CN109164117A - Based on-bituminous concrete damage forecast the method for mortar interface Fracture of gathering materials - Google Patents
Based on-bituminous concrete damage forecast the method for mortar interface Fracture of gathering materials Download PDFInfo
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Abstract
The invention discloses a kind of based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials, this method includes microscopical structure modeling, interfacial fracture law-analysing and damage forecast model three parts, microscopical structure models the space microscopical structure model that different aggregate particles are established using X-Ray CT equipment, calculates-mortar interface the Broken condition that gathers materials in conjunction with viscous-elastic material constitutive and energy to failure parameter；Interfacial fracture law-analysing extracts evaluation index of the fracture Dissipated energy as interface fracture behaviors according to numerical result, and calculates corresponding four spatial parameters to gather materials: volume, surface area, sphericity and three-dimensional fractal value；Damage forecast model is broken Dissipated energy as output valve, establishes the projected relationship of gather materials spatial parameter and damage status using four spatial parameters that gather materials as input value.The present invention is with respect to traditional asphalt concrete damage prediction technique, it is contemplated that its essence is interfacial fracture caused by aggregate particle, improves the validity of damage forecast significantly.
Description
Technical field
The invention belongs to bituminous concrete damage forecast research fields, more particularly to one kind to be based on bituminous concrete CT image
Microscopical structure reconstruct with damage forecast technology.
Background technique
Bituminous concrete is the civil engineering material proportionally mixed by aggregate particle, miberal powder and asphalt material,
In its construction for being widely used in town road and expressway works, important base is provided for Chinese society expanding economy
Plinth.However, bituminous concrete gradually appears disease damage in use, durability and safety to road infrastructure
Have an adverse effect.Therefore, the damage status being likely to occur under load action for assessment bituminous concrete, needing to establish it has
The damage forecast technology of effect, the optimization for material and structure design provide reference.
Asphalt concrete structure damage prediction be road engineering research field emphasis and long-standing difficult point.
Due to the aggregate particle inside bituminous concrete there are different-shape, and the aggregate particle body of different-shape to damage generate with
The influence of machine, especially gather materials-mortar interface due to stress concentration phenomenon Unpredictability, it tends to be difficult to effectively sentence
The damage status of disconnected interface weak part.
The research in bituminous concrete damage field has been changed from macroscopical large scale to microcosmic small scale at this stage,
A variety of microscopical structure models suitable for Damage Evaluation are established, as Chinese invention patent " is based on bituminous pavement test specimen X-ray
The thin sight physical model reconstructing method CN201510197932.4 " that gathers materials of CT image, but simultaneously not operatively carry out bituminous concrete
The research of structural damage and its prediction.On the other hand, the damage at interface between mortar of gathering materials causes bituminous concrete to damage
Key, how effectively to establish the assessment technique of interface damage is the important foundation for carrying out bituminous concrete damage forecast.Into one
Step ground, conventional numeric, which calculates, expends a large amount of manpower and material resources, therefore carries out to gather materials and study with mortar interface injuring rule, building collection
Material feature and interface damage relational database are the effective ways for predicting bituminous concrete damage status under load action.
Summary of the invention
Goal of the invention: the above status with there are aiming at the problem that, the present invention proposes a kind of based on-mortar interface fracture of gathering materials
The bituminous concrete damage forecast method of rule, the present invention establish the mould of interface damage behavior between different aggregate particles and mortar
Quasi- method, and interface damage Predicting Technique of the BP neural network model buildings based on feature of gathering materials is combined, this method solve
Problem is computed repeatedly existing for previous damage forecast, it can be according to the aggregate particle raw material feature evaluation for standby bituminous concrete of drawing up
The damage status being likely to occur.
In order to achieve the above technical purposes, this hair, which is bought, adopts the following technical scheme that
It is a kind of based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials, this method includes following
Step:
S1, microscopical structure modeling
The space microscopical structure model that different aggregate particles are established using X-Ray CT equipment, in conjunction with viscous-elastic material constitutive
- mortar interface the Broken condition that gathers materials is calculated with energy to failure parameter；
S2, interfacial fracture law-analysing
According to the space microscopical structure model of the obtained different aggregate particles of step S1 and the-mortar interface fracture shape that gathers materials
Condition acquisition is gathered materials-mortar interface fracture Dissipated energy, gather materials described in extraction-mortar interface fracture Dissipated energy is as interface fracture behaviors
Evaluation index, and calculate corresponding four spatial parameters to gather materials: volume, surface area, sphericity and three-dimensional fractal value；
S3, damage forecast model
Using four spatial parameters that gather materials as input value, be broken Dissipated energy and be used as output valve, foundation gather materials spatial parameter and
The prediction model of damage status.
Step S1 specifically includes following sub-step:
S1.1, multiple aggregate particles are chosen as objects of statistics, all aggregate particles is carried out using X-Ray CT equipment
Scanning, obtains the tomoscan image data of aggregate particle；
S1.2, according to the resulting each aggregate particle tomoscan image data of step S1.1, built by image processing techniques
Found the space microscopical structure model of each aggregate particle.
Step S2 is specifically: according to the space microscopical structure model of aggregate particle obtained by step S1.2, on the one hand carrying out empty
Between image analysis, calculate four spatial parameters of aggregate particle: volume, surface area, sphericity and three-dimensional fractal dimension, another party
- mortar interface the fracture behaviour that gathers materials is simulated using numerical software in face, and obtains interfacial fracture Dissipated energy index.
Step S3 specifically includes following sub-step:
S3.1, using four spatial parameters of aggregate particle as fan-in evidence, corresponding fracture Dissipated energy index be output end
Data, establish the neural network model based on BP algorithm, and training show that four spatial parameters and the prediction being broken between Dissipated energy close
System；
S3.2, according to projected relationship obtained by step S3.1, carry out damage status prediction according to bituminous concrete feature of gathering materials.
In step S1, the particle size range for choosing aggregate particle is 2.36mm~16mm, and amounts of particles is greater than 200, with true
Protect enough sample numbers；Selected aggregate particle is placed in multilayer trellis mold, and is scanned by X-Ray CT, sweeps
Retouching resolution ratio is 10 μm~100 μm, and sweep span is 0.1mm~0.2mm.
In the step S1, has the aggregate particle identification and extraction journey of batch processing function using MATLAB software programming
Sequence carries out binary conversion treatment by tomoscan image of the MATLAB function im2bw to aggregate particle, establishes different aggregate particles
Space-filling model.
In the step S2, using MATLAB software according to the pixel number and sweep span of aggregate particle bianry image, knot
The volume and surface area of aggregate particle can be calculated by closing image resolution sizes, further, can be by volume and surface area by public
Formula converts to obtain the sphericity of aggregate particle；
The net calculated by the three-dimensional fractal dimension calculation procedure of MATLAB software programming aggregate particle, three-dimensional fractal dimension
Lattice size range obtains four spatial parameters of aggregate particle between 1 times of resolution ratio~100 times resolution ratio by the above process.
Interfacial fracture Dissipated energy index described caused by aggregate particle is obtained especially by following method in the step S2
:
Diameter 5cm~10cm is established using ABAQUS finite element software, the cylindrical body of high 5cm~10cm chooses any list
Only aggregate particle imports the cylindrical body, it is ensured that the two mass center is overlapped；It is cut and is gathered materials in the cylindrical body by boolean operation
The identical inner cavity of grain, and be setting contact interface with cohesion Lixing by aggregate particle outer surface and surface of internal cavity；Contact boundary
Face uses viscous-elastic material constitutive, and the lesion mimic of contact interface is realized by setting energy to failure parameter；Cylindrical body with gather materials
Particle is all made of C3D8 dividing elements grid, and having a size of 0.1mm~0.5mm, cylinder bottom applies the perimeter strip being completely fixed
The lower pressure of constant rate of speed is arranged in part, top, and rate control is 1mm/s~2mm/s.
In the step S3, the neural network model based on BP algorithm is compiled using MATLAB, chooses all aggregate particles
Four spatial parameters be fan-in evidence, corresponding fracture Dissipated energy index is as fan-out evidence, by based on BP algorithm
The training of neural network model obtains the prediction model of the fracture Dissipated energy based on spatial parameter.
In the step S3.2, for some type of asphalt concrete structure, proportional arrangement concrete is matched according to design level
Material and molded test test specimen determine four spatial parameters of each aggregate particle inside test specimen after X-Ray CT scan, and
It determines that the accumulation that all aggregate particles may cause is broken Dissipated energy by neural network prediction model, Dissipated energy is broken by accumulation
The easy damaged performance of bituminous concrete is assessed.
The utility model has the advantages that compared with prior art, technical solution of the present invention has following advantageous effects:
(1) present invention establishes a kind of bituminous concrete damage forecast method based on aggregate particle feature, mixed for pitch
Xtah Crude Clay structure has preferably provided effective assessment technology.
(2) it in terms of aggregate particle characteristic parameter, proposes using volume, surface area, sphericity and three-dimensional fractal dimension
It is characterized, specifies the quantizating index for atypical characteristic of gathering materials.
(3) in terms of bituminous concrete damage forecast, established using nerve network system aggregate particle feature and gather materials-
Mortar interface injuring relation, improves precision of prediction.
(4) in addition, this technique avoids the scenes that Classical forecast technology needs to expend a large amount of manpower and material resources, it is only necessary to constantly complete
Kind damage data library can damage the bituminous concrete of different types of structure and predict.
Detailed description of the invention
Fig. 1 is the flow chart of the method for the present invention；
Fig. 2 is the aggregate particle of different characteristic；
Wherein, a is 1 photo of Aggregate Type, and b is 2 photo of Aggregate Type；
Fig. 3 is aggregate particle holder structural schematic diagram；
Fig. 4 is the X-Ray CT scan and reconstruct image of aggregate particle；
Wherein, a1 is 1 reconstruct image of Aggregate Type, and b1 is 2 reconstruct image of Aggregate Type；
Fig. 5 is aggregate particle three-dimensional fractal dimension；
Fig. 6 is aggregate particle interfacial fracture numerical simulation；
Fig. 7 is aggregate particle stress state and interfacial fracture process；
Wherein, c is different time aggregate particle stress state figure, and d is different time aggregate particle interfacial fracture procedure chart；
Fig. 8 is the neural network model based on BP algorithm；
Fig. 9 is the independent aggregate particle validity of Neural Network model predictive；
Figure 10 is bituminous concrete damage forecast result.
Specific embodiment
Further description of the technical solution of the present invention with reference to the accompanying drawings and examples.
It is of the present invention a kind of based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials, tool
Body includes the following steps:
(1) multiple aggregate particles are chosen as objects of statistics, all aggregate particles are swept using X-Ray CT equipment
It retouches, obtains the tomoscan image data of aggregate particle；
(2) it according to the resulting each aggregate particle tomoscan image data of step (1), is established by image processing techniques each
The space microscopical structure model of aggregate particle；
(3) using the space microscopical structure model of aggregate particle obtained by step (2), volume image analysis is on the one hand carried out,
Four spatial parameters of aggregate particle: volume, surface area, sphericity and three-dimensional fractal dimension are calculated, numerical value is on the other hand used
Software simulates the-mortar interface fracture behaviour that gathers materials, and obtains interfacial fracture Dissipated energy index；
(4) using four spatial parameters of aggregate particle as fan-in evidence, corresponding fracture Dissipated energy index is fan-out
According to, neural network model of the foundation based on BP algorithm, the projected relationship that training obtains four spatial parameters and is broken between Dissipated energy；
(5) according to projected relationship obtained by step (4), the feature that can gather materials according to bituminous concrete carries out damage status prediction.
In the step (1), the particle size range for choosing aggregate particle is 2.36mm~16mm, and amounts of particles is preferably greater than 200
, to ensure enough sample numbers；Selected aggregate particle can be placed in multilayer trellis mold, and by X-Ray CT into
Row scanning, scanning resolution are 10 μm~100 μm, and sweep span is 0.1mm~0.2mm.
In the step (2), has the aggregate particle identification of batch processing function using MATLAB software programming and extract
Program carries out binary conversion treatment to the tomoscan image of aggregate particle by MATLAB function im2bw, establishes difference and gathers materials
The space-filling model of grain.
In the step (3), using MATLAB software according to the pixel number and sweep span of aggregate particle bianry image, knot
The volume and surface area of aggregate particle can be calculated by closing image resolution sizes, further, can be by volume and surface area by public
Formula converts to obtain the sphericity of aggregate particle；By the three-dimensional fractal dimension calculation procedure of MATLAB software programming aggregate particle,
The size of mesh opening range that three-dimensional fractal dimension calculates is between 1 times of resolution ratio~100 times resolution ratio.Gathered materials by the above process
Four spatial parameters of particle.
In the step (3), diameter 5cm~10cm, the cylinder of high 5cm~10cm are established using ABAQUS finite element software
Body chooses any individually aggregate particle and imports the cylindrical body, it is ensured that the two mass center is overlapped；Through boolean operation in the cylindrical body
Cutting and the identical inner cavity of aggregate particle, and be with cohesion Lixing by aggregate particle outer surface and surface of internal cavity
Contact interface is arranged in (Cohesive Behavior)；Contact interface uses viscous-elastic material constitutive, and is joined by setting energy to failure
Number realizes the lesion mimic of contact interface；Cylindrical body and aggregate particle are all made of C3D8 dividing elements grid, having a size of 0.1mm~
0.5mm, cylinder bottom apply the boundary condition being completely fixed, and the lower pressure of constant rate of speed is arranged in top, and rate control is
1mm/s~2mm/s；By the above process, interfacial fracture Dissipated energy index caused by aggregate particle is calculated.
In the step (4), the neural network model based on BP algorithm is compiled using MATLAB, chooses all aggregate particles
Four spatial parameters be fan-in evidence, corresponding fracture Dissipated energy index is as fan-out evidence, by based on BP algorithm
The training of neural network model obtains the fracture Dissipated energy prediction model based on spatial parameter.
In the step (5), for some type of asphalt concrete structure, molded test test specimen, warp are matched according to design level
Four spatial parameters of each aggregate particle inside test specimen are determined after crossing X-Ray CT scan, and are determined by neural network prediction model
The accumulation that all aggregate particles may cause is broken Dissipated energy, by accumulation fracture Dissipated energy to the easy damaged of bituminous concrete
It can be carried out assessment.
Specific reconstructing method combines following embodiments to be described below:
Embodiment
As shown in Figure 1, a kind of based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials, the party
Method includes microscopical structure modeling, interfacial fracture law-analysing and damage forecast model three parts, by establishing different aggregate particles
Interface damage database corresponding to feature determines bituminous concrete damage forecast model in conjunction with nerve network system.
As shown in Fig. 2, choosing the aggregate particle for having different-shape feature Yu volume size first, selected in the present embodiment
Two types aggregate particle is as objects of statistics, and each type chooses 200 according to particle size and gathers materials, and particle size range is
2.36mm~16mm.
As shown in Fig. 3~Fig. 4, aggregate particle container of the production for scanning, length is 10cm, in the present embodiment
Aggregate particle container is divided into 4 layers, places 25 for every layer and gathers materials, total can place 100 aggregate particles；Using Germany
The Y.CT Precision S type CT equipment of YXLON.International company production is scanned, resolution ratio 0.1mm,
Sweep span is 0.1mm；After being scanned, 1000 original CT image files, file format BMP can get.
Batch reading is carried out to CT image sequence using the imread function of MATLAB software, and extracts independent aggregate particle
It is handled；Aggregate particle volume and surface area are determined by pixel quantity, and are calculated using the following equation the aggregate particle
Sphericity:
As shown in figure 5, using the three-dimensional fractal dimension of MATLAB calculating aggregate particle: with various sizes of grid dividing collection
Expect that particle, size of mesh opening are determined according to CT image pixel dimensions, in the range of 1 pixel~100 pixels, obtains size of mesh opening and packet
Number of grid containing aggregate particle, the two in log-log coordinate system slope of a curve as three-dimensional fractal dimension index:
By the above method, it is disposed and amounts to 400 aggregate particles and obtain related data, is i.e. volume Vol, surface area
Surf, sphericity 3DTS and three-dimensional fractal dimension 3DFD.
As shown in fig. 6, use MATLAB by the binary image data reconstruction of aggregate particle for aggregate particle spatial model,
And import and calculated in ABAQUS finite element software: initially setting up the cylindrical model having a size of diameter 5cm, high 5cm and represent
Asphalt mortar, bituminous mortar, cut inside cylindrical body using boolean operation with the identical intracavity space of aggregate particle, and will gather materials
Grain translation is wherein；Aggregate particle elasticity modulus is 55000MPa, and Poisson's ratio 0.01, asphalt mortar, bituminous mortar is assumed to be viscoelastic material, this
Structure relationship such as table 1:
1 asphalt mortar, bituminous mortar viscoelastic material parameter of table
Gather materials-mortar interface simulated using the Cohesive Behavior in ABAQUS, energy to failure parameter such as table
Shown in 2:
Table 2 gathers materials-mortar interface fracture behaviour parameter
Cylinder bottom is completely fixed, and top applies the displacement for pushing that constant rate is 0.01mm/s, and simulated time is set to
200s。
As shown in fig. 7, principal stress situation caused by different aggregate particles can be determined by numerical simulation, in addition, passing through
Setting fracture Dissipated energy index, the available-crack conditions of mortar interface in different time points of gathering materials.
As shown in figure 8, the Establishment of Neural Model damage forecast model based on BP algorithm is chosen, with volume Vol, surface
Product Surf, sphericity 3DTS and three-dimensional fractal dimension 3DFD are as fan-in evidence, and corresponding fracture Dissipated energy DDE is as output
End data amounts to 400 groups of data and is trained, determines neural network prediction model.
For the validity for verifying neural network prediction model, optionally take 66 aggregate particles that X-Ray CT is used to reconstruct first
Calculating analysis is carried out using ABAQUS finite element afterwards, obtains the fracture Dissipated energy index of interface damage；Meanwhile 66 are analyzed respectively
Volume, surface area, sphericity and the three-dimensional fractal dimension index gathered materials obtain fracture Dissipated energy using Neural Network model predictive
Index calculates gained fracture Dissipated energy with numerical value and compares, as shown in Figure 9.As it can be seen that the predicted value and number of neural network model
It is worth calculated value to compare with the preferable degree of correlation.
Using the degree of impairment of the Neural Network model predictive bituminous concrete after verifying, AC-13, SUP-13 are prepared respectively
With SMA-13 three classes bituminous concrete, every class formation forms 2 groups of test specimens by rotary compactor, and is formed after being cut by drill core
The cylinder specimen of high 7.5cm, diameter 5cm carry out uniaxial compression test under the conditions of 60 DEG C, and it is 1.2cm that control, which pushes displacement,.
Using cylinder specimen internal structure situation before and after X-Ray CT scan compression failure, the increase of space hole is calculated
Rate is as interface damage degree quantizating index.
It is analyzed by the aggregate particle to 6 groups of test specimens, each group test specimen aggregate particle is calculated using neural network model
Caused fracture Dissipated energy predicted value is used to represent the damage forecast value of this group of test specimen, with space hole Magnification after cumulative
It compares, as shown in Figure 10, preferable linear dependence is presented in the two, is broken consumption by the accumulation that neural network model determines
The scattered assessment that can be used as bituminous concrete faulted condition.
Claims (10)
1. a kind of based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials, which is characterized in that this method
The following steps are included:
S1, microscopical structure modeling
The space microscopical structure model that different aggregate particles are established using X-Ray CT equipment in conjunction with viscous-elastic material constitutive and is broken
It splits energy parameter and calculates-mortar interface the Broken condition that gathers materials；
S2, interfacial fracture law-analysing
According to the space microscopical structure model of the obtained different aggregate particles of step S1 and gather materials-mortar interface Broken condition obtains
- mortar interface fracture the Dissipated energy that gathers materials is taken ,-mortar interface fracture Dissipated energy commenting as interface fracture behaviors of gathering materials described in extraction
Valence index, and calculate corresponding four spatial parameters to gather materials: volume, surface area, sphericity and three-dimensional fractal value；
S3, damage forecast model
Using four spatial parameters that gather materials as input value, Dissipated energy is broken as output valve, establishes gather materials spatial parameter and damage
The prediction model of situation.
2. it is according to claim 1 based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials,
It is characterized in that, step S1 specifically includes following sub-step:
S1.1, multiple aggregate particles are chosen as objects of statistics, all aggregate particles are scanned using X-Ray CT equipment,
Obtain the tomoscan image data of aggregate particle；
S1.2, according to the resulting each aggregate particle tomoscan image data of step S1.1, established by image processing techniques each
The space microscopical structure model of aggregate particle.
3. it is according to claim 2 based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials,
It is characterized in that, step S2 is specifically: according to the space microscopical structure model of aggregate particle obtained by step S1.2, on the one hand carrying out empty
Between image analysis, calculate four spatial parameters of aggregate particle: volume, surface area, sphericity and three-dimensional fractal dimension, another party
- mortar interface the fracture behaviour that gathers materials is simulated using numerical software in face, and obtains interfacial fracture Dissipated energy index.
4. it is according to claim 1 based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials,
It is characterized in that, step S3 specifically includes following sub-step:
S3.1, using four spatial parameters of aggregate particle as fan-in evidence, corresponding fracture Dissipated energy index be fan-out evidence,
Establish the neural network model based on BP algorithm, the projected relationship that training obtains four spatial parameters and is broken between Dissipated energy；
S3.2, according to projected relationship obtained by step S3.1, carry out damage status prediction according to bituminous concrete feature of gathering materials.
5. it is according to claim 1 based on the-bituminous concrete damage forecast method of mortar interface Fracture of gathering materials,
It is characterized in that, in step S1, the particle size range for choosing aggregate particle is 2.36mm ~ 16mm, and amounts of particles is greater than 200, with true
Protect enough sample numbers；Selected aggregate particle is placed in multilayer trellis mold, and is scanned by X-Ray CT, sweeps
Retouching resolution ratio is 10 μm ~ 100 μm, and sweep span is 0.1mm ~ 0.2mm.
6. according to claim 1 a kind of based on the-bituminous concrete damage forecast side of mortar interface Fracture that gathers materials
Method, it is characterised in that: in the step S1, using MATLAB software programming have batch processing function aggregate particle identification with
Extraction procedure carries out binary conversion treatment by tomoscan image of the MATLAB function im2bw to aggregate particle, establishes different collection
Expect the space-filling model of particle.
7. according to claim 1 a kind of based on the-bituminous concrete damage forecast side of mortar interface Fracture that gathers materials
Method, it is characterised in that: in the step S2, using MATLAB software according between the pixel number and scanning of aggregate particle bianry image
Away from, the volume and surface area of aggregate particle can be calculated in conjunction with image resolution sizes, it further, can be by volume and surface area warp
It crosses formula scales and obtains the sphericity of aggregate particle；
The grid ruler calculated by the three-dimensional fractal dimension calculation procedure of MATLAB software programming aggregate particle, three-dimensional fractal dimension
Very little range obtains four spatial parameters of aggregate particle between 1 times of resolution ratio ~ 100 times resolution ratio by the above process.
8. according to claim 1 a kind of based on the-bituminous concrete damage forecast side of mortar interface Fracture that gathers materials
Method, it is characterised in that: interfacial fracture Dissipated energy index described caused by aggregate particle is especially by as follows in the step S2
Method obtains:
Diameter 5cm ~ 10cm, the cylindrical body of high 5cm ~ 10cm are established using ABAQUS finite element software, selection is arbitrarily individually gathered materials
Particle imports the cylindrical body, it is ensured that the two mass center is overlapped；It is cut in the cylindrical body by boolean operation complete with aggregate particle
Identical inner cavity, and be setting contact interface with cohesion Lixing by aggregate particle outer surface and surface of internal cavity；Contact interface uses
Viscous-elastic material constitutive, and pass through the lesion mimic of setting energy to failure parameter realization contact interface；Cylindrical body is equal with aggregate particle
Using C3D8 dividing elements grid, having a size of 0.1mm ~ 0.5mm, cylinder bottom applies the boundary condition being completely fixed, top
The lower pressure of constant rate of speed is set, and rate control is 1mm/s ~ 2mm/s.
9. according to claim 1 a kind of based on the-bituminous concrete damage forecast side of mortar interface Fracture that gathers materials
Method, it is characterised in that: in the step S3, the neural network model based on BP algorithm is compiled using MATLAB, chooses all collection
Four spatial parameters for expecting particle are fan-in evidence, and corresponding fracture Dissipated energy index is as fan-out evidence, by being based on
The training of BP algorithm neural network model obtains the prediction model of the fracture Dissipated energy based on spatial parameter.
10. according to claim 4 a kind of based on the-bituminous concrete damage forecast side of mortar interface Fracture that gathers materials
Method, it is characterised in that: in the step S3.2, for some type of asphalt concrete structure, proportional arrangement is matched according to design level
Concrete material and molded test test specimen determine four spaces ginseng of each aggregate particle inside test specimen after X-Ray CT scan
Number, and determine that the accumulation that all aggregate particles may cause is broken Dissipated energy by neural network prediction model, it is broken by accumulation
Dissipated energy assesses the easy damaged performance of bituminous concrete.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110619181A (en) * | 2019-09-23 | 2019-12-27 | 哈尔滨工业大学 | Method for calculating three-dimensional microscopic structure characterization parameters of asphalt mixture |
| CN111582162A (en) * | 2020-05-07 | 2020-08-25 | 中国矿业大学 | Mineral dissociation degree obtaining method based on particle fracture characteristics |
| CN111582164A (en) * | 2020-05-07 | 2020-08-25 | 中国矿业大学 | Mineral dissociation method based on fracture characteristic criterion |
| CN111582161A (en) * | 2020-05-07 | 2020-08-25 | 中国矿业大学 | Mineral dissociation system based on fracture characteristic criterion |
| CN111650088A (en) * | 2020-06-10 | 2020-09-11 | 河海大学 | Real-time detection method for rheological property of fluid concrete mixture |
| CN113111563A (en) * | 2021-05-21 | 2021-07-13 | 郑州大学 | Method for evaluating adhesive property of interface between geopolymer mortar and concrete |
| CN113640148A (en) * | 2021-08-11 | 2021-11-12 | 郑州大学 | Multi-characteristic mortar and concrete matrix bonding performance analysis method |
| CN114048646A (en) * | 2021-10-28 | 2022-02-15 | 浙江大学 | Asphalt surface layer damage state inversion method based on finite element correction and artificial intelligence |
| CN115100176A (en) * | 2022-07-14 | 2022-09-23 | 中国海洋大学 | Neural network-based reinforced concrete column damage assessment method |
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Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110619181A (en) * | 2019-09-23 | 2019-12-27 | 哈尔滨工业大学 | Method for calculating three-dimensional microscopic structure characterization parameters of asphalt mixture |
| CN111582162A (en) * | 2020-05-07 | 2020-08-25 | 中国矿业大学 | Mineral dissociation degree obtaining method based on particle fracture characteristics |
| CN111582164A (en) * | 2020-05-07 | 2020-08-25 | 中国矿业大学 | Mineral dissociation method based on fracture characteristic criterion |
| CN111582161A (en) * | 2020-05-07 | 2020-08-25 | 中国矿业大学 | Mineral dissociation system based on fracture characteristic criterion |
| CN111650088A (en) * | 2020-06-10 | 2020-09-11 | 河海大学 | Real-time detection method for rheological property of fluid concrete mixture |
| CN113111563A (en) * | 2021-05-21 | 2021-07-13 | 郑州大学 | Method for evaluating adhesive property of interface between geopolymer mortar and concrete |
| CN113111563B (en) * | 2021-05-21 | 2023-02-24 | 郑州大学 | Method for evaluating adhesive property of interface between geopolymer mortar and concrete |
| CN113640148A (en) * | 2021-08-11 | 2021-11-12 | 郑州大学 | Multi-characteristic mortar and concrete matrix bonding performance analysis method |
| CN114048646A (en) * | 2021-10-28 | 2022-02-15 | 浙江大学 | Asphalt surface layer damage state inversion method based on finite element correction and artificial intelligence |
| CN114048646B (en) * | 2021-10-28 | 2024-07-23 | 浙江大学 | Asphalt surface layer damage state inversion method based on finite element correction and artificial intelligence |
| CN115100176A (en) * | 2022-07-14 | 2022-09-23 | 中国海洋大学 | Neural network-based reinforced concrete column damage assessment method |
| CN115100176B (en) * | 2022-07-14 | 2024-05-14 | 中国海洋大学 | Reinforced concrete column damage assessment method based on neural network |
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