Blasting flying rock drop point distribution prediction method

Abstract

The invention discloses a blasting flying rock drop point distribution prediction method. The method comprises the steps that physical and mechanical parameters of on-site rocks are acquired; carrying out an on-site blasting test, and collecting actual drop point distribution data of flying rocks; establishing a finite element-discrete element coupling model, then carrying out blasting simulation calculation, and obtaining an initial speed, an initial direction and an initial coordinate of flying rocks; calculating a flying stone throwing distance, and drawing a flying stone drop point distribution diagram according to a calculation result; determining mesoscopic parameters of the finite element-discrete element coupling model through comparison verification; and applying the finite element-discrete element coupling model with the determined mesoscopic parameters to actual side slope rock blasting simulation, and drawing a flying rock drop point distribution map to predict the actual drop point of flying rock. According to the method, the influence of physical and mechanical parameters of rocks, blasting working condition parameters and model mesoscopic parameters on flying stone drop points is comprehensively considered, the accuracy of predicting the flying stone throwing distance through numerical blasting simulation is improved by correcting a ballistic formula, and the accurate mesoscopic parameters of the model are obtained through a contrast experiment; and the accuracy of predicting the falling point of the flying rocks by the model is improved.

Description

Technical Field

[0001] The invention relates to the technical field of blasting, and in particular to a method for predicting the falling point of blasting flying rocks. Background Art

[0002] In the process of excavating rocky highway slopes, blasting technology has been widely used as an efficient and economical construction method. However, blasting can also bring about flying rock hazards. Flying rock is one of the main hazards in the blasting process, which can easily lead to casualties, equipment damage and other production safety accidents. How to effectively predict the throwing distance of flying rocks and take corresponding flying rock control measures to reduce the hazards of flying rocks in blasting is one of the issues that should be paid special attention to in blasting construction.

[0003] The calculation formula for the safe distance of flying rocks in conventional blasting is r = 20 kn 2 w, where r represents the safe distance for flying rocks, k is a coefficient related to rock properties, topography, geology and meteorology, n is the explosive effect index of the largest explosive package, and w is the minimum resistance line of the largest explosive package.

[0004] However, conventional empirical formulas take into account limited factors and are not very accurate, and are unable to accurately predict the distribution of flying rocks falling points during blasting. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method for predicting the distribution of blasting flying rock falling points, so as to solve the technical problem that the accuracy of predicting the blasting flying rock falling points by using conventional empirical formulas is not high.

[0006] The method for predicting the distribution of blasting flying rocks falling points of the present invention comprises the following steps:

[0007] 1) Take samples of rocks at the blasting site and then test to obtain the physical and mechanical parameters of the rocks at the site.

[0008] 2) Conduct on-site blasting tests and collect data on the actual location of flying rocks;

[0009] 3) Based on the physical and mechanical parameters obtained in step 1), a finite element model of rock, blasthole blockage, explosives, and air is established using ANSYS / LSDYNA software; at the same time, a closed shell is established and discrete elements are generated to simulate blasting flying rocks, thereby obtaining a finite element-discrete element coupling model;

[0010] 4) Setting the blasting parameters that affect the distribution of flying rock drop points in the finite element-discrete element coupling model, and then performing blasting simulation calculations;

[0011] 5) Obtaining the initial velocity, initial direction and initial coordinates of the flying rocks according to the blasting simulation calculation;

[0012] 6) The ballistics formula is corrected by introducing the initial coordinates of the flying rock, and the following corrected formula is obtained:

[0013]

[0014] Among them: x0, y0 are the initial coordinates of the flying stone in the x and y directions; α is the throwing angle of the flying stone, v0 is the initial velocity of the flying stone, and H0-H is the elevation difference;

[0015] The flying stone throwing distance is calculated according to the above formula (1), and a flying stone landing point distribution map is drawn according to the calculation result;

[0016] 7) Determine the microscopic parameters of the finite element-discrete element coupling model through comparative verification:

[0017] The actual flying rock falling point distribution data collected in step 2) is used to verify the flying rock falling point distribution map drawn in step 6), and the mesoscopic parameters of the finite element-discrete element coupling model in step 3) are adjusted to reduce the error between the simulated flying rock falling point distribution and the actual falling point distribution to an acceptable range, thereby determining the mesoscopic parameters of the finite element-discrete element coupling model; the mesoscopic parameters include normal damping coefficient, tangential damping coefficient, static friction coefficient, rolling friction coefficient, normal stiffness coefficient, and ratio of normal stiffness to tangential stiffness;

[0018] 8) The finite element-discrete element coupling model after the microscopic parameters are determined is used for the actual slope rock blasting simulation. The physical and mechanical parameters and blasting condition parameters are set according to the actual situation. Then, the blasting simulation calculation is carried out and the flying rock falling point distribution map is drawn. Then, the actual falling point of the flying rocks is predicted based on the drawn flying rock falling point distribution map.

[0019] Furthermore, the physical and mechanical parameters in step 1) include elastic modulus, Poisson's ratio and shear modulus.

[0020] Furthermore, the blasting operating parameters described in step 4) include charge structure, uncoupling coefficient, resistance line and delay.

[0021] Beneficial effects of the present invention:

[0022] The method for predicting the distribution of flying rock landing points during blasting of the present invention simulates slope rock blasting by establishing a finite element-discrete element coupling model, and comprehensively considers the influence of the physical and mechanical parameters of the rock, the blasting condition parameters and the model microscopic parameters on the flying rock landing points, and improves the accuracy of the prediction of the flying rock throwing distance by correcting the ballistics formula, and obtains the accurate microscopic parameters of the model through comparative experiments, thereby comprehensively improving the accuracy of the prediction of the flying rock landing point distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Flow chart for blasting fly rock prediction;

[0024] Figure 2This is a blasting simulation diagram;

[0025] Figure 3 It is the blasting flying rock velocity-time curve diagram;

[0026] Figure 4 It is the coordinate-time curve diagram of blasting flying rocks;

[0027] Figure 5 The distribution map of flying rocks falling points obtained by numerical simulation;

[0028] Figure 6 This is the revised distribution map of flying rocks falling points. DETAILED DESCRIPTION

[0029] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0030] As shown in the figure, the method for predicting the distribution of blasting flying rocks in this embodiment includes the following steps:

[0031] 1) Take samples of the rocks at the blasting site, and then test to obtain the physical and mechanical parameters of the rocks at the site. Specifically, the physical and mechanical parameters include elastic modulus, Poisson's ratio, shear modulus, etc.

[0032] 2) Conduct on-site blasting tests and collect data on the actual landing points of flying rocks.

[0033] 3) Based on the physical and mechanical parameters obtained in step 1), a finite element model of rock, blasthole blockage, explosives, and air is established using ANSYS / LSDYNA software; at the same time, a closed shell is established and discrete elements are generated to simulate blasting flying rocks, thereby obtaining a finite element-discrete element coupling model.

[0034] 4) Set the blasting parameters that affect the distribution of flying rock drop points in the finite element-discrete element coupling model. The blasting parameters include charge structure, uncoupling coefficient, resistance line and delay, etc. Then perform blasting simulation calculation. Figure 2 shown.

[0035] 5) Obtain the initial speed, initial direction and initial coordinates of the flying rocks according to the blasting simulation calculation. The blasting flying rock speed-time curve is as follows: Figure 3 As shown in the figure, the coordinate-time curve of blasting flying rocks is as follows: Figure 4 shown.

[0036] 6) The ballistics formula is corrected by introducing the initial coordinates of the flying rock, and the following corrected formula is obtained:

[0037]

[0038] Among them: x0, y0 are the initial coordinates of the flying stone in the x and y directions; α is the throwing angle of the flying stone, v0 is the initial velocity of the flying stone, and H0-H is the elevation difference;

[0039] The flying stone throwing distance is calculated according to the above formula (1), and the flying stone landing point distribution map is drawn according to the calculation result. Figure 5 shown.

[0040] 7) Determine the microscopic parameters of the finite element-discrete element coupling model through comparative verification:

[0041] The actual flying rock falling point distribution data collected in step 2) is used to verify the flying rock falling point distribution map drawn in step 6), and the microscopic parameters of the finite element-discrete element coupling model in step 3) are adjusted to reduce the error between the simulated flying rock falling point distribution and the actual falling point distribution to an acceptable range, thereby determining the microscopic parameters of the finite element-discrete element coupling model; the microscopic parameters include the normal damping coefficient, the tangential damping coefficient, the static friction coefficient, the rolling friction coefficient, the normal stiffness coefficient, and the ratio of the normal stiffness to the tangential stiffness. The corrected flying rock falling point distribution map is shown in FIG. Figure 6 shown.

[0042] 8) The finite element-discrete element coupling model after the microscopic parameters are determined is used for the actual slope rock blasting simulation. The physical and mechanical parameters and blasting condition parameters are set according to the actual situation. Then, the blasting simulation calculation is carried out and the flying rock falling point distribution map is drawn. Then, the actual falling point of the flying rocks is predicted based on the drawn flying rock falling point distribution map.

[0043] According to the prediction results, real-time warnings are given for flying rocks that may fall into dangerous areas, and corresponding flying rock control measures are taken to reduce the hazards of flying rocks caused by blasting.

[0044] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for predicting the distribution of blasting flying rocks, characterized by: The following steps are involved: 1) Take samples of rocks at the blasting site and then test to obtain the physical and mechanical parameters of the rocks at the site. 2) Conduct on-site blasting tests and collect data on the actual location of flying rocks; 3) Based on the physical and mechanical parameters obtained in step 1), a finite element model of rock, blasthole blockage, explosives, and air is established using ANSYS / LSDYNA software; at the same time, a closed shell is established and discrete elements are generated to simulate blasting flying rocks, thereby obtaining a finite element-discrete element coupling model; 4) Setting the blasting parameters that affect the distribution of flying rock drop points in the finite element-discrete element coupling model, and then performing blasting simulation calculations; 5) Obtaining the initial velocity, initial direction and initial coordinates of the flying rocks according to the blasting simulation calculation; 6) The ballistics formula is corrected by introducing the initial coordinates of the flying rock, and the following corrected formula is obtained: Among them: x0, y0 are the initial coordinates of the flying stone in the x and y directions; α is the throwing angle of the flying stone, v0 is the initial velocity of the flying stone, and H0-H is the elevation difference; The flying stone throwing distance is calculated according to the above formula (1), and a flying stone landing point distribution map is drawn according to the calculation result; 7) Determine the microscopic parameters of the finite element-discrete element coupling model through comparative verification: The actual flying rock falling point distribution data collected in step 2) is used to verify the flying rock falling point distribution map drawn in step 6), and the mesoscopic parameters of the finite element-discrete element coupling model in step 3) are adjusted to reduce the error between the simulated flying rock falling point distribution and the actual falling point distribution to an acceptable range, thereby determining the mesoscopic parameters of the finite element-discrete element coupling model; the mesoscopic parameters include normal damping coefficient, tangential damping coefficient, static friction coefficient, rolling friction coefficient, normal stiffness coefficient, and ratio of normal stiffness to tangential stiffness; 8) The finite element-discrete element coupling model after the microscopic parameters are determined is used for the actual slope rock blasting simulation. The physical and mechanical parameters and blasting condition parameters are set according to the actual situation. Then, the blasting simulation calculation is carried out and the flying rock falling point distribution map is drawn. Then, the actual falling point of the flying rocks is predicted based on the drawn flying rock falling point distribution map.

2. The method for predicting the distribution of blasting flying rocks according to claim 1, characterized in that: The physical and mechanical parameters described in step 1) include elastic modulus, Poisson's ratio and shear modulus.

3. The method for predicting the distribution of blasting flying rocks according to claim 1, characterized in that: The blasting parameters described in step 4) include charge structure, uncoupling coefficient, resistance line and delay.

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