CN115311410A - Asphalt mixture three-dimensional discrete element model construction method, storage medium and equipment - Google Patents
Asphalt mixture three-dimensional discrete element model construction method, storage medium and equipment Download PDFInfo
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Abstract
A method, a storage medium and equipment for constructing a three-dimensional discrete element model of an asphalt mixture belong to the technical field of digitized design of the asphalt mixture. In order to solve the problem that the existing asphalt mixture three-dimensional discrete element model construction method cannot give consideration to both accuracy and high efficiency, the invention acquires a slice image of the asphalt mixture based on industrial CT, and utilizes a digital image processing technology to identify, extract and segment aggregate components; then, carrying out three-dimensional reconstruction on the aggregate particle model, deriving a surface grid model of the individual aggregate, and creating an aggregate particle model template library by using software; then, constructing a skeleton structure of a specified grading type through a random generation algorithm; filling ball particle simulation asphalt mortar among the aggregate particles, and randomly deleting a specified number of ball simulation gaps according to the void ratio; and finally, giving corresponding microscopic contact parameters to the model to simulate the mechanical behavior of the asphalt mixture, and realizing the construction of the three-dimensional discrete element model by taking the peak load error rate as an index for evaluating the accuracy of the discrete element model.
Description
Technical Field
The invention belongs to the technical field of asphalt mixture digital design, and particularly relates to an asphalt mixture three-dimensional discrete element model construction method, a storage medium and equipment.
Background
In terms of structural material composition, the asphalt mixture is a multiphase composite material which is composed of aggregates, asphalt and fillers and has gaps inside, and has obvious non-homogeneous anisotropy, particle properties and nonlinear characteristics. The mechanical property difference among different components causes uneven transmission distribution, complex stress deformation and large difference of contact force chains in the asphalt mixture under the action of external load, and the traditional macroscopic property test cannot consider the complexity of the microscopic structure composition of the asphalt mixture and also cannot deeply understand the association between the microscopic structure in the mixture and the mechanical behavior, so that the method has certain limitation.
A Discrete Element Method (DEM) is a numerical Method for simulating mechanical behavior of particle materials, is based on a discontinuous medium theory, is particularly suitable for analyzing the mesomechanics characteristics and stress deformation of Discrete or cemented materials (problems of non-uniformity, discontinuity and large deformation), can quantify the transmission distribution condition of an internal contact force chain when the materials are loaded, and can intuitively express the force and displacement of each particle, thereby better understanding the internal mechanical mechanism of the materials when the materials are stressed from the mesoscopic structure level.
The existing asphalt mixture discrete element modeling is mainly two-dimensional modeling, and the stress state of the asphalt mixture cannot be truly reflected; the three-dimensional discrete element model can reflect the internal stress state of the structure body, provides a powerful tool for internal force chain research, but no effective means exists for constructing the model, and the problems of accuracy, efficiency and the like still exist. The existing asphalt mixture three-dimensional discrete element model construction methods are mainly divided into two types, one type is constructed based on a random generation algorithm, most of the methods utilize a multi-surface generation algorithm to simulate aggregate particles and randomly put in a simulated skeleton structure, and the method has the advantages that the modeling efficiency is high, the grading composition of the generated model can be accurately controlled, but the aggregate particle model constructed by the algorithm cannot fully represent the surface morphology of real aggregate particles, has a large difference with the actual aggregate, and the authenticity of a force chain cannot be ensured; the other type is that an in-situ asphalt mixture discrete element digital test piece is established based on an industrial CT and a digital image technology, the method can better restore the real microscopic structure of the asphalt mixture to a certain extent, but due to error transmission in the image acquisition, processing and segmentation processes, the established digital test piece has a certain error with the real structure, and meanwhile, due to the fact that the method ensures that the in-situ construction greatly prolongs the model construction time, the method has no practical application value, but the processing of the interface positions between aggregate and mortar boundary and aggregate is not clear at present, and the accuracy of a force chain result is not ideal. Aiming at the limitations existing in the construction of the prior asphalt mixture discrete element model, the invention provides a method for constructing the asphalt mixture three-dimensional discrete element model with both the model authenticity and the modeling efficiency.
Disclosure of Invention
The invention aims to solve the problem that the existing asphalt mixture three-dimensional discrete element model construction method cannot give consideration to both accuracy and high efficiency, and further provides an asphalt mixture three-dimensional discrete element model construction method giving consideration to both model authenticity and modeling efficiency.
A construction method of a three-dimensional discrete element model of an asphalt mixture comprises the following steps:
1. carrying out X-Ray scanning on a standard Marshall test piece of the asphalt mixture based on industrial CT to obtain a slice image of the asphalt mixture;
2. guiding the slice image obtained in the step one into digital image processing software, and extracting and segmenting aggregate components by using the digital image processing software;
3. performing three-dimensional reconstruction on the aggregate particle model on the basis of the second step to derive a surface grid model of the monoclinic aggregate;
4. importing the aggregate particle surface grid file with each grade of particle size into discrete element software, creating an aggregate particle model template by utilizing a column algorithm, and establishing a template library of the aggregate particle model;
5. calculating the volume of aggregate with each grade of grain diameter according to the volume, grading type, oilstone ratio, porosity, aggregate density and asphalt density index of the Marshall test piece, calling an aggregate grain model in the template library constructed in the step four, putting aggregate grain groups with specified grading type in a specified cylindrical wall space through a random generation algorithm, eliminating the overlapping amount among grains by utilizing a circulation command, setting gravity to enable the aggregate grain groups to be naturally stacked, and finally compacting the aggregate grain groups to a specified height by applying acceleration to the wall body on the upper surface to form a framework structure;
6. filling ball particle simulation asphalt mortar among the aggregate particles by using a language program, and randomly deleting a specified number of ball simulation void structures according to the set void ratio, thereby realizing the construction of the three-dimensional digital test piece of the asphalt mixture;
7. endowing the constructed digitalized test piece of the asphalt mixture with a corresponding contact model and microscopic contact parameters to simulate the mechanical behavior of the asphalt mixture;
8. and (4) carrying out a virtual indirect tensile test and an indoor macroscopic mechanical test, taking the peak load error percentage p as an evaluation index of the accuracy of the discrete element model, and if the value of p exceeds the modeling requirement, adjusting the discrete element microscopic model parameters in the step seven until the error percentage is less than the error requirement, thereby completing the construction of the three-dimensional discrete element model of the asphalt mixture.
Preferably, the process of extracting and segmenting the aggregate components by using the digital image processing software in the step two is as follows:
firstly, aggregate components are identified and extracted through non-local mean filtering, gray level equalization, interactive threshold segmentation and a background detection correction algorithm, and then the segmentation of the adhered aggregate particles is realized through watershed segmentation, morphological opening operation, hole filling algorithm processing and a three-dimensional contact segmentation algorithm.
A computer storage medium having stored therein at least one instruction, the at least one instruction being loaded and executed by a processor to implement the asphalt mixture three-dimensional discrete meta-model building method.
The equipment comprises a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to realize the asphalt three-dimensional discrete element model building method.
Compared with the existing modeling method, the method has the following advantages:
by the method, a large number of aggregate particle model templates can be efficiently and quickly obtained, so that the real surface morphology of the aggregate particles is fully represented. The asphalt mixture forming process is accompanied with the crushing and stacking of the aggregates, the aggregates of the formed asphalt mixture have a certain difference with the aggregates before forming, compared with the aggregate particles which are directly scanned, the aggregates extracted based on the Marshall test piece of the asphalt mixture are in a real state after forming, and the accuracy of model construction is ensured. The image processing and segmentation method is provided, the aggregate and the mucilage are accurately distinguished, and the authenticity of the aggregate form is ensured. The template library of the aggregate particle model is established for calling, so that the model building time is greatly shortened, and the model building simplicity is improved. Compared with a method for directly constructing a model, the method for naturally stacking aggregate particle groups by setting gravity truly simulates the molding process of a test piece, and the authenticity is greatly improved. The method improves the accuracy of the three-dimensional discrete element model of the asphalt mixture, the constructed aggregate calling library ensures the authenticity and convenience of the model construction, the grading type of the constructed digital test piece can be accurately controlled by utilizing a random generation algorithm, the real accuracy and the efficiency of the modeling result are considered, the modeling method of the three-dimensional discrete element model of the asphalt mixture is optimized, an effective support means is provided for the research of the mechanical property of the asphalt mixture, and the further research of the digitized design of the asphalt mixture is promoted.
Drawings
FIG. 1 is a diagram showing the reconstruction effect of the aggregate structure of the asphalt mixture.
FIG. 2 is a flow chart of image processing using Avizo.
Fig. 3 is a digital image of the asphalt mix processing flow.
FIG. 4 aggregate particle template library.
FIG. 5 is an effect diagram of a constructed three-dimensional discrete element digital test piece of the asphalt mixture.
FIG. 6 is a cross-sectional view of a constructed three-dimensional discrete element digital test piece of the asphalt mixture.
Fig. 7 is a graph comparing the mechanical curves of the virtual test and the laboratory test.
Detailed Description
The first embodiment is as follows:
the embodiment is a method for constructing a three-dimensional discrete element model of an asphalt mixture, which comprises the following steps:
1. and carrying out X-Ray scanning on the asphalt mixture standard Marshall test piece based on industrial CT to obtain a slice image of the asphalt mixture Marshall test piece.
2. Importing the slice image obtained in the step one into digital image processing software Avizo; firstly, identifying and extracting aggregate components through non-local mean filtering, gray level equalization, interactive threshold segmentation and a background detection correction algorithm, and then realizing the segmentation of adhered aggregate particles through watershed segmentation, morphological opening operation, hole filling algorithm processing and a three-dimensional contact segmentation algorithm.
3. And on the basis of the second step, carrying out three-dimensional reconstruction on the aggregate particle model through a volume drawing command, and constructing and exporting a surface mesh file (STL file) of the single aggregate model by utilizing a surface mesh generation command.
4. And importing the aggregate particle surface grid file with each grade of particle size into discrete element software, creating an aggregate particle model template by using a column algorithm, and establishing a template library of the aggregate particle model.
In the present embodiment, the critical parameters ratio and distance for controlling the Clump algorithm are set to 0.3 and 150, respectively.
5. Calculating the volume of aggregate with each grade of particle size according to the indexes of the volume, the grading type, the oilstone ratio, the void ratio, the aggregate density and the asphalt density of the Marshall test piece, randomly calling an aggregate particle model in the template library constructed in the fourth step, putting an aggregate particle group with the specified grading type in the specified cylindrical wall space through a random generation algorithm, eliminating the overlapping amount among particles by utilizing a cycle circulation command, setting gravity to enable the aggregate particle group to be naturally stacked, and finally compacting the aggregate particle group to the specified height by applying acceleration to the wall body on the upper surface to form a framework structure.
In the present embodiment, the height of the cylindrical wall is 200mm.
6. Filling ball particle simulation asphalt mortar components among aggregate particles by utilizing a fish language compiling program, and deleting specified number of ball particle simulation gap structures at random according to the set void ratio, thereby realizing the construction of the three-dimensional digital test piece of the asphalt mixture.
In the present embodiment, the ball particle radius of the simulated asphalt mortar is 0.8mm.
7. And endowing the constructed digitized test piece of the asphalt mixture with a corresponding contact model and microscopic contact parameters to simulate the mechanical behavior of the asphalt mixture.
In this embodiment, the microscopic contact parameters of the discrete element model include contact stiffness parameters between aggregate units, contact stiffness and bonding parameters between aggregate and mortar units, and contact stiffness and bonding parameters between mortar units.
8. And (4) carrying out a virtual indirect tensile test and an indoor macroscopic mechanical test, taking the peak load error percentage p as an evaluation index of the accuracy of the discrete element model, and if the value of p exceeds the modeling requirement, adjusting the discrete element microscopic model parameters in the step seven until the error percentage is less than the error requirement, thereby completing the construction of the three-dimensional discrete element model of the asphalt mixture.
The indirect tensile test was carried out according to the road engineering asphalt-based asphalt mixture test protocol (JTG E20-2011).
In this embodiment, if the modeling error requirement of the discrete element model is lower than 10%, the discrete element model is successfully constructed.
The second embodiment is as follows:
the embodiment is a computer storage medium, wherein at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to realize the asphalt mixture three-dimensional discrete element model building method.
It should be understood that any of the methods described herein, including any methods described herein, may correspondingly be provided as a computer program product, software, or computerized method, which may include a non-transitory machine-readable medium having stored thereon instructions, which may be used to program a computer system, or other electronic device. Storage media may include, but is not limited to, magnetic storage media, optical storage media; a magneto-optical storage medium comprising: read only memory ROM, random access memory RAM, erasable programmable memory (e.g., EPROM and EEPROM), and flash memory layers; or other type of media suitable for storing electronic instructions.
The third concrete implementation mode:
the embodiment is an asphalt mixture three-dimensional discrete element model construction device, which comprises a processor and a memory, and it should be understood that any device described in the present invention, which comprises a processor and a memory, may also comprise other units and modules that perform display, interaction, processing, control, etc. and other functions through signals or instructions;
the memory is stored with at least one instruction, and the at least one instruction is loaded and executed by the processor to realize the asphalt mixture three-dimensional discrete element model construction method.
Example (b):
the construction method of the three-dimensional discrete element model of the asphalt mixture is implemented according to the following steps:
1. and carrying out X-Ray scanning on the asphalt mixture standard Marshall test piece based on industrial CT to obtain a slice image of the asphalt mixture Marshall test piece.
2. And (3) importing the slice image obtained in the step one into digital image processing software Avizo, wherein the Avizo image processing flow is shown in FIG. 2.
Firstly, identifying and extracting aggregate components through non-local mean filtering, gray level equalization, interactive threshold segmentation and a background detection correction algorithm, and then realizing the segmentation of adhered aggregate particles through watershed segmentation, morphological opening operation, hole filling algorithm processing and a three-dimensional contact segmentation algorithm, wherein the morphological opening operation processes an aggregate model and can simplify image data on the basis of keeping a basic form; finally, label analysis (label analysis) is performed, and mutually separated parts are labeled (distinguished by colors, and volume coordinates and the like can be read).
It should be noted that, in fact, the present invention is not limited to the processing procedure of the present invention, and it is only required to realize segmentation, but the processing procedure of the present invention can process the image well, and the segmentation effect is very good, and the digital image of the processing procedure of the asphalt mixture is as shown in fig. 3, so that the present invention can clearly segment the particles with different particle sizes.
3. And performing three-dimensional reconstruction on the aggregate particle model through a volume rendering command on the basis of the step two, as shown in fig. 1, and constructing and exporting a surface mesh file (STL file) of the single aggregate model by using a surface mesh generation command.
4. The aggregate particle surface mesh files with different particle sizes are imported into discrete element software, aggregate particle model templates are created by utilizing a column algorithm (key parameters ratio and distance are respectively set to be 0.3 and 150), a template library of the aggregate particle models is established, and as shown in fig. 4, 100 different aggregate particle templates are constructed in the embodiment.
5. Calculating the volume of aggregate with each grade of particle size according to the indexes of the Marshall test piece such as volume, grading type, oilstone ratio, void ratio, aggregate density and asphalt density according to the formula (1), constructing a cylindrical wall with the height of 200mm and the diameter of 101.6mm, randomly calling an aggregate particle model in a template library constructed in the fourth step, putting an aggregate particle group with a specified grading type in the constructed cylindrical wall through a random generation algorithm clock distribution command, eliminating the overlapping amount among particles by utilizing a cycle circulating command, setting gravity to naturally stack the aggregate particle group, and finally compacting the aggregate particle group to the specified height of 63.5mm to form a framework structure by applying the speed of-1 m/s to the upper surface wall.
In the formula: v Ln -the volume of grade n particle size aggregate;
P n+1 、P n the percentage passage of the particle sizes of the n +1 th and the n th
V S -the volume occupied by the fine aggregate (below 2.36 mm);
V L -coarse aggregate (2.36 mm and above) volume;
v is the specimen volume;
ρ a -pitch density;
ρ s -aggregate density;
alpha-oilstone ratio;
VV-void fraction.
6. Filling ball simulated asphalt mortar components with the radius of 0.8mm among the aggregate particles by utilizing a fish language compiling program, and randomly deleting a specified number of ball particle simulated void structures according to the void ratio determined in the fifth step, so that the construction of the three-dimensional digital test piece of the asphalt mixture is realized, wherein the software effect graph of the three-dimensional digital test piece of the asphalt mixture is shown in fig. 5; the cross-sectional view of the three-dimensional digital asphalt mixture test piece is shown in fig. 6.
7. Endowing a corresponding contact model and microscopic contact parameters to the constructed asphalt mixture digital test piece to simulate the mechanical behavior of the asphalt mixture, adopting a linear rigidity contact model for the contact between aggregates, adopting a linear contact bonding model for the contact model between asphalt mortar, and adopting a linear contact bonding model for the contact model between aggregates and asphalt mortar. The corresponding mesoscopic parameters of the model are shown in tables 1-3.
TABLE 1 contact parameters between aggregates
TABLE 2 contact parameters inside asphalt mortar
TABLE 3 contact parameters between asphalt mortar and aggregate
Wherein A is the cross-sectional area of the elastic beam in contact, and the unit is m 2 And L is the length of the contact elastic beam, the unit is m, A and L can traverse all contacts by using a fish language, the radius of the entity units at two ends of the contacts is obtained and calculated, and A/L = L is set.
8. And performing a virtual indirect tensile test, taking an indoor macroscopic test mechanical curve as a verification index, and adjusting microscopic contact parameters to enable the mechanical curves of the virtual test and the indoor test to achieve a better matching degree, wherein the peak load error is 6%, and the model is successfully established. The mechanical curve comparison of the indirect tensile test is shown in fig. 7.
According to the invention, a large number of aggregate particle model templates can be efficiently and quickly obtained, so that the real surface morphology of aggregate particles is fully represented, the accuracy degree of the three-dimensional discrete element model of the asphalt mixture is improved, the gradation type of the constructed digital test piece can be accurately controlled by utilizing a random generation algorithm, the real accuracy and the efficiency of modeling are both considered, the modeling method of the three-dimensional discrete element model of the asphalt mixture is optimized, and the further deep research on the digital design of the asphalt mixture is promoted.
The above-described calculation examples of the present invention are merely to explain the calculation model and the calculation flow of the present invention in detail, and are not intended to limit the embodiments of the present invention. It will be apparent to those skilled in the art that other variations and modifications can be made on the basis of the foregoing description, and it is not intended to exhaust all of the embodiments, and all obvious variations and modifications which fall within the scope of the invention are intended to be included within the scope of the invention.
Claims (10)
1. A construction method of a three-dimensional discrete element model of an asphalt mixture is characterized by comprising the following steps:
1. carrying out X-Ray scanning on a standard Marshall test piece of the asphalt mixture based on industrial CT to obtain a slice image of the asphalt mixture;
2. guiding the slice image obtained in the first step into digital image processing software, and extracting and segmenting the aggregate components by using the digital image processing software;
3. performing three-dimensional reconstruction on the aggregate particle model on the basis of the second step to derive a surface grid model of the monoclinic aggregate;
4. importing the aggregate particle surface grid file with each grade of particle size into discrete element software, creating an aggregate particle model template by utilizing a column algorithm, and establishing a template library of the aggregate particle model;
5. calculating the volume of aggregate with each grade of particle size according to the indexes of the volume, the grading type, the oilstone ratio, the void ratio, the aggregate density and the asphalt density of the Marshall test piece, calling an aggregate particle model in the template library constructed in the fourth step, putting aggregate particle groups with the specified grading type in the specified cylindrical wall space through a random generation algorithm, eliminating the overlapping amount among particles by utilizing a circulation command, setting gravity to enable the aggregate particle groups to be naturally stacked, and finally compacting the aggregate particle groups to the specified height by applying acceleration to the wall body on the upper surface to form a framework structure;
6. filling ball particle simulation asphalt mortar among the aggregate particles by using a language program, and randomly deleting a specified number of ball simulation void structures according to the set void ratio, thereby realizing the construction of the three-dimensional digital test piece of the asphalt mixture;
7. endowing the constructed digitized test piece of the asphalt mixture with a corresponding contact model and microscopic contact parameters to simulate the mechanical behavior of the asphalt mixture;
8. and (4) carrying out a virtual indirect tensile test and an indoor macroscopic mechanical test, taking the peak load error percentage p as an evaluation index of the accuracy of the discrete element model, and if the value of p exceeds the modeling requirement, adjusting the discrete element microscopic model parameters in the step seven until the error percentage is less than the error requirement, thereby completing the construction of the three-dimensional discrete element model of the asphalt mixture.
2. The method for constructing the three-dimensional discrete element model of the asphalt mixture according to claim 1, wherein the processing procedure of extracting and segmenting the aggregate components by using digital image processing software in the second step is as follows:
firstly, aggregate components are identified and extracted through non-local mean filtering, gray level equalization, interactive threshold segmentation and a background detection correction algorithm, and then the segmentation of the adhered aggregate particles is realized through watershed segmentation, morphological opening operation, hole filling algorithm processing and a three-dimensional contact segmentation algorithm.
3. The asphalt mixture three-dimensional discrete element model construction method according to claim 1 or 2, wherein the key parameters ratio and distance of the step four control Clump algorithm are respectively set to 0.3 and 150.
4. The method for constructing the three-dimensional discrete element model of the asphalt mixture as recited in claim 3, wherein the number of the aggregate particle templates constructed in the fourth step is 100.
5. The method for constructing the three-dimensional discrete element model of the asphalt mixture according to claim 4, wherein in the fifth step, the height of the cylindrical wall is 200mm, the diameter of the cylindrical wall is 101.6mm, and the compaction height of the cylindrical wall is 63.5mm.
6. The method for constructing the three-dimensional discrete element model of asphalt mixture as claimed in claim 5, wherein the ball particle radius of the simulated asphalt mortar in the sixth step is 0.8mm.
7. The method for constructing the three-dimensional discrete element model of the asphalt mixture as claimed in claim 6, wherein the discrete element model parameters in the seventh step are rigidity parameters among aggregates, rigidity and bonding parameters among asphalt mortars, and rigidity and bonding parameters among aggregates and asphalt mortars.
8. The method for constructing the three-dimensional discrete element model of asphalt mixture according to claim 8, wherein in the eighth step, the modeling error requirement of the discrete element model is lower than 10%, and the discrete element model is successfully constructed.
9. A computer storage medium, characterized in that at least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the method for constructing a three-dimensional discrete element model of asphalt mixture according to any one of claims 1 to 8.
10. An asphalt mixture three-dimensional discrete element model construction device, which is characterized by comprising a processor and a memory, wherein the memory is stored with at least one instruction, and the at least one instruction is loaded and executed by the processor to realize the asphalt mixture three-dimensional discrete element model construction method according to one of claims 1 to 8.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116467901A (en) * | 2023-03-02 | 2023-07-21 | 中国地质大学（北京） | Discrete element modeling method and device for broken stone |
| CN116469499A (en) * | 2023-06-20 | 2023-07-21 | 宁德时代新能源科技股份有限公司 | Adhesive state simulation method, adhesive state simulation device, computer equipment and storage medium |
| CN117350141A (en) * | 2023-12-04 | 2024-01-05 | 佛山市交通科技有限公司 | Fatigue damage simulation method and equipment for regenerated asphalt mixture based on discrete elements |
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2022
- 2022-07-20 CN CN202210859983.9A patent/CN115311410A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116467901A (en) * | 2023-03-02 | 2023-07-21 | 中国地质大学（北京） | Discrete element modeling method and device for broken stone |
| CN116469499A (en) * | 2023-06-20 | 2023-07-21 | 宁德时代新能源科技股份有限公司 | Adhesive state simulation method, adhesive state simulation device, computer equipment and storage medium |
| CN116469499B (en) * | 2023-06-20 | 2023-09-22 | 宁德时代新能源科技股份有限公司 | Adhesive state simulation method, adhesive state simulation device, computer equipment and storage medium |
| CN117350141A (en) * | 2023-12-04 | 2024-01-05 | 佛山市交通科技有限公司 | Fatigue damage simulation method and equipment for regenerated asphalt mixture based on discrete elements |
| CN117350141B (en) * | 2023-12-04 | 2024-04-05 | 佛山市交通科技有限公司 | Fatigue damage simulation method and equipment for regenerated asphalt mixture based on discrete elements |
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