CN114091309A - Method and device for determining maintenance age of filling body based on numerical simulation - Google Patents
Method and device for determining maintenance age of filling body based on numerical simulation Download PDFInfo
- Publication number
- CN114091309A CN114091309A CN202111394252.3A CN202111394252A CN114091309A CN 114091309 A CN114091309 A CN 114091309A CN 202111394252 A CN202111394252 A CN 202111394252A CN 114091309 A CN114091309 A CN 114091309A
- Authority
- CN
- China
- Prior art keywords
- age
- blasting
- maintenance
- determining
- filling body
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012423 maintenance Methods 0.000 title claims abstract description 139
- 238000000034 method Methods 0.000 title claims abstract description 76
- 238000004088 simulation Methods 0.000 title claims abstract description 36
- 238000005422 blasting Methods 0.000 claims abstract description 147
- 230000008569 process Effects 0.000 claims abstract description 39
- 239000002360 explosive Substances 0.000 claims abstract description 34
- 230000001902 propagating effect Effects 0.000 claims abstract description 14
- 239000000945 filler Substances 0.000 claims description 51
- 230000003068 static effect Effects 0.000 claims description 28
- 230000006378 damage Effects 0.000 claims description 24
- 238000004590 computer program Methods 0.000 claims description 20
- 238000012545 processing Methods 0.000 claims description 10
- 230000008859 change Effects 0.000 claims description 9
- 238000003860 storage Methods 0.000 claims description 6
- 230000000644 propagated effect Effects 0.000 claims description 4
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 238000005065 mining Methods 0.000 abstract description 10
- 238000010586 diagram Methods 0.000 description 12
- 239000000463 material Substances 0.000 description 10
- 230000006870 function Effects 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 239000003086 colorant Substances 0.000 description 2
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000012530 fluid Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005312 nonlinear dynamic Methods 0.000 description 1
- 238000012856 packing Methods 0.000 description 1
- 238000003825 pressing Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Agronomy & Crop Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Marine Sciences & Fisheries (AREA)
- Animal Husbandry (AREA)
- General Health & Medical Sciences (AREA)
- Mining & Mineral Resources (AREA)
- Primary Health Care (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The embodiment of the application is suitable for the technical field of mining, and provides a method and a device for determining the maintenance age of a filling body based on numerical simulation, wherein the method comprises the following steps: acquiring blasting parameters, wherein the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in the ore and a filling body; simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting propagating in the filling body at each curing age; determining the dynamic tensile strength of said pack at each of said curing ages; and determining the optimal curing age of the filling body according to the peak strength and the dynamic tensile strength corresponding to each curing age. By adopting the method, the influence of deep hole blasting on the stability of the filling body can be simulated, the optimal curing age of the filling body is determined, the safety of the stoping operation is ensured, and the stoping efficiency is improved.
Description
Technical Field
The embodiment of the application belongs to the technical field of mining, and particularly relates to a method and a device for determining the curing age of a filling body based on numerical simulation.
Background
In the technical field of mining, a filling body is an integral body formed by filling materials into a goaf. In a stope of the filling mining method of upward stoping, the filling body can be used as a workbench; in a stope with downward stoping, the filling bodies may act as artificial roofs.
Deep hole blasting is one of the necessary steps in mining. Generally, there are many stopes for simultaneous mining, and deep hole blasting recovery may be simultaneously performed in a plurality of underground middle sections. After stoping, the goaf needs to be filled with filling materials to form a filling body. However, because of the heavy duty of the stope production, several days after curing, a new blasting operation is started near the stope. At this time, the strength of the filling body is very low, and the stability damage of the filling body of the stope caused by deep hole blasting is large. Therefore, the influence of the deep hole blasting on the chamber filling body is researched, and the method has important significance for ensuring the operation safety and improving the extraction efficiency.
Disclosure of Invention
In view of this, the embodiment of the present application provides a method and a device for determining a maintenance age of a filler based on numerical simulation, so as to simulate an influence of deep hole blasting on stability of the filler, determine an optimal maintenance age of the filler, ensure safety of a mining operation, and improve mining efficiency.
A first aspect of an embodiment of the present application provides a method for determining a maintenance age of a filler based on numerical simulation, including:
acquiring blasting parameters, wherein the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in the ore and a filling body;
simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting propagating in the filling body at each curing age;
determining the dynamic tensile strength of said pack at each of said curing ages;
and determining the optimal curing age of the filling body according to the peak strength and the dynamic tensile strength corresponding to each curing age.
Optionally, the simulating a blasting process based on the blasting parameters to obtain peak intensities of stress waves generated by blasting propagating inside the filler at various curing ages includes:
simulating a blasting process based on the blasting parameters respectively for each maintenance age of the filler;
acquiring a plurality of blasting cloud pictures generated by simulating the blasting process;
identifying from a plurality of the shot clouds a peak intensity of propagation of the stress wave within a fill at each age.
Optionally, said determining the dynamic tensile strength of said infill at each of said curing ages comprises:
determining the static tensile strength of said pack at each of said curing ages;
determining the dynamic tensile strength of the filling body in each maintenance age according to the static tensile strength; wherein, for any of said maintenance ages, said dynamic tensile strength is 4-8 times said static tensile strength.
Optionally, for any of the maintenance ages, the dynamic tensile strength is 8 times the static tensile strength.
Optionally, the determining an optimal curing age of the filler according to the peak strength and the dynamic tensile strength corresponding to each curing age includes:
aiming at each maintenance age, determining the damage depth of blasting to the filling body of each maintenance age according to the peak intensity and the dynamic tensile strength corresponding to the maintenance age;
and determining the optimal curing age of the filling body according to the failure depth.
Optionally, the determining an optimal curing age of the filling body according to the failure depth comprises:
determining a plurality of target maintenance ages of which the damage depth is smaller than a preset depth threshold from each maintenance age;
and determining the target maintenance age with the shortest time as the optimal maintenance age.
Optionally, the determining an optimal curing age of the filling body according to the failure depth comprises:
sequencing the maintenance ages according to the time sequence;
calculating a variation value of the damage depth between the maintenance ages;
and determining the maintenance age with longer time in the maintenance ages corresponding to the maximum change value as the optimal maintenance age.
A second aspect of an embodiment of the present application provides a filler maintenance age determination device based on numerical simulation, including:
the system comprises a blasting parameter acquisition module, a data processing module and a data processing module, wherein the blasting parameter acquisition module is used for acquiring blasting parameters, and the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in ores and a filling body;
the blasting process simulation module is used for simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting and propagated in the filling body at each curing age;
the tensile strength determining module is used for determining the dynamic tensile strength of the filling body at each maintenance age;
and the maintenance age determining module is used for determining the optimal maintenance age of the filling body according to the peak intensity and the dynamic tensile strength corresponding to each maintenance age.
A third aspect of embodiments of the present application provides a computing device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the method for determining the maintenance age of a filler based on numerical simulation as defined in any one of the above first aspects when executing the computer program.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium storing a computer program, which when executed by a processor, implements the method for determining a maintenance age of a filler based on numerical simulation of any one of the first aspect described above.
A fifth aspect of embodiments of the present application provides a computer program product, which, when run on a computer, causes the computer to execute the method for determining a maintenance age of a filler based on numerical simulation of any one of the first aspects.
Compared with the prior art, the embodiment of the application has the following advantages:
according to the embodiment of the application, the blasting process can be simulated based on the blasting parameters by acquiring the blasting parameters, and the peak intensity of the stress wave generated by blasting and propagated inside the filler in each curing age is obtained, so that after the dynamic tensile strength of the filler in each curing age is determined, the optimal curing age of the filler can be determined according to the peak intensity and the dynamic tensile strength corresponding to each curing age. According to the embodiment of the application, the optimal maintenance age of the filling body is determined by simulating the influence of deep hole blasting on the stability of the filling body, the safety of the stoping operation is guaranteed, and the stoping efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the embodiments or the description of the prior art will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic flow chart illustrating steps of a method for determining a maintenance age of a filler based on numerical simulation according to an embodiment of the present application;
FIG. 2 is a schematic illustration of an edge hole spacing according to an embodiment of the present application;
fig. 3 is a schematic diagram of one possible implementation manner of step S102 in a method for determining a curing age of a filler based on numerical simulation according to an embodiment of the present application;
fig. 4 is a schematic diagram of one possible implementation manner of step S103 in a method for determining a maintenance age of a filler based on numerical simulation according to an embodiment of the present application;
FIG. 5 is a schematic illustration of the dynamic tensile strength change of a filling body according to an embodiment of the present application;
fig. 6 is a schematic diagram illustrating a possible implementation manner of step S104 in a method for determining a curing age of a filler based on numerical simulation according to an embodiment of the present application;
FIG. 7 is a schematic illustration of the depth of failure of an obturator according to an embodiment of the present application;
fig. 8 is a schematic diagram of one possible implementation manner of step S1042 in a method for determining a maintenance age of a filler based on numerical simulation according to an embodiment of the present application;
FIG. 9 is a graphical illustration of a relationship between depth of failure and age according to an embodiment of the present application;
FIG. 10 is a schematic diagram of a pack maintenance age determination apparatus based on numerical simulation according to an embodiment of the present application;
FIG. 11 is a block diagram of a computing device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
The technical solution of the present application will be described below by way of specific examples.
Referring to fig. 1, a schematic flowchart illustrating steps of a method for determining a maintenance age of a filler based on numerical simulation according to an embodiment of the present application is shown, which may specifically include the following steps:
s101, obtaining blasting parameters, wherein the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in ores and a filling body.
It should be noted that the method may be applied to a computing device, that is, an execution subject of the embodiment of the present application is a computing device, and the computing device may be an electronic device such as a notebook computer or a desktop computer, and the embodiment of the present application does not limit the type of the computing device.
In the present embodiment, the blasting parameters may be the same as the actual blasting parameters planned for blasting operations in the mine. The blasting parameters should include at least the velocity of the explosive blast, the diameter of the explosive, the distance between the holes, etc. The side hole distance refers to the distance between the position where the explosive is placed in the ore and the filling body during blasting operation, and the distance can be a vertical distance generally. Generally, the explosives used in blasting operations comprise a plurality of explosives, and the side hole spacing of the plurality of explosives is generally the same during a single blast.
Illustratively, the explosive blast velocity is 3500 m/s and the explosive diameter is 90 mm. Fig. 2 is a schematic diagram of an edge hole pitch according to an embodiment of the present application. Fig. 2 shows an ore 21 and a filling body 22, wherein three explosive charges 211 are placed in the ore 21, and the vertical distance between the explosive charges 211 and the filling body 22 is the side hole distance L. The edge-to-hole spacing L shown in fig. 2 is 0.5 meters.
And S102, simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting propagating in the filling body at each curing age.
In the embodiment of the application, the blasting process can be simulated by adopting an explicit nonlinear dynamic analysis general finite element program LS-DYNA. The LS-DYNA program is a highly nonlinear transient dynamic analysis program, can solve the large deformation dynamic responses of high-speed collision, explosion, mould pressing and the like of various two-dimensional and three-dimensional inelastic structures, and can solve the problems of heat transfer, fluid and fluid-solid coupling and the like. The LS-DYNA program has rich material models, provides over 140 models of metallic and non-metallic materials for users to choose from, and allows users to customize material models. The LS-DYNA program package also comprises more than 16 unit types, and various units can be selected by various theoretical algorithms and have large displacement, large strain and large rotation performance.
In the embodiment of the application, the LS-DYNA program can be pre-installed in the computing device. After the computing device obtains the blasting parameters, the LS-DYNA program can be called to simulate the blasting process.
Alternatively, the LS-DYNA program may be installed in other electronic devices that are capable of communicating with the computing device. After the computing device obtains the blasting parameters, the blasting parameters can be sent to the electronic device based on communication connection with other electronic devices, and the electronic device is instructed to simulate the blasting process according to the received blasting parameters. Information obtained by simulating the blast may be transmitted back to the computing device for processing.
In the embodiment of the application, the LS-DYNA program is adopted to simulate the blasting process, so that information including the peak intensity of stress waves generated by blasting and propagating in the filling body can be obtained. This stress wave, i.e. due to the blasting, will have an influence on the stability of the filling body. Because the mechanical properties of the filling bodies in different curing ages are different, the influence of stress waves generated by the same type of blasting on the filling bodies is also different. Therefore, blasting simulation can be respectively carried out on the fillers in each maintenance age, and information about propagation of stress waves generated by blasting in the fillers in each maintenance age can be obtained.
Illustratively, the maintenance ages may be set to 3 days, 5 days, 7 days, 10 days, 15 days, 25 days, 28 days, etc., respectively, in combination with the practice.
In a possible implementation manner of the embodiment of the present application, as shown in fig. 3, the process of simulating a blasting process based on blasting parameters to obtain peak intensity of stress waves generated by blasting propagating inside a filler at each curing age may include the following sub-steps S1021 to S1023:
and S1021, simulating a blasting process based on the blasting parameters respectively for each maintenance age of the filler.
And S1022, acquiring a plurality of blasting cloud pictures generated by simulating the blasting process.
And S1023, identifying the peak intensity of the stress wave propagating inside the filling body at each maintenance age from a plurality of blasting cloud charts.
In a specific implementation, the blasting process may be simulated separately for each curing age of the pack. For example, for fillers with a curing age of 3 days, 5 days, 7 days, 10 days, 15 days, 25 days, 28 days, etc., a blasting process is simulated.
After the LS-DYNA program simulates blasting, the LS-DYNA program outputs a corresponding blasting cloud picture. The computing device may obtain information related to each blast by processing the blast cloud map. In this way, the computing device may obtain information that the stress wave generated by the blast propagates inside the pack at maintenance ages of 3 days, 5 days, 7 days, 10 days, 15 days, 25 days, 28 days, etc. This information may include the peak intensity of the propagation of the stress wave, i.e. the intensity maximum of the stress wave.
Generally, the intensity of the stress wave propagating inside the filling body can be represented by different colors in a blasting cloud graph output by an LS-DYNA program. The computing device may determine the peak intensity of stress wave propagation based on the magnitudes of the stress wave intensities represented by the different colors.
S103, determining the dynamic tensile strength of the filling body at each maintenance age.
In the present embodiment, the dynamic tensile strength can be used to analyze whether the structure of the filling body is damaged. Generally, if the peak strength of the stress wave propagating inside the filling body is greater than or equal to the dynamic tensile strength of the filling body, it means that the filling body will deform under the action of the stress wave, resulting in the structural failure of the filling body. If the peak strength of the propagation of the stress wave inside the filling body is smaller than the dynamic tensile strength of the filling body, it means that the filling body can withstand the stress wave of the peak strength, and the filling body will not be structurally damaged by the propagation of the stress wave.
Generally, the dynamic tensile strength of the pack varies from one curing age to another. Generally, as the age of the pack increases, the dynamic tensile strength of the pack increases accordingly. Illustratively, a pack of 28 days of curing age has a dynamic tensile strength that is greater than the dynamic tensile strength of a pack of 20 days of curing age.
In one possible implementation manner of the embodiment of the present application, as shown in fig. 4, determining the dynamic tensile strength of the filler at each curing age may include the following sub-steps S1031 to S1032:
and S1031, measuring the static tensile strength of the filling body at each curing age.
And S1032, determining the dynamic tensile strength of the filling body in each curing age according to the static tensile strength.
In general, the dynamic tensile strength of the filling body is not easily obtained directly, but by means of experiments, the static tensile strength of the filling body can be obtained. Since the dynamic tensile strength of the material and the static tensile strength often have a certain numerical relationship, the dynamic tensile strength of the material can be indirectly determined by measuring the static tensile strength of the filling body.
In the examples of the present application, a mechanical test may be performed in advance depending on the type of material used for the filler, and the static tensile strength when the material is used as the filler may be measured.
In specific implementation, mechanical tests can be respectively performed on the fillers in each curing age to obtain the static tensile strength of the fillers in each curing age. For example, the filling body can be formed by first using the filling material actually used for filling the mine empty area, and after curing the filling body for 3 days, the static tensile strength of the filling body formed by the material at the curing age of 3 days can be measured through a mechanical test. For other times of the curing age, the static tensile strength of the pack may also be calculated in a similar manner as described above.
The dynamic tensile strength of the pack at each curing age may then be determined based on the relationship between the dynamic tensile strength and the static tensile strength. Typically, the dynamic tensile strength is 4-8 times the static tensile strength for any curing age. For example, the dynamic tensile strength of the pack in the 3-day curing age is 4 to 8 times the static tensile strength of the pack in the 3-day curing age; the dynamic tensile strength of the filling body in the 7-day curing age is 4-8 times of the static tensile strength of the filling body in the 7-day curing age.
In one possible implementation of the embodiments of the present application, for any one of the maintenance ages, the subsequent processing may be performed with a dynamic tensile strength 8 times the static tensile strength. For example, after the static tensile strength of the filling body of each curing age is measured by a mechanical test, a value 8 times the static tensile strength can be taken as the dynamic tensile strength corresponding to the filling body of the curing age.
Fig. 5 is a schematic diagram illustrating a change in dynamic tensile strength of a filling according to an embodiment of the present application. The dynamic tensile strength of the pack for the curing ages of 3 days, 5 days, 7 days, 10 days, 15 days, 20 days, 25 days, and 28 days in this order is shown in fig. 5. Wherein, for a certain filling body shown in figure 5, the dynamic tensile strength is 0.5MPa at the curing age of 3 days; the dynamic tensile strength is 2.4MPa at the curing age of 28 days.
And S104, determining the optimal curing age of the filler according to the peak strength and the dynamic tensile strength corresponding to each curing age.
In the present embodiment, the filler structure may be considered to be broken when the peak strength of the stress wave as it propagates inside the filler is greater than the dynamic tensile strength of the filler. Thus, the optimal maintenance age of the pack may be determined based on the particular degree to which the pack is damaged. For example, a relatively light failure level pack may be identified, and the maintenance age corresponding to the blasting process that caused the failure may then be determined as the optimal maintenance age.
In one possible implementation manner of the embodiment of the present application, as shown in fig. 6, determining the optimal curing age of the filling body according to the peak strength and the dynamic tensile strength corresponding to each curing age may include the following sub-steps S1041 to S1042:
and S1041, determining the damage depth of blasting to the filling body of each curing age according to the peak intensity and the dynamic tensile strength corresponding to the curing age for each curing age.
S1042, determining the optimal curing age of the filling body according to the damage depth.
As mentioned above, the blasting cloud chart output by the LS-DYNA program after the simulated blasting can represent the intensity of the stress wave propagating in the filling body, and the depth of damage of the blasting process to the filling body of each curing age can be determined from the blasting cloud chart by combining the dynamic tensile strength of the filling body of each curing age determined in the previous steps. The optimal curing age for the pack may then be determined based on the depth of failure.
Illustratively, the LS-DYNA program outputs a shot cloud including the stress wave intensity at each location of the pack after the simulated shot, for example, at a 3-day curing age. According to the magnitude relation between the peak intensity of the stress wave and the dynamic tensile strength, whether the blasting damages the filling body can be determined. If a failure is caused, the failure depth due to the failure can be determined from the intensity of the stress wave at each position. Fig. 7 is a schematic view of the depth of fracture of a filling body according to an embodiment of the present application. Fig. 7 shows the depth of failure of a 3-day curing age pack under the stress wave generated by blasting, which is 1.16 m.
In one possible implementation manner of the embodiment of the present application, when determining the optimal maintenance age of a filler according to a failure depth, a plurality of target maintenance ages with failure depths smaller than a preset depth threshold may be determined from the respective maintenance ages, and then the target maintenance age with the shortest time may be determined as the optimal maintenance age of the filler.
As shown in table one, the example of the failure depth of the filling body of different curing ages under the effect of the stress wave generated by blasting is provided in the embodiment of the present application:
table one:
| maintenance age (Tian) | 3 | 5 | 7 | 10 | 15 | 20 | 25 | 28 |
| Depth of destruction (rice) | 1.16 | 0.78 | 0.60 | 0.54 | 0.46 | 0.42 | 0.38 | 0.36 |
If the preset depth threshold is 0.7 m, the target curing ages include 7 days, 10 days, 15 days, 20 days, 25 days and 28 days for the failure depth shown in table one, and the failure depth of the filling body at each curing age is less than the preset depth threshold of 0.7 m.
Although at longer curing ages the depth of failure of the pack is less, a longer curing age also means longer waiting times for the actual blasting operation in the mine, which can adversely affect ore mining. Therefore, after a plurality of target maintenance ages are determined based on the preset depth threshold, the target maintenance age with the shortest time may be determined as the optimal maintenance age. For example, in the above example, the shortest one of the target care ages is 7 days, and the time of 7 days may be the optimal care age. Therefore, the damage of the blasting operation to the filling body can be guaranteed within an acceptable range, and the smooth operation of the mining operation can also be guaranteed.
In one possible implementation of the embodiment of the present application, as shown in fig. 8, determining the optimal curing age of the pack according to the depth of failure may include the following sub-steps S141 to S143:
and S141, sequencing the maintenance ages according to the time sequence.
And S142, calculating the change value of the damage depth among the maintenance ages.
And S143, determining the maintenance age with longer time in the maintenance ages corresponding to the maximum change value as the optimal maintenance age.
In the embodiment of the present application, the maintenance ages are sorted according to the time sequence, and the maintenance ages may be sorted from short to long according to the time sequence. For example, for each of the maintenance ages shown in table one, they may be ranked in the order of 3 days, 5 days, 7 days, 10 days, 15 days, 20 days, 25 days to 28 days.
Then, a variation value of the damage depth between the maintenance ages may be calculated, respectively, and the variation value may be used to indicate whether the variation of the damage depth is significant at any two maintenance ages.
In the embodiment of the present application, for the maintenance age and the destruction depth thereof shown in table one, a schematic diagram of the relationship between the destruction depth and the maintenance age as shown in fig. 9 can be plotted. In fig. 9, the abscissa indicates the age and the ordinate indicates the depth of destruction. Calculating the variation in failure depth between maintenance ages may be viewed as identifying the slope of the line between the failure depths of the fill between maintenance ages in the schematic diagram of failure depth versus maintenance age shown in fig. 9.
In the embodiment of the present application, a maintenance age with a longer time among maintenance ages corresponding to the maximum variation value may be determined as the optimal maintenance age.
As can be seen from fig. 9, the change in the destruction depth is most significant in the curing age corresponding to the maximum change value, that is, in the process of increasing from the 3-day curing age to the 7-day curing age in fig. 9. Therefore, it is possible to increase the maintenance age, which is longer in time among the 3-day maintenance age, the 5-day maintenance age, and the 7-day maintenance age included in the process of increasing from the 3-day maintenance age to the 7-day maintenance age, that is, the 7-day maintenance age, as the optimal maintenance age for the pack.
According to the embodiment of the application, numerical simulation research is carried out on the relation between the maintenance age of the filling body and the damage depth of the filling body by researching the influence rule of the simulation blasting operation on the stability of the filling body. The results show that the failure depth of the filling body is closely related to the maintenance age, the failure depth of the filling body is gradually reduced along with the increase of the maintenance age, and after a certain period of maintenance age (for example, 7 days), the failure depth of the filling body is obviously weakened by the blasting disturbance. Thus, the above-mentioned time (7 days) can be regarded as the optimum curing age.
In the embodiment of the application, the blasting process can be simulated based on the blasting parameters by obtaining the blasting parameters, so that the peak strength of the stress wave generated by blasting propagating inside the filler in each curing age is obtained, and after the dynamic tensile strength of the filler in each curing age is determined, the optimal curing age of the filler can be determined according to the peak strength and the dynamic tensile strength corresponding to each curing age. According to the embodiment of the application, the influence of deep hole blasting on the stability of the filling body is simulated, the optimal curing age of the filling body is determined, the safety of the stoping operation is guaranteed, and the stoping efficiency is improved.
Referring to fig. 10, a schematic diagram of a filling body maintenance age determining apparatus based on numerical simulation according to an embodiment of the present application is shown, and may specifically include a blasting parameter obtaining module, a blasting process simulation module, a tensile strength determining module, and a maintenance age determining module, where:
a blasting parameter obtaining module 1001, configured to obtain blasting parameters, where the blasting parameters include a blasting speed of an explosive, a diameter of the explosive, and a side hole distance, and the side hole distance is a distance between a position of the explosive in an ore and a filler;
a blasting process simulation module 1002, configured to simulate a blasting process based on the blasting parameters, to obtain peak intensities of stress waves generated by blasting propagating inside the packing at each curing age;
a tensile strength determination module 1003, configured to determine a dynamic tensile strength of the filling body at each of the curing ages;
and a maintenance age determining module 1004, configured to determine an optimal maintenance age of the filler according to the peak strength and the dynamic tensile strength corresponding to each maintenance age.
In this embodiment, the blasting process simulation module 1002 may be specifically configured to: simulating a blasting process based on the blasting parameters respectively for each maintenance age of the filler; acquiring a plurality of blasting cloud pictures generated by simulating the blasting process; identifying from a plurality of the shot clouds a peak intensity of propagation of the stress wave within a fill at each age.
In this embodiment, the tensile strength determining module 1003 may be specifically configured to: determining the static tensile strength of said pack at each of said curing ages; determining the dynamic tensile strength of the filling body in each maintenance age according to the static tensile strength; wherein, for any of said maintenance ages, said dynamic tensile strength is 4-8 times said static tensile strength.
In the examples herein, the dynamic tensile strength is 8 times the static tensile strength for any of the maintenance ages.
In this embodiment of the present application, the maintenance age determining module 1004 may be specifically configured to: for each curing age, determining the damage depth of blasting to a filling body of each curing age according to the peak intensity and the dynamic tensile strength corresponding to the curing age; and determining the optimal curing age of the filling body according to the failure depth.
In a possible implementation manner of the embodiment of the present application, the maintenance age determining module 1004 may further be configured to: determining a plurality of target maintenance ages of which the damage depth is smaller than a preset depth threshold from each maintenance age; and determining the target maintenance age with the shortest time as the optimal maintenance age.
In another possible implementation manner of the embodiment of the present application, the maintenance age determining module 1004 may be further configured to: sequencing the maintenance ages according to the time sequence; calculating a variation value of the damage depth between the maintenance ages; and determining the maintenance age with longer time in the maintenance ages corresponding to the maximum change value as the optimal maintenance age.
For the apparatus embodiment, since it is substantially similar to the method embodiment, it is described relatively simply, and reference may be made to the description of the method embodiment section for relevant points.
Referring to FIG. 11, a schematic diagram of a computing device of one embodiment of the present application is shown. As shown in fig. 11, the computing device 1100 of the present embodiment includes: a processor 1110, a memory 1120, and computer programs 1121 stored in the memory 1120 and operable on the processor 1110. The processor 1110, when executing the computer program 1121, implements the steps of the above-described method for determining the maintenance age of a filler based on numerical simulation, such as the steps S101 to S104 shown in fig. 1. Alternatively, the processor 1110, when executing the computer program 1121, implements the functions of each module/unit in each device embodiment described above, for example, the functions of the modules 1001 to 1004 shown in fig. 10.
Illustratively, the computer programs 1121 can be divided into one or more modules/units that are stored in the memory 1120 and executed by the processor 1110 to accomplish the present application. The one or more modules/units can be a series of computer program instruction segments capable of performing specific functions, which can be used to describe the execution of the computer program 1121 in the computing device 1100. For example, the computer program 1121 may be divided into a blasting parameter obtaining module, a blasting process simulation module, a tensile strength determination module, and a maintenance age determination module, and the specific functions of each module are as follows:
the system comprises a blasting parameter acquisition module, a data processing module and a data processing module, wherein the blasting parameter acquisition module is used for acquiring blasting parameters, and the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in ores and a filling body;
the blasting process simulation module is used for simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting and propagated in the filling body at each curing age;
the tensile strength determining module is used for determining the dynamic tensile strength of the filling body at each maintenance age;
and the maintenance age determining module is used for determining the optimal maintenance age of the filling body according to the peak intensity and the dynamic tensile strength corresponding to each maintenance age.
The computing device 1100 may be a desktop computer, a cloud server, or the like. The computing device 1100 may include, but is not limited to, a processor 1110, a memory 1120. Those skilled in the art will appreciate that fig. 11 is only one example of a computing device 1100 and is not intended to be limiting and that computing device 1100 may include more or less components than those shown, or some of the components may be combined, or different components, e.g., computing device 1100 may also include input output devices, network access devices, buses, etc.
The Processor 1110 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 1120 may be an internal storage unit of the computing device 1100, such as a hard disk or a memory of the computing device 1100. The memory 1120 may also be an external storage device of the computing device 1100, such as a plug-in hard drive provided on the computing device 1100, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and so forth. Further, the memory 1120 may also include both internal and external storage for the computing device 1100. The memory 1120 is used to store the computer programs 1121 and other programs and data required by the computing device 1100. The memory 1120 may also be used to temporarily store data that has been output or is to be output.
The embodiment of the application also discloses a computing device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the method for determining the maintenance age of the filler based on the numerical simulation according to the various embodiments.
The embodiment of the application also discloses a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the method for determining the maintenance age of the filler based on the numerical simulation according to the previous embodiments.
The embodiment of the application also discloses a computer program product, which when running on a computer, causes the computing device to execute the method for determining the maintenance age of the filler based on the numerical simulation described in the foregoing embodiments.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present application, and they should be construed as being included in the present application.
Claims (10)
1. A method for determining the maintenance age of a filler based on numerical simulation is characterized by comprising the following steps:
obtaining blasting parameters, wherein the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in ores and a filling body;
simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting propagating in the filling body at each curing age;
determining the dynamic tensile strength of said pack at each of said curing ages;
and determining the optimal curing age of the filling body according to the peak strength and the dynamic tensile strength corresponding to each curing age.
2. The method according to claim 1, wherein said simulating a blasting process based on said blasting parameters to obtain peak intensities of stress waves generated by the blasting propagating within the pack at various curing ages comprises:
simulating a blasting process based on the blasting parameters respectively for each maintenance age of the filler;
acquiring a plurality of blasting cloud pictures generated by simulating the blasting process;
identifying from a plurality of the shot clouds a peak intensity of propagation of the stress wave within a fill at each age.
3. The method according to claim 1 or 2, wherein said determining the dynamic tensile strength of said filling body at each of said curing ages comprises:
determining the static tensile strength of said pack at each of said curing ages;
determining the dynamic tensile strength of the filling body in each maintenance age according to the static tensile strength; wherein, for any of said maintenance ages, said dynamic tensile strength is 4-8 times said static tensile strength.
4. The method of claim 3, wherein said dynamic tensile strength is 8 times said static tensile strength for any of said maintenance ages.
5. The method according to any one of claims 1, 2 or 4, wherein said determining an optimal curing age of said filling body according to peak strengths and dynamic tensile strengths corresponding to each of said curing ages comprises:
for each curing age, determining the damage depth of blasting to a filling body of each curing age according to the peak intensity and the dynamic tensile strength corresponding to the curing age;
and determining the optimal curing age of the filling body according to the failure depth.
6. The method of claim 5, wherein said determining an optimal maintenance age for said pack based on said depth of failure comprises:
determining a plurality of target maintenance ages of which the damage depth is smaller than a preset depth threshold from each maintenance age;
and determining the target maintenance age with the shortest time as the optimal maintenance age.
7. The method of claim 5, wherein said determining an optimal maintenance age for said pack based on said depth of failure comprises:
sequencing the maintenance ages according to the time sequence;
calculating a variation value of the damage depth between the maintenance ages;
and determining the maintenance age with longer time in the maintenance ages corresponding to the maximum change value as the optimal maintenance age.
8. A filler maintenance age determination device based on numerical simulation, characterized by comprising:
the system comprises a blasting parameter acquisition module, a data processing module and a data processing module, wherein the blasting parameter acquisition module is used for acquiring blasting parameters, and the blasting parameters comprise blasting speed of explosives, diameter of the explosives and side hole distance, and the side hole distance is the distance between the position of the explosives in ores and a filling body;
the blasting process simulation module is used for simulating a blasting process based on the blasting parameters to obtain the peak intensity of stress waves generated by blasting and propagated in the filling body at each curing age;
the tensile strength determining module is used for determining the dynamic tensile strength of the filling body at each maintenance age;
and the maintenance age determining module is used for determining the optimal maintenance age of the filling body according to the peak intensity and the dynamic tensile strength corresponding to each maintenance age.
9. A computing device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements a method for determining a maintenance age of a filler based on numerical simulation according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out a method for determining a maintenance age of a filler based on numerical simulation according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111394252.3A CN114091309A (en) | 2021-11-23 | 2021-11-23 | Method and device for determining maintenance age of filling body based on numerical simulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111394252.3A CN114091309A (en) | 2021-11-23 | 2021-11-23 | Method and device for determining maintenance age of filling body based on numerical simulation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114091309A true CN114091309A (en) | 2022-02-25 |
Family
ID=80303242
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111394252.3A Pending CN114091309A (en) | 2021-11-23 | 2021-11-23 | Method and device for determining maintenance age of filling body based on numerical simulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114091309A (en) |
-
2021
- 2021-11-23 CN CN202111394252.3A patent/CN114091309A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Fukuda et al. | Development of a GPGPU‐parallelized hybrid finite‐discrete element method for modeling rock fracture | |
| Vakili et al. | A new cavability assessment criterion for longwall top coal caving | |
| Karekal et al. | Application of a mesh-free continuum method for simulation of rock caving processes | |
| CN109975119B (en) | Rock double-shaft compression blasting design method | |
| GB2563241A (en) | Hydraulic fracturing simulation | |
| Walton | Improving continuum models for excavations in rockmasses under high stress through an enhanced understanding of post-yield dilatancy | |
| CN114543603B (en) | Determination method and device for mine blasting edge hole distance | |
| Himanshu et al. | Explicit dynamics based numerical simulation approach for assessment of impact of relief hole on blast induced deformation pattern in an underground face blast | |
| CN115325893A (en) | Tunnel blasting expanding excavation construction method and system | |
| Wu et al. | Development of a finite-discrete element method with finite-strain elasto-plasticity and cohesive zone models for simulating the dynamic fracture of rocks | |
| CN105164552B (en) | The method for analyzing seismic data | |
| CN114091309A (en) | Method and device for determining maintenance age of filling body based on numerical simulation | |
| Li et al. | Research on mining-induced deformation and stress, insights from physical modeling and theoretical analysis | |
| Jia et al. | Study of the influencing factors of the liquid CO2 phase change fracturing effect in coal seams | |
| Berisavljević et al. | Development and application of methodology for quantification of overbreaks in hard rock tunnel construction | |
| CN116187122A (en) | Method and device for arranging blast holes, terminal equipment and medium | |
| CN117057110A (en) | Construction method of P-wave induced elliptic tunnel surrounding rock dynamic stress concentration coefficient calculation model | |
| CN115310686A (en) | Method, device, equipment and medium for predicting blasting qualified rate of strip mine | |
| Zhang et al. | Study on the crack propagation behaviour of eccentric uncoupled blasting in a deep-level rock mass | |
| Chen et al. | Modeling progressive damage and failure of rock under continuous cyclic loading considering strength degradation of mesoscopic finite elements | |
| Lei et al. | Spatio-temporal evolution of acoustic emission events and initiation of stress fields in the fracturing of rock mass around a roadway under cyclic high-stress loading | |
| CN114239339A (en) | Method and device for determining mine blasting edge hole distance and computing equipment | |
| CN112446151B (en) | Explicit dynamic ground stress initialization method, system, medium and computer equipment | |
| CN116086263A (en) | Proportioning method, device and equipment for tailing disposal empty yard | |
| CN112100796A (en) | Drilling track determination method and device for preventing casing in shale gas well from being damaged |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |