simulation of the blasting process is completed, the state of all particles in the blasting fragmentation model is identified by means of the cross-section analysis function in the finite element analysis software to distinguish the undamaged particles and the damaged particles; For the damaged area, the damaged particle sets that are connected to each other and jointly constitute an independent fragment are identified according to the spatial topological correlation between the particles; each damaged particle set is defined as a particle aggregation unit, which represents a rock block formed after blasting; the total number of particles contained in each particle aggregation unit is counted, and the total number of particles is multiplied by the mass of a single particle calibrated in advance to obtain the total mass of the particle aggregation unit; then, the theoretical volume of the fragment is inversely calculated according to the known density of the rock mass material through the mass-density relationship; The volume of each fragment is subjected to cube root operation to convert it into a geometrically representative linear dimension, which is the equivalent rock block size of the fragment.

3. The method of claim 2, wherein, The process of identifying the damaged particle sets that are connected to each other and jointly constitute an independent fragment comprises the following steps: The spatial coordinate data of the damaged particles in the damaged area are processed to establish a spatial relationship criterion based on the proximity criterion to judge whether any two particles are directly related in space; The spatial relationship criterion is applied to compare all the damaged particles with each other; when any two particles satisfy the spatial relationship criterion, a virtual connection link is established between the two particles, indicating that the two particles belong to the same potential spatial aggregation; after all particle pairs are traversed, the virtual connection links link some or all of the damaged particles to each other to form a complex and discontinuous spatial connection network; The spatial connection network is analyzed to decompose it into a plurality of maximum connected sub-networks that are independent of each other and internally connected; all the particles in each maximum connected sub-network are related to each other through direct or indirect virtual connection links, and the maximum connected sub-network has no connection relationship with other parts of the spatial connection network; a macroscopic spatial connection network is deconstructed into a plurality of microscopic independent connected components.

4. The method of claim 3, wherein, The process of analyzing the spatial connection network comprises the following steps: A unified unvisited state flag is created for all the damaged particles in the spatial connection network to track the access state of each particle in subsequent processing; Select an unvisited particle as the starting point of the current exploration from the spatially connected network; start a local connectivity exploration process; search and mark all other particles that are directly or indirectly associated with the current starting point through all virtual connection links; all marked particles form a temporary particle group, and all particles in the temporary particle group are connected to each other and have no path to particles outside the group through virtual connection links; The temporary particle group is confirmed and recorded as an independent maximal connected subnetwork; at the same time, the access state of all particles in the maximal connected subnetwork is updated to visited; outside the marked temporary particle group, another unvisited particle is selected as a new starting point in the spatially connected network, and the local connectivity exploration and marking process is repeated to identify and record the next independent maximal connected subnetwork; This cycle is repeated to access and process each unvisited damaged particle in the spatially connected network, and each cycle starts with an unvisited particle as the starting point, and finally generates an independent maximal connected subnetwork; when there is no longer any unvisited damaged particle in the spatially connected network, the cycle terminates.

5. The method of claim 4, wherein, The process of starting a local connectivity exploration process includes the following steps: Create a dynamic list named current exploration sequence and add the starting point particle as the first element of the current exploration sequence; at the same time, create an empty set named temporary association set to temporarily store all discovered associated particles; Enter an iterative processing loop, in which, in each iteration, the particle at the front end of the current exploration sequence is taken out and called the current core particle; perform a key operation on the current core particle; Screen the obtained adjacent particles; all adjacent particles that meet the conditions are marked as newly discovered associated particles; The newly discovered associated particles are processed in two ways: all newly discovered associated particles are added to the temporary association set; the newly discovered associated particles are appended to the end of the current exploration sequence to become the current core particle to be processed in subsequent iterations; at the same time, the access state of the newly discovered associated particles is updated to visited; after completing the processing of all adjacent particles of the current core particle, the iteration ends; the processed current core particle in the current exploration sequence is removed, and the subsequent particles in the current exploration sequence are waiting to be processed.

6. The method of claim 5, wherein, The process of processing the newly discovered associated particles in two ways includes the following steps: Perform the first processing operation on the newly discovered associated particles: integrate the newly discovered associated particles into a container named temporary association set; and continue to exist throughout the local connectivity exploration process, gathering all associated particles traced back from the current starting point particle; Perform the second parallel processing operation: sequentially append the same batch of newly discovered associated particles to the tail of a dynamic list named current exploration sequence in the order in which they are discovered; the current exploration sequence plans the order of particles to be explored next; After two processes, the newly discovered associated particles are endowed as components of a temporary associated set and as members queued in the current probe sequence; the output of the updated temporary associated set containing more particles and the updated current probe sequence containing more particles to be probed.

7. The method of claim 6, wherein, The process of sequentially appending to the tail of a dynamic list named current probe sequence includes the following steps: Obtaining the inherent order of the newly discovered associated particles; when the current core particle queries its virtual connection link, the obtained adjacent particles form an initial, spatial query result-based native sequence; Creating a temporary ordered list named to-be-enqueued particle group, and placing the newly discovered associated particles in the to-be-enqueued particle group in their native sequence without any changes; the ordered list of the to-be-enqueued particle group is concatenated to the end of the existing content of the current probe sequence dynamic list; After the concatenation is completed, the to-be-enqueued particle group is dissolved, and its content has become part of the current probe sequence; the length of the current probe sequence is extended, and the newly added tail content provides new particle objects to be probed for the iteration process.

8. The particle flow simulation based rock breakage size distribution statistical method of claim 1, wherein, The blasting parameters of one set of blasting schemes in the engineering project are obtained, and the size of the blasting block size model is determined according to the blasting parameters; at the same time, different rock mass occurrences are sampled, and similar material mix proportions are used to cast test specimens of different rock types, and static mechanical test is performed to obtain the static mechanical performance parameters of the cast test specimens; The blasting parameters include main blast hole arrangement and initiation delay selection, blast hole diameter design, and explosive and detonator selection; the static mechanical performance parameters include density, uniaxial compressive strength, elastic modulus, and fracture toughness.

9. The particle flow simulation based rock breakage size distribution statistical method of claim 1, wherein, The mass of a single particle is measured, and the rock block size of the incomplete damage particle is counted; the rock block size represented by adjacent completely damaged particles is counted, and the remaining completely damaged loose particles are considered to have a block size less than 20mm; the statistical results of the number of particles in the blast pile under the specific explosive unit consumption are given; the average broken block size of the rock mass under the corresponding explosive unit consumption in the actual project is predicted.

10. A rock breaking lump size statistics system based on particle flow simulation, which is applied to the rock breaking lump size statistics method based on particle flow simulation according to any one of claims 1 to 9, characterized in that, The rock breaking block size statistical system based on particle flow simulation, comprising: An acquisition blasting parameter module is configured to obtain blasting parameters of one set of blasting schemes in an engineering project, and determine the size of a blasting block size model according to the blasting parameters; at the same time, different rock mass occurrences are sampled, and similar material mix proportions are used to cast test specimens of different rock types, and static mechanical test is performed to obtain the static mechanical performance parameters of the cast test specimens; An equivalent rock block size module is configured to scale the blasting parameters and the static mechanical performance parameters, and input them into a finite element analysis software, and establish a blasting block size model according to the scale; use the cross-section selection function of the finite element analysis software to count the damaged particles and the undamaged particles, and obtain how many particles in each block after blasting; multiply the number of particles in each block by the mass of a single particle to obtain the mass of the block, and calculate the volume of the block according to the density of the concrete; use the equivalent length to represent the block size, and use the cube root of the volume as the equivalent rock block size; The rock mass average broken block size module is used for measuring the mass of single particles and the statistical existence of rock block size of incomplete damage particles, the statistical rock block size represented by adjacent completely damaged particles, and the remaining completely damaged loose particles are regarded as block size less than 20 mm, and the statistical results of the number of blasted particles under the specific charge of explosives are given; the average broken block size of the rock mass under the corresponding specific charge of explosives in the actual engineering is predicted.

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