CN107368624A - Aggregate particle model generation algorithm and Inhomogeneous charge material test specimen model generating method - Google Patents
Aggregate particle model generation algorithm and Inhomogeneous charge material test specimen model generating method Download PDFInfo
- Publication number
- CN107368624A CN107368624A CN201710446911.0A CN201710446911A CN107368624A CN 107368624 A CN107368624 A CN 107368624A CN 201710446911 A CN201710446911 A CN 201710446911A CN 107368624 A CN107368624 A CN 107368624A
- Authority
- CN
- China
- Prior art keywords
- aggregate particle
- model
- mrow
- particle model
- polygon
- 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.)
- Granted
Links
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
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention discloses a kind of aggregate particle model generation algorithm and Inhomogeneous charge material test specimen model generating method, wherein, the aggregate particle model generation algorithm comprises the following steps：First side numbers of the random one positive integer N more than 3 of generation as initial polygon, random generation N is to polar coordinates in the range of polar diameter and polar angle；Each polar coordinates are converted into rectangular co-ordinate, and adjusts polygon aspect ratio and is allowed to meet aggregate particle model aspect ratio；Then adjustment polygon width is allowed to meet aggregate particle simulated target width；Polygon major axis is finally adjusted with X-axis angle to realize the randomness of aggregate particle model angle, generates single aggregate particle model.The Inhomogeneous charge material test specimen model generating method of the present invention is based on aggregate particle model generation algorithm, on the premise of it need not carry out image procossing to bitumen mixture specimen, efficiently quick and more accurately Inhomogeneous charge material model of the generation available for FEM calculation.
Description
Technical field
Inhomogeneous charge material test specimen mould the present invention relates to a kind of generating algorithm of aggregate particle model and based on the algorithm
Type generation method, belong to road engineering technical field.
Background technology
Asphalt is using bi tumenf orr oad as cementing material, and filler is used as using a certain proportion of miberal powder, rubble etc.
A kind of composite architectural materials that institute's mix forms.Although asphalt is a kind of composite, the mixing of traditional pitch
Material design method does not take into full account influence of the compound each component property to composite overall performance, but is regarded as
A kind of isotropic isotropic body.But the different degrees of pitch that must influence of the meeting such as the grading of aggregate, geometry, mechanical property mixes
The overall performance of material is closed, and finally influences service life of road surface.Therefore, asphalt is considered as into inhomogeneous composite materials to carry out
Research, can Optimization Design, and then improve Pavement Performance.
In order to solve problem above, countries in the world have proposed many methods.These methods are roughly divided into two kinds of thinkings：One
It is to be based on image processing techniques, such as CT scan technology, bitumen mixture specimen section is scanned, is obtained to section and is gathered materials and drip
Blue or green plane distribution image, and then handle and obtain the Inhomogeneous charge material areal model that can be used for FEM calculation.Such a side
Method operation is complex, and cost is higher and it is necessary to based on existing bitumen mixture specimen, can not provide a numeral completely
The virtual experimental system of change.Another method is to directly generate drip according to material properties such as bitumen aggregate ratio, porosity, gradings of aggregates
Blue or green compound numeral test specimen.But this method algorithm is complicated at present, and the numeral generated is gathered materials model forms feature and reality
Gap is larger, and time cost is higher.
Therefore, on the basis of prior art, the present invention proposes a kind of generating algorithm of aggregate particle model, and is based on being somebody's turn to do
Algorithm proposes a kind of Inhomogeneous charge material test specimen model generating method, need not carry out image procossing to bitumen mixture specimen
On the premise of, efficiently quick and more accurately generation Inhomogeneous charge material model, and then entered using finite element software to it
Row correlation computations.
The content of the invention
Goal of the invention：For problems of the prior art, the present invention provides a kind of generation of aggregate particle model and calculated
Method, and provide a kind of generation method of Inhomogeneous charge material test specimen model based on the algorithm.
Technical scheme：A kind of generating algorithm of aggregate particle model of the present invention, comprises the steps：
(1) side numbers of the random one positive integer N more than 3 of generation as initial polygon, in the range of polar diameter and polar angle
Random generation N represents N number of summit of random polygon to polar coordinates, respectively；
(2) random polygon vertex polar coordinates are converted into rectangular co-ordinate, and adjust polygon aspect ratio and be allowed to meet collection
Expect granular model aspect ratio；
(3) adjustment polygon width is allowed to meet aggregate particle simulated target width；
(4) polygon major axis is adjusted with X-axis angle to realize the randomness of aggregate particle model angle, and generation is single to gather materials
Granular model.
The generating algorithm of above-mentioned aggregate particle model can generate two-dimentional aggregate particle model or three-dimensional aggregate particle model.
Exemplified by generating two-dimentional aggregate particle model, each step in a kind of generating algorithm of aggregate particle model of the invention
It is specific as follows：
In step (1), N is generated at random in the range of polar diameter (L1, L2) scope, polar angle (0,2 π) to polar coordinates, and according to
Polar angle sorts from small to large；A pair of polar coordinates (L2, π) are inserted after polar coordinates of the polar angle less than π and closest to π, and last
A pair of polar coordinates (L2,2 π) are inserted after a pair of polar coordinates.
In step (2), the method for adjustment polygon aspect ratio is：Aggregate particle simulated target aspect ratio is set as ratio_
Target, the current aspect ratio of polygon are ratio_current, and each apex coordinate is (X, Y), and all summits of adjustment polygon are indulged
Coordinate, it is allowed to equal with ratio_target, abscissa X is kept constant during adjustment, and ordinate Y adjusts according to formula (1)：
In step (3), the method in adjustment polygon broadband is：Sets target aggregate particle model width is width_
Target, the current width of polygon is set as width_current, each apex coordinate is (X, Y), is adjusted according to formula (2) and formula (3)
Whole each summit is horizontal, ordinate：
In step (4), the method for adjustment polygon major axis and X-axis angle is：The random generation rotation in the range of (0,2 π)
Angle, it is set as angle, sets each apex coordinate as (X, Y), adjusts (X, Y), realize the rotation of polygon；Each summit is horizontal, indulges and sits
Mark adjusts according to following step：
1. calculating each summit and X-axis angle, it is set as alpha；
2. calculating each summit and the origin of coordinates (0,0) distance, it is set as R；
3. each summit and X-axis angle after rotating are calculated according to formula (4)：
Alpha=alpha+angle (4)
4. each apex coordinate (X, Y) is adjusted according to formula (5) and formula (6)：
X=R × cos (alpha) (5)
Y=R × sin (alpha) (6).
When generating three-dimensional aggregate particle model using a kind of generating algorithm of aggregate particle model of the present invention, its method step
It is identical when suddenly with generating two-dimentional aggregate particle model, it is only necessary to by the two-dimensional parameter increase in above-mentioned specific steps to be three-dimensional, to phase
Coordinate is answered to enter line translation., will if the width of two-dimentional aggregate particle is width_target, length length_target
Two-dimentional aggregate particle model stretches h along normal direction, you can three-dimensional aggregate particle model is generated, wherein, width_target ＜ h
＜ length_target.
A kind of Inhomogeneous charge material test specimen model generation side based on aggregate particle model generation algorithm of the present invention
Method, comprise the following steps：
(1) mixture gradation is determined, and measures each particle diameter density of gathering materials, each particle diameter of coarse aggregate in grading is calculated and gathers materials
Amounts of particles ratio；
(2) using the rectangular coordinate system origin of coordinates as starting point, put with this and calculated for reference point according to the generation of aggregate particle model
Method generates single aggregate particle model；
(3) according to each apex coordinate of aggregate particle model and compound test specimen model scope, it is terminal to determine random site,
The aggregate particle model is translated into so far point, obtains position of the aggregate particle in compound；
(4) judge various point locations on the aggregate particle model whether therewith previous existence into all aggregate particle models it is mutually overlapping
It is folded, terminal is redefined if overlapping；
(5) after all aggregate particle model generations, cementing material is generated in test specimen internal voids, is molded heterogeneous mixed
Close material test specimen model.
For two-dimentional aggregate particle model, in above-mentioned steps (3), the determination method of its random site is：Set compound
Border is respectively top, bottom, left, right to test specimen model up and down, each apex coordinate of aggregate particle model for (X,
Y), random site point coordinates is (x, y), traversal each apex coordinate of aggregate particle model (X, Y), determines abscissa smallest point and most
A little louder, it is demarcated as (x_min, y) and (x_max, y) respectively, determines ordinate smallest point and maximum point, be demarcated as (x, y_ respectively
Min) and (x, y_max), random site point abscissa scope is determined according to formula (7) and formula (8)：
The upper limit：X_right=right- | x_max | (7)
Lower limit：X_left=left+ | x_min | (8)；
Random site point ordinate scope is determined according to formula (9) and formula (10)：
The upper limit：Y_top=top- | y_max | (9)
Lower limit：Y_bottom=bottom+ | y_min | (10)
During for three-dimensional aggregate particle model, in step (3), the determination method of its random site is：
If compound test specimen model up, down, left, right, before and after border be respectively top, bottom, left, right,
Front, back, each apex coordinate of aggregate particle model are (X, Y, Z), and random site point of the aggregate particle in test specimen profile is sat
It is designated as (x, y, z), traversal each apex coordinate of aggregate particle model (X, Y, Z), determines abscissa smallest point and maximum point, mark respectively
Be set to (x_min, y, z) and (x_max, y, z), determine ordinate smallest point and maximum point, be demarcated as respectively (x, y_min, z) and
(x, y_max, z), ordinate smallest point and maximum point are determined, be demarcated as (x, y, z_min) and (x, y, z_max) respectively, according to
Formula (11) and formula (12) determine random site point abscissa x spans：
The upper limit：X_right=right- | x_max | (11)
Lower limit：X_left=left+ | x_min | (12)；
Random site point ordinate y spans are determined according to formula (13) and formula (14)：
The upper limit：Y_top=top- | y_max | (13)
Lower limit：Y_bottom=bottom+ | y_min | (14)；
Random site point ordinate z spans are determined according to formula (15) and formula (16)：
The upper limit：Z_front=front- | z_max | (15)
Lower limit：Z_back=back+ | z_min | (16).
Accordingly, for three-dimensional aggregate particle model, in step (4), judged by the three-view diagram of three-dimensional aggregate particle
N-th aggregate particle model with whether existing N-1 aggregate particle model overlapping in compound test specimen model, specifically sentence
Disconnected method is：The three-view diagram and M (1≤M of n-th aggregate particle are judged successively<N-1) whether the three-view diagram of individual aggregate particle is sent out
Life is overlapping, if at least one three-view diagram does not overlap, n-th aggregate particle is not sent out with m-th aggregate particle
Life is overlapping, can carry out the judgement of n-th aggregate particle and the M+1 aggregate particle position relationship；If n-th aggregate particle
Three-view diagram and three-view diagram at least one three-view diagram of existing N-1 aggregate particle do not overlap, then N
N-1 aggregate particle of individual aggregate particle and other does not overlap.
Beneficial effect：Compared with prior art, the advantage of the invention is that：(1) using the aggregate particle model of the present invention
Generating algorithm generate single aggregate particle model when, its formation speed is fast, can effectively save time cost；(2) it is of the invention
The generation method of Inhomogeneous charge material test specimen model is based on aggregate particle model generation algorithm, and actual pitch need not mixed
On the premise of expecting that test specimen carries out image procossing, according to gather materials grading, the association attributes such as sample dimensions, can rapidly and accurately generate
Available for the Inhomogeneous charge material test specimen model of FEM calculation, the speed and precision of raising compound simulation calculation.
Brief description of the drawings
Fig. 1 is the schematic diagram of the Inhomogeneous charge material test specimen model generated in embodiment.
Embodiment
Technical scheme is described further with reference to specific embodiments and the drawings.
A kind of generating algorithm of aggregate particle model of the present invention, comprises the steps：
(1) side numbers of the random one positive integer N more than 3 of generation as initial polygon, in the range of polar diameter and polar angle
Random generation N represents N number of summit of random polygon to polar coordinates, respectively；
Exemplified by generating two-dimentional aggregate particle model, generated at random in the range of polar diameter (L1, L2) scope, polar angle (0,2 π)
N sorts from small to large to polar coordinates, and according to polar angle；A pair of polar coordinates are inserted after polar coordinates of the polar angle less than π and closest to π
(L2, π), and a pair of polar coordinates (L2,2 π) are inserted after last is to polar coordinates.
(2) random polygon vertex polar coordinates are converted into rectangular co-ordinate, and adjust polygon aspect ratio and be allowed to meet collection
Expect granular model aspect ratio；
Specifically, the method for adjustment polygon aspect ratio is：Aggregate particle simulated target aspect ratio is set as ratio_
Target, the current aspect ratio of polygon are ratio_current, and each apex coordinate is (X, Y), and all summits of adjustment polygon are indulged
Coordinate, it is allowed to equal with ratio_target, abscissa X is kept constant during adjustment, and ordinate Y adjusts according to formula (1)：
(3) adjustment polygon width is allowed to meet aggregate particle simulated target width；
In this step, the method in adjustment polygon broadband is：Sets target aggregate particle model width is width_
Target, the current width of polygon is set as width_current, each apex coordinate is (X, Y), is adjusted according to formula (2) and formula (3)
Whole each summit is horizontal, ordinate：
(4) polygon major axis is adjusted with X-axis angle to realize the randomness of aggregate particle model angle, and generation is single to gather materials
Granular model.
Specifically, the method for adjustment polygon major axis and X-axis angle is：Generate the anglec of rotation at random in the range of (0,2 π),
It is set as angle, sets each apex coordinate as (X, Y), adjusts (X, Y), realize the rotation of polygon；Each summit is horizontal, ordinate
Adjusted according to following step：
1. calculating each summit and X-axis angle, it is set as alpha；
2. calculating each summit and the origin of coordinates (0,0) distance, it is set as R；
3. each summit and X-axis angle after rotating are calculated according to formula (4)：
Alpha=alpha+angle (4)
4. each apex coordinate (X, Y) is adjusted according to formula (5) and formula (6)：
X=R × cos (alpha) (5)
Y=R × sin (alpha) (6).
A kind of generating algorithm of aggregate particle model of the present invention cannot be only used for generating two-dimentional aggregate particle model, also may be used
Generate three-dimensional aggregate particle model.Three-dimensional aggregate particle mould is generated using a kind of generating algorithm of aggregate particle model of the present invention
It is identical when its method and step is with generating two-dimentional aggregate particle model during type, it is only necessary to increase the two-dimensional parameter in above-mentioned specific steps
Three-dimensional is added as, line translation is entered to corresponding coordinate.If the width of two-dimentional aggregate particle is width_target, length is
Length_target, two-dimentional aggregate particle model is stretched into h along normal direction, you can three-dimensional aggregate particle model is generated, its
In, width_target ＜ h ＜ length_target.
A kind of Inhomogeneous charge material test specimen model generating method based on aggregate particle model generation algorithm of the present invention, including
Following steps：
(1) mixture gradation is determined, and measures each particle diameter density of gathering materials, each particle diameter of coarse aggregate in grading is calculated and gathers materials
Amounts of particles ratio；
(2) using the rectangular coordinate system origin of coordinates as starting point, the aggregate particle model for reference point according to the present invention is put with this
Generating algorithm generate single aggregate particle model；Two-dimentional or three-dimensional aggregate particle model can be generated herein according to actual conditions；
(3) according to each apex coordinate of aggregate particle model and compound test specimen model scope, it is terminal to determine random site,
The aggregate particle model is translated into so far point, obtains position of the aggregate particle in compound；
For two-dimentional aggregate particle model, the determination method of its random site is：Set bottom left on compound test specimen model
Right margin is respectively top, bottom, left, right, and each apex coordinate of aggregate particle model is (X, Y), and random site point is sat
It is designated as (x, y), traversal each apex coordinate of aggregate particle model (X, Y), determines abscissa smallest point and maximum point, be demarcated as respectively
(x_min, y) and (x_max, y), determines ordinate smallest point and maximum point, is demarcated as (x, y_min) and (x, y_max) respectively,
Random site point abscissa scope is determined according to formula (7) and formula (8)：
The upper limit：X_right=right- | x_max | (7)
Lower limit：X_left=left+ | x_min | (8)；
Random site point ordinate scope is determined according to formula (9) and formula (10)：
The upper limit：Y_top=top- | y_max | (9)
Lower limit：Y_bottom=bottom+ | y_min | (10).
During for three-dimensional aggregate particle model, the determination method of its random site is：
If compound test specimen model up, down, left, right, before and after border be respectively top, bottom, left, right,
Front, back, each apex coordinate of aggregate particle model are (X, Y, Z), and random site point of the aggregate particle in test specimen profile is sat
It is designated as (x, y, z), traversal each apex coordinate of aggregate particle model (X, Y, Z), determines abscissa smallest point and maximum point, mark respectively
Be set to (x_min, y, z) and (x_max, y, z), determine ordinate smallest point and maximum point, be demarcated as respectively (x, y_min, z) and
(x, y_max, z), ordinate smallest point and maximum point are determined, be demarcated as (x, y, z_min) and (x, y, z_max) respectively, according to
Formula (11) and formula (12) determine random site point abscissa x spans：
The upper limit：X_right=right- | x_max | (11)
Lower limit：X_left=left+ | x_min | (12)；
Random site point ordinate y spans are determined according to formula (13) and formula (14)：
The upper limit：Y_top=top- | y_max | (13)
Lower limit：Y_bottom=bottom+ | y_min | (14)；
Random site point ordinate z spans are determined according to formula (15) and formula (16)：
The upper limit：Z_front=front- | z_max | (15)
Lower limit：Z_back=back+ | z_min | (16).
(4) judge various point locations on the aggregate particle model whether therewith previous existence into all aggregate particle models it is mutually overlapping
It is folded, terminal is redefined if overlapping；
For two-dimentional aggregate particle model, when generating n-th two dimension aggregate particle, it should be judged whether with the 1st, 2,
3 ... ... N-1 aggregate particles are overlapping.If overlapping, the aggregate particle random site point (x, y) is redefined.
For three-dimensional aggregate particle model, n-th aggregate particle model is judged by the three-view diagram of three-dimensional aggregate particle
With whether existing N-1 aggregate particle model overlapping in compound test specimen model.Specifically determination methods are：Judge successively
The three-view diagram and M (1≤M of n-th aggregate particle<N-1) whether the three-view diagram of individual aggregate particle overlaps, if at least
One three-view diagram does not overlap, then n-th aggregate particle does not overlap with m-th aggregate particle, can carry out N
The judgement of individual aggregate particle and the M+1 aggregate particle position relationship；If the three-view diagram of n-th aggregate particle is with having existed
Three-view diagram at least one three-view diagram of N-1 aggregate particle do not overlap, then n-th aggregate particle and other N-
1 aggregate particle does not overlap.
(5) after all aggregate particle model generations, cementing material is generated in test specimen internal voids, is molded heterogeneous mixed
Close material test specimen model.
Embodiment
Exemplified by generating bitumen mixture specimen model as shown in Figure 1, sample dimensions 500mm*500mm；Its outermost
Enclose for test specimen profile 3, the aggregate particle 1 of sizes is filled with test specimen model, space 2 is left between aggregate particle 1.
Set residue after m (19mm) sieves as 19mm sieve apertures to gather materials amounts of particles, residue is gathered materials after the screening of remaining sieve aperture
Grain number amount is by that analogy.Each particles quantitative proportion that gathers materials after screening is：
m(19mm):m(12.5mm):m(9.5mm):m(4.75mm):M (2.36mm)=13:12.2:14.7:20.4:
15.3。
First two-dimentional aggregate particle model is generated using the generating algorithm of the aggregate particle model of the present invention first.
(1) side numbers of the random one positive integer N more than 3 of generation as initial polygon.In polar diameter (1,2) scope, pole
Generation N sorts from small to large to polar coordinates, and according to polar angle at random in the range of angle (0,2 π)；It is less than π and closest to π's in polar angle
A pair of polar coordinates (2, π) are inserted after polar coordinates, and a pair of polar coordinates (2,2 π) are inserted after last is to polar coordinates.
(2) the random polygon vertex polar coordinates of gained are converted into rectangular co-ordinate, now original polar origin is changed into
Rectangular co-ordinate origin, the major axis end points of polygon is (- 2,0), (2,0), and adjustment polygon aspect ratio is allowed to meet aggregate particle
Model aspect ratio.
(3) after aspect ratio adjustment, then adjust polygon width and be allowed to meet aggregate particle simulated target width.
(4) polygon major axis is adjusted with X-axis angle to realize the randomness of aggregate particle model angle.
4 steps more than, it is possible to achieve the generation of first aggregate particle model.
Then, determine a position as first aggregate particle in compound at random in compound test specimen space
Position.Now, test specimen model is limited to 500 in the Y direction, lower limit 0, is limited to 500 in the X direction, lower limit 0.Random site
Point (x, y) abscissa scope should meet following formula：
The upper limit：X_right=500- | x_max |
Lower limit：X_left=0+ | x_min |
Random site point (x, y) ordinate scope should meet following formula：
The upper limit：Y_top=500- | y_max |
Lower limit：Y_bottom=0+ | y_min |
First each apex coordinate of aggregate particle is translated into (x, y) respectively, you can obtain first aggregate particle and mixing
Position in material.
Hereafter, the individual two-dimentional aggregate particles of the P that sequentially generates the 2nd, 3,4 after the same method ....As generation Q (Q<P)
Whether during individual two-dimentional aggregate particle, it should being judged with the 1st, 2,3 ... ..., Q-1 aggregate particle is overlapping.If overlapping, again
Determine the aggregate particle random site point (x, y).Aggregate particle model sum when generation and aggregate particle model needed for calculating
When sum is identical, stops generation and gather materials granular model.
The filled bitumen mortar in aggregate particle model space, generate Inhomogeneous charge material model, such as Fig. 1.
Claims (10)
1. a kind of generating algorithm of aggregate particle model, it is characterised in that single using the method generation for generating random polygon
Aggregate particle model, it specifically includes following step：
(1) side numbers of the random one positive integer N more than 3 of generation as initial polygon, it is random in the range of polar diameter and polar angle
Generation N represents N number of summit of random polygon to polar coordinates, respectively；
(2) random polygon vertex polar coordinates are converted into rectangular co-ordinate, and adjust polygon aspect ratio and be allowed to satisfaction and gather materials
Grain model aspect ratio；
(3) adjustment polygon width is allowed to meet aggregate particle simulated target width；
(4) polygon major axis is adjusted with X-axis angle to realize the randomness of aggregate particle model angle, generates single aggregate particle
Model.
2. the generating algorithm of aggregate particle model according to claim 1, it is characterised in that the aggregate particle model is
Two-dimentional aggregate particle model；In step (1), generation N is sat to pole at random in the range of polar diameter (L1, L2) scope, polar angle (0,2 π)
Mark, and sorted from small to large according to polar angle；A pair of polar coordinates (L2, π) are inserted after polar coordinates of the polar angle less than π and closest to π,
And a pair of polar coordinates (L2,2 π) are inserted after last is to polar coordinates.
3. the generating algorithm of aggregate particle model according to claim 2, it is characterised in that in step (2), the adjustment
The method of polygon aspect ratio is：Aggregate particle simulated target aspect ratio is set as ratio_target, polygon is at present in length and breadth
Than being (X, Y) for ratio_current, each apex coordinate, all summit ordinates of polygon are adjusted, are allowed to and ratio_
Target is equal, and abscissa X is kept constant during adjustment, and ordinate Y adjusts according to formula (1)：
<mrow>
<mi>Y</mi>
<mo>=</mo>
<mi>Y</mi>
<mo>&times;</mo>
<mfrac>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>t</mi>
<mi>i</mi>
<mi>o</mi>
<mo>_</mo>
<mi>t</mi>
<mi>arg</mi>
<mi>e</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>r</mi>
<mi>a</mi>
<mi>t</mi>
<mi>i</mi>
<mi>o</mi>
<mo>_</mo>
<mi>c</mi>
<mi>u</mi>
<mi>r</mi>
<mi>r</mi>
<mi>e</mi>
<mi>n</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
<mo>.</mo>
</mrow>
4. the generating algorithm of aggregate particle model according to claim 2, it is characterised in that in step (3), the adjustment
The method in polygon broadband is：Sets target aggregate particle model width is width_target, sets the current width of polygon
For width_current, each apex coordinate is (X, Y), and each summit horizontal stroke, ordinate are adjusted according to formula (2) and formula (3)：
<mrow>
<mi>X</mi>
<mo>=</mo>
<mi>X</mi>
<mo>&times;</mo>
<mfrac>
<mrow>
<mi>w</mi>
<mi>i</mi>
<mi>d</mi>
<mi>t</mi>
<mi>h</mi>
<mo>_</mo>
<mi>t</mi>
<mi>arg</mi>
<mi>e</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>w</mi>
<mi>i</mi>
<mi>d</mi>
<mi>t</mi>
<mi>h</mi>
<mo>_</mo>
<mi>c</mi>
<mi>u</mi>
<mi>r</mi>
<mi>r</mi>
<mi>e</mi>
<mi>n</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>2</mn>
<mo>)</mo>
</mrow>
</mrow>
<mrow>
<mi>Y</mi>
<mo>=</mo>
<mi>Y</mi>
<mo>&times;</mo>
<mfrac>
<mrow>
<mi>w</mi>
<mi>i</mi>
<mi>d</mi>
<mi>t</mi>
<mi>h</mi>
<mo>_</mo>
<mi>t</mi>
<mi>arg</mi>
<mi>e</mi>
<mi>t</mi>
</mrow>
<mrow>
<mi>w</mi>
<mi>i</mi>
<mi>d</mi>
<mi>t</mi>
<mi>h</mi>
<mo>_</mo>
<mi>c</mi>
<mi>u</mi>
<mi>r</mi>
<mi>r</mi>
<mi>e</mi>
<mi>n</mi>
<mi>t</mi>
</mrow>
</mfrac>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
<mo>.</mo>
</mrow>
5. the generating algorithm of aggregate particle model according to claim 2, it is characterised in that set the width of two-dimentional aggregate particle
Spend for width_target, length length_target, two-dimentional aggregate particle model is stretched into h along normal direction, you can raw
Into three-dimensional aggregate particle model, wherein, width_target ＜ h ＜ length_target.
6. the generating algorithm of aggregate particle model according to claim 2, it is characterised in that in step (4), the adjustment
The method of polygon major axis and X-axis angle is：Generate the anglec of rotation at random in the range of (0,2 π), be set as angle, set each top
Point coordinates is (X, Y), adjusts (X, Y), realizes the rotation of polygon；Each summit is horizontal, ordinate adjusts according to following step：
1. calculating each summit and X-axis angle, it is set as alpha；
2. calculating each summit and the origin of coordinates (0,0) distance, it is set as R；
3. each summit and X-axis angle after rotating are calculated according to formula (4)：
Alpha=alpha+angle (4)
4. each apex coordinate (X, Y) is adjusted according to formula (5) and formula (6)：
X=R × cos (alpha) (5)
Y=R × sin (alpha) (6).
A kind of 7. generation method of the Inhomogeneous charge material test specimen model based on algorithm described in claim 1, it is characterised in that bag
Include following steps：
(1) mixture gradation is determined, and measures each particle diameter density of gathering materials, calculates each particle diameter of coarse aggregate and aggregate particle in grading
Quantitative proportion；
(2) using the rectangular coordinate system origin of coordinates as starting point, put with this and calculated for reference point according to the generation of the aggregate particle model
Method generates single aggregate particle model；
(3) according to each apex coordinate of aggregate particle model and compound test specimen model scope, it is terminal to determine random site, by this
Aggregate particle model translates so far point, obtains position of the aggregate particle in compound；
(4) judge various point locations on the aggregate particle model whether therewith previous existence into all aggregate particle models overlap, if
It is overlapping, redefine terminal；
(5) after all aggregate particle model generations, cementing material is generated in test specimen internal voids, is molded Inhomogeneous charge material
Test specimen model.
8. the Inhomogeneous charge material test specimen model generation of the generating algorithm according to claim 7 based on aggregate particle model
Method, it is characterised in that for two-dimentional aggregate particle model, in step (3), the determination method of the random site is：
Setting compound test specimen model, border is respectively top, bottom, left, right up and down, and aggregate particle model is each
Apex coordinate is (X, Y), and random site point coordinates is (x, y), traversal each apex coordinate of aggregate particle model (X, Y), it is determined that horizontal
Coordinate smallest point and maximum point, it is demarcated as (x_min, y) and (x_max, y) respectively, determines ordinate smallest point and maximum point, point
It is not demarcated as (x, y_min) and (x, y_max), random site point abscissa scope is determined according to formula (7) and formula (8)：
The upper limit：X_right=right- | x_max | (7)
Lower limit：X_left=left+ | x_min | (8)；
Random site point ordinate scope is determined according to formula (9) and formula (10)：
The upper limit：Y_top=top- | y_max | (9)
Lower limit：Y_bottom=bottom+ | y_min | (10).
9. the Inhomogeneous charge material test specimen model generation of the generating algorithm according to claim 7 based on aggregate particle model
Method, it is characterised in that for three-dimensional aggregate particle model, in step (3), the determination method of the random site is：
If compound test specimen model up, down, left, right, before and after border is respectively top, bottom, left, right, front,
Back, each apex coordinate of aggregate particle model are (X, Y, Z), and random site point coordinates of the aggregate particle in test specimen profile is
(x, y, z), traversal each apex coordinate of aggregate particle model (X, Y, Z), determines abscissa smallest point and maximum point, is demarcated as respectively
(x_min, y, z) and (x_max, y, z), determines ordinate smallest point and maximum point, be demarcated as respectively (x, y_min, z) and (x,
Y_max, z), ordinate smallest point and maximum point are determined, is demarcated as (x, y, z_min) and (x, y, z_max) respectively, according to formula
(11) and formula (12) determines random site point abscissa x spans：
The upper limit：X_right=right- | x_max | (11)
Lower limit：X_left=left+ | x_min | (12)；
Random site point ordinate y spans are determined according to formula (13) and formula (14)：
The upper limit：Y_top=top- | y_max | (13)
Lower limit：Y_bottom=bottom+ | y_min | (14)；
Random site point ordinate z spans are determined according to formula (15) and formula (16)：
The upper limit：Z_front=front- | z_max | (15)
Lower limit：Z_back=back+ | z_min | (16).
10. the Inhomogeneous charge material test specimen model life of the generating algorithm according to claim 9 based on aggregate particle model
Into method, it is characterised in that in step (4), by the three-view diagram of three-dimensional aggregate particle come judge n-th aggregate particle model with
Whether existing N-1 aggregate particle model is overlapping in compound test specimen model, and specific determination methods are：Is judged successively
The three-view diagram and M (1≤M of N number of aggregate particle<N-1) whether the three-view diagram of individual aggregate particle overlaps, if at least one
Individual three-view diagram does not overlap, then n-th aggregate particle does not overlap with m-th aggregate particle, can carry out n-th
The judgement of aggregate particle and the M+1 aggregate particle position relationship；If the three-view diagram of n-th aggregate particle with it is existing
The three-view diagram of N-1 aggregate particle at least one three-view diagram does not overlap, then n-th aggregate particle and other N-1
Individual aggregate particle does not overlap.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710446911.0A CN107368624B (en) | 2017-06-14 | 2017-06-14 | Aggregate particle model generation algorithm and heterogeneous mixture test piece model generation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710446911.0A CN107368624B (en) | 2017-06-14 | 2017-06-14 | Aggregate particle model generation algorithm and heterogeneous mixture test piece model generation method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107368624A true CN107368624A (en) | 2017-11-21 |
| CN107368624B CN107368624B (en) | 2021-03-26 |
Family
ID=60304950
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710446911.0A Active CN107368624B (en) | 2017-06-14 | 2017-06-14 | Aggregate particle model generation algorithm and heterogeneous mixture test piece model generation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107368624B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109211945A (en) * | 2018-08-22 | 2019-01-15 | 东南大学 | A method of based on DEM analysis asphalt mixture gap structure |
| CN109991401A (en) * | 2019-04-19 | 2019-07-09 | 长沙理工大学 | A kind of consideration is gathered materials the three-dimensional random number test specimen generation method of feature |
| CN110083936A (en) * | 2019-04-26 | 2019-08-02 | 中煤科工集团重庆研究院有限公司 | Consider form parameter is crushed gravel particle generation method |
| CN111080790A (en) * | 2019-11-28 | 2020-04-28 | 河海大学 | Concave body generation method and device based on convex hull algorithm |
| CN112415628A (en) * | 2019-08-20 | 2021-02-26 | 核工业二一六大队 | Sandstone-type uranium ore sampling plane distribution diagram mapping method |
| CN114925590A (en) * | 2022-06-24 | 2022-08-19 | 中南大学 | Aggregate generation algorithm and construction method of reclaimed water stable aggregate discrete element numerical model |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4617084B2 (en) * | 2004-01-16 | 2011-01-19 | 佐藤道路株式会社 | Construction method of porous concrete pavement |
| US20140101557A1 (en) * | 2009-12-18 | 2014-04-10 | Morningside Analytics, Llc | Valence graph tool for custom network maps |
| JP2015098527A (en) * | 2013-11-19 | 2015-05-28 | 三菱レイヨン株式会社 | Packing material composition, and method for repairing cement asphalt mortar layer of slab track by using the composition |
| CN104827575A (en) * | 2015-05-12 | 2015-08-12 | 广西大学 | Bidirectional migration method for two-dimensional random feeding of concrete aggregates |
-
2017
- 2017-06-14 CN CN201710446911.0A patent/CN107368624B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4617084B2 (en) * | 2004-01-16 | 2011-01-19 | 佐藤道路株式会社 | Construction method of porous concrete pavement |
| US20140101557A1 (en) * | 2009-12-18 | 2014-04-10 | Morningside Analytics, Llc | Valence graph tool for custom network maps |
| JP2015098527A (en) * | 2013-11-19 | 2015-05-28 | 三菱レイヨン株式会社 | Packing material composition, and method for repairing cement asphalt mortar layer of slab track by using the composition |
| CN104827575A (en) * | 2015-05-12 | 2015-08-12 | 广西大学 | Bidirectional migration method for two-dimensional random feeding of concrete aggregates |
Non-Patent Citations (6)
| Title |
|---|
| X SHU 等: "Laboratory evaluation of fatigue characteristics of recycled asphalt mixture", 《CONSTRUCTION AND BUILDING MATERIALS》 * |
| 刘小明 等: "《公路工程试验与检测》", 31 August 2015, 中南大学出版社 * |
| 可小军 等: "《电脑室内装修设计实例与技巧》", 31 January 2006, 国防工业出版社 * |
| 姜绍飞 等: "混凝土细观层次损伤数值模拟-随机骨料结构的生成", 《沈阳建筑大学学报(自然科学版)》 * |
| 徐向红 等: "《机械零件的识图与测绘》", 31 August 2012, 复旦大学出版社 * |
| 王江洋 等: "沥青混合料非均质多层次结构数字试件的二维随机生成算法", 《公路》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109211945A (en) * | 2018-08-22 | 2019-01-15 | 东南大学 | A method of based on DEM analysis asphalt mixture gap structure |
| CN109211945B (en) * | 2018-08-22 | 2021-03-19 | 东南大学 | Method for analyzing void structure of asphalt mixture based on discrete elements |
| CN109991401A (en) * | 2019-04-19 | 2019-07-09 | 长沙理工大学 | A kind of consideration is gathered materials the three-dimensional random number test specimen generation method of feature |
| CN110083936A (en) * | 2019-04-26 | 2019-08-02 | 中煤科工集团重庆研究院有限公司 | Consider form parameter is crushed gravel particle generation method |
| CN110083936B (en) * | 2019-04-26 | 2023-06-16 | 中煤科工集团重庆研究院有限公司 | Method for generating crushable crushed stone particles by considering shape parameters |
| CN112415628A (en) * | 2019-08-20 | 2021-02-26 | 核工业二一六大队 | Sandstone-type uranium ore sampling plane distribution diagram mapping method |
| CN112415628B (en) * | 2019-08-20 | 2022-07-26 | 核工业二一六大队 | Sandstone-type uranium ore sampling plane distribution diagram forming method |
| CN111080790A (en) * | 2019-11-28 | 2020-04-28 | 河海大学 | Concave body generation method and device based on convex hull algorithm |
| CN111080790B (en) * | 2019-11-28 | 2022-04-05 | 河海大学 | Concave body generation method and device based on convex hull algorithm |
| CN114925590A (en) * | 2022-06-24 | 2022-08-19 | 中南大学 | Aggregate generation algorithm and construction method of reclaimed water stable aggregate discrete element numerical model |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107368624B (en) | 2021-03-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107368624A (en) | Aggregate particle model generation algorithm and Inhomogeneous charge material test specimen model generating method | |
| CN103218480B (en) | Method for randomly building bituminous mixture multilayered structure simulation model | |
| CN105714637B (en) | A kind of Optimising aggregate gradation method based on void in mineral aggregate | |
| Li et al. | Computed tomography based numerical simulation for triaxial test of soil–rock mixture | |
| US20140257742A1 (en) | Method to structure mineral aggregate gradation by using three control points and two curves | |
| Zhang et al. | Effects of coarse aggregate content on the paste rheological thresholds of fresh self-compacting concrete | |
| CN104700097B (en) | A kind of mineral constituent recognition methods based on mineral standard entropy color database | |
| CN107644121A (en) | The reverse three-dimensionalreconstruction and body modeling method of a kind of ground surface material skeleton structure | |
| CN101051395A (en) | Three dimension visual method based on geological body of geophysical field data | |
| WO2014067677A1 (en) | Apparatus, method and computer program for spatially representing a digital map section | |
| Yang et al. | Aggregate representation for mesostructure of stone based materials using a sphere growth model based on realistic aggregate shapes | |
| CN104809756B (en) | Asphalt mixture gap spatial construction method based on X-ray CT images | |
| Cannone Falchetto et al. | Microstructural characterization of asphalt mixtures containing recycled asphalt materials | |
| CN106970207B (en) | A method of the Chloride Ion in Concrete diffusion analysis based on meso-mechanical model | |
| CN101510273A (en) | Method for rapidly counting city planning earth area and computer program | |
| WO2022166232A1 (en) | Rock identification method, system and apparatus, terminal, and readable storage medium | |
| Engin et al. | Size distribution analysis of aggregates using LiDAR scan data and an alternate algorithm | |
| CN108181211A (en) | A kind of evaluation method of the compound geometrical property of mineral aggregate coarse aggregate | |
| CN113129283A (en) | Digital image-based filler grading intelligent detection compaction control method | |
| Ragia et al. | 3D reconstruction and visualization of alternatives for restoration of historic buildings: A new approach | |
| CN107830800B (en) | A method of fine elevation is generated based on vehicle-mounted scanning system | |
| Aschenbrener et al. | Factors that Affect the Voids in the Mineral Aggregate in Hot Mix Asphalt | |
| CN110399643A (en) | Ice water cumulose soil roadbed filling modification method overly moist | |
| CN102034228B (en) | Ancient book image inpainting method and device | |
| CN104652230B (en) | A kind of for cold regeneration mix hit real before and after the method for adjustment of grating |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |