CN110334414B - Method and device for calculating degradation strength of polymer based on strength phase diagram - Google Patents
Method and device for calculating degradation strength of polymer based on strength phase diagram Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a device for calculating the degradation strength of a polymer based on a strength phase diagram, wherein the method comprises the following steps of 1, reading the strength phase diagram of the polymer to be calculated; step 2, traversing from the origin of coordinates of the intensity phase diagram, and judging the intensity state of the cells on each pixel point; step 3, according to a neighbor-boundary expansion algorithm, identifying holes and cracks in a region formed by pixel points in the same strength state in the phase diagram, and acquiring the region areas and the density degrees of the holes and the cracks in the regions in different strength states; step 4, calculating the intensities of the cells in different intensity states according to the area and the density of holes and cracks in the areas in different intensity states and a pre-established intensity calculation model; and 5, calculating the total strength of the polymer according to the strengths of the cells in different strength states.
Description
Technical Field
The invention relates to the field of degradable high polymer materials, in particular to a method and a device for calculating the degradation strength of a polymer based on a strength phase diagram.
Background
Nowadays, with the continuous development and maturation of medical science, degradable high polymer materials are developed. The novel medical product made of PLA and the copolymer thereof is gushed out, particularly shows excellent performance on a tissue scaffold, is accepted by social researchers and doctors as the tissue scaffold, and the support strength during degradation is matched with the growth speed of human tissues, so that the research on the change of the material degradation strength is the most active topic in the current research. Research on the degradation process of materials is gradually and deeply conducted, and not all at once. Zygourakis proposes to establish a mathematical model to simulate the release of drugs attached to a degradable material by utilizing the randomness of Monte Carlo, and to simulate Mongolian drugs for the first timeThe tecarol process is used in the random degradation of high polymers. Thombre and Himinelstein firstly propose the influence of reaction environment on degradation, if the reaction environment is acidic, ester bonds are hydrolyzed by acid, the concentration of hydrogen ions is increased, so that the polarity of a degradation system is increased, the autocatalysis capacity of a degradable material is stronger, and the degradation is accelerated.
The influence of diffusion of short molecular chains on degradation was mainly analyzed by et al. Professor Pan proposed a model for the change in elastic modulus for hydrolysis and short chain diffusion of semi-crystalline degradable materials, considering that the strength of the crystal is greater than that of the semi-crystalline and the void strength is zero. But this equation does not take into account crystallization. The Shirazi professor couples the molecular weight model and the elastic modulus model based on the calculation formula of the elastic modulus proposed by Flory, which is one of the most accurate models in the research on the strength change of the high polymer so far. Zhang et al found that the size of inclusions affects the strength required for interfacial separation, and that the strength is related to the size of interfacial impurities. Tanaka et al doped spherical impurities of varying sizes into the material, and found that the larger the size of the impurity, the less stress is required to break the interface. Under the continuous exploration and research of many researchers, the influence of crystallization, voids, molecular weight and composition size on strength has not yet been found, so that the analysis and calculation of strength are very difficult and challenging.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for calculating polymer degradation strength based on an intensity phase diagram, which can calculate the polymer degradation strength according to a fitting method.
A method for calculating the degradation strength of a polymer based on a strength phase diagram comprises the following steps:
step 1, reading a strength phase diagram of a polymer to be calculated;
step 3, according to a neighbor-boundary expansion algorithm, identifying holes and cracks in a region formed by pixel points in the same strength state in the phase diagram, and acquiring the region areas and the density degrees of the holes and the cracks in the regions in different strength states;
and 5, calculating the total strength of the polymer according to the strengths of the cells in different strength states.
A device for calculating polymer degradation strength based on an intensity phase diagram, comprising:
a reading unit which reads the strength phase diagram of the polymer to be calculated;
the judging unit is used for traversing from the origin of coordinates of the intensity phase diagram and judging the intensity state of the cells on each pixel point;
the acquisition unit is used for identifying holes and cracks in the area formed by the pixels with the same strength state in the phase diagram according to a neighbor-boundary expansion algorithm, and acquiring the area and the density of the holes and the cracks in the areas with different strength states;
the first calculation unit is used for calculating the intensities of the cells in different intensity states according to the area and the density of holes and cracks in the regions in different intensity states and a pre-established intensity calculation model;
a second calculation unit that calculates the total strength of the polymer based on the strengths of the unit cells in the different strength states.
According to the invention, the polymer degradation strength can be calculated according to a fitting method, and the calculation method is simpler.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a method for calculating the degradation strength of a polymer based on a strength-phase diagram according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a method for calculating the degradation strength of a polymer based on a strength-phase diagram according to another embodiment of the present invention;
FIG. 3 is a schematic diagram of a neighbor-boundary extension algorithm according to another embodiment of the present invention;
FIG. 4 is a definition of a fracture in the present invention;
FIG. 5 is a definition of neighbor-boundary extension algorithm holes;
FIG. 6 is a definition of a complex shape for a neighbor-boundary extension algorithm;
FIG. 7 is a graph showing the change in degradation strength of a mixed polymer-degradable material of 60% PLLA and 40% PVA, in which the yellow strength state is an amorphous phase, the red strength state is a crystalline phase, and the gray and black strength states are void phases;
FIG. 8 is a comparison of the simulated values of molecular weight, crystallinity, and intensity of 60% PLLA and 40% PVA materials provided in accordance with an embodiment of the present invention with experimental values, green for crystallinity, blue for normalized intensity, and red for normalized molecular weight;
FIG. 9 is a graph showing the degradation intensity change of PLA degradation materials, wherein the yellow intensity state is amorphous phase, the red intensity state is crystalline phase at 0 degree, and the gray and black intensity states are void phase
FIG. 10 is a comparison of the simulated values of molecular weight, crystallinity, and intensity of PLA material provided by the embodiments of the present invention with experimental values, where green is crystallinity, blue is normalized intensity, and red is normalized molecular weight;
FIG. 11 is a connection diagram of a computing device for polymer degradation strength based on an intensity phase diagram according to an embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For convenience of description, the above devices are described separately in terms of functional division into various units/modules. Of course, the functionality of the units/modules may be implemented in one or more software and/or hardware implementations of the invention.
As shown in fig. 1, the method for calculating the degradation strength of a polymer based on an intensity phase diagram according to the present invention comprises:
step 1, reading a strength phase diagram of a polymer to be calculated; the step 1 specifically comprises the following steps:
reading a strength phase diagram of a polymer to be calculated, wherein a pixel point of the strength phase diagram is L; l is greater than a predetermined value. L can be set according to actual conditions.
step 3, according to a neighbor-boundary expansion algorithm, identifying holes and cracks in a region formed by pixel points in the same strength state in the phase diagram, and acquiring the region areas and the density degrees of the holes and the cracks in the regions in different strength states;
the step 3 comprises the following steps:
s301, reading the phase diagrams in sequence according to a time sequence, and identifying holes and cracks;
s302, traversing from the coordinate origin of the cell, and judging that the region formed by the target pixel is a hole when the transverse direction and the longitudinal direction of the region are both more than or equal to N; when the area formed by the target pixels only meets the condition that the longitudinal length is more than or equal to N or only meets the condition that the transverse length is more than or equal to N, judging the area to be a crack;
s303, counting the number and the area of the holes; if the target pixel belongs to the hole, setting an access traversal mark of the target pixel to be 1;
s304, traversing the crack, specifically: firstly, longitudinally traversing the crack, if the access traversal identifier of the pixel point is 0 and belongs to the crack, setting the access identifier of the pixel point to be 1, and adding the crack into a set for storing the crack; after the longitudinal traversing is finished, the fracture is traversed transversely, the method is the same as that of the longitudinal traversing, and then a set of the fracture and the hole is obtained respectively;
s305, circularly traversing according to the crack and hole set which is solved by the phase diagram picture or the state; then, the minimum and maximum coordinate values are calculated according to the current coordinates of the cracks or holes, and the range of the current area is determined;
s306, judging whether the coordinates in the current crack are marked or not; if marked, executing the next step; if not, performing S304;
s307, performing outward rectangular expansion on the range of the current crack, increasing N pixel points for the first time, increasing 2 x N for the second time, repeating the same, traversing the current expansion range, and checking whether the crack or hole set exists in the currently traversed range; if so, adding an adjacent crack or hole set, and adding 1 to the number of the current adjacent cracks; if no other areas except the current crack or hole are adjacent or the total area of the composition area does not account for 1/3 of the expanded area, stopping the expansion, storing the adjacent cracks into a set, and ending the cycle;
s308, traversing each crack or hole in the crack set in sequence until the completion, and acquiring the holes in the regions with different strength states, the region areas of the cracks and the density degree.
the step 4 comprises the following steps:
when the intensity state of the unit cell is a crystalline phase, calculating the intensity of the unit cell specifically comprises:
in the formula, σzIs the strength value of the crystalline phase, αzhIs the number of cracks in the zone, alphazcIs the number of holes in the area, SzhIs the sum of the areas of the cracks in the zone, SzcIs the sum of the areas of the holes in the zone, phi,
Is a predetermined parameter related to the material properties, l × l being the number of cells;
when the intensity state of the unit cell is an amorphous phase, calculating the intensity of the unit cell specifically comprises:
in the formula, σaIs the strength value of the crystalline phase, αahIs the number of cracks in the zone, alphaacIs the number of holes in the area, SahIs the sum of the areas of the cracks in the zone, SacIs the area sum of the holes in the area, gamma and eta are preset parameters related to material properties, and l x l is the number of cells;
when the intensity state of the unit cell is a null phase, calculating the intensity of the unit cell specifically comprises:
in the formula, σeAs a value of the intensity of the null phase, αehIs the number of cracks in the zone, alphaecIs the number of holes in the area, SehIs the sum of the areas of the cracks in the zone, SecIs the sum of the areas of the pores in the region, μ, v are predetermined parameters related to the material properties, l × l is the number of cells.
The method for establishing the model in advance comprises the following steps:
step 21, reading a strength phase diagram of a polymer for modeling;
step 22, traversing from the origin of coordinates of the intensity phase diagram for modeling, and judging the intensity state of the cells on each pixel point;
step 23, according to a neighbor-boundary expansion algorithm, identifying holes and cracks in a region formed by pixels in the same strength state in the phase diagram for modeling, and acquiring the region areas and the density degrees of the holes and the cracks in the regions in different strength states;
step 24, calculating the intensities of the cells in different intensity states according to the intensity states of the cells and the initial value of the model;
step 25, calculating the total intensity for modeling of the polymer according to the intensities of the unit cells in the different intensity states;
and 26, comparing the total strength for modeling with the experimental value of the total strength of the polymer for modeling, and continuously adjusting the parameters of the model to obtain an optimal model as the built model.
And 5, calculating the total strength of the polymer according to the strengths of the cells in different strength states.
The step 5 comprises the following steps:
in the formula (I), the compound is shown in the specification,
as total intensity, XA(t)、XZ(t)、XE(t) the proportion of the unit cells in the three states of amorphous, crystalline and empty phase to the total number of the unit cells; sigmazValue of crystalline phase intensity, σaValue of crystalline phase intensity, σeAnd the values are void phase intensity values.
The invention provides a polymer degradation strength modeling and calculating method based on phase diagram image processing, a biomedical degradable high polymer material is widely applied in medicine due to good mechanical property and degradation performance, and the matching of strength change and degradation rate in the degradation process is a key consideration factor in the design of a high polymer device. The strength model of the polymer degradation process can be established to quantitatively research the strength evolution in the degradation process. The structural change in the polymer erosion degradation process is used as an entry point, the structural change reflects the evolution of the strength phase, the concept of a strength phase diagram is provided, the characteristic identification is carried out on the strength phase diagram by an image processing method, the characteristic identification with the shape of a hole and a crack is provided by a neighbor-boundary expansion algorithm (NNBE), and the strength model of different phases is established by the characteristic. And model calculation is compared with experimental data, the fitting effect of the model simulation value and the experimental value is good, and the feasibility of the intensity model and the phase diagram feature extraction algorithm is demonstrated.
A polymer degradation strength modeling and calculating method based on phase diagram image processing,
the high polymer is represented by discretized unit cells;
initially, a polymer chain exists in each cell;
the material is degraded, and the polymer chain is broken;
the broken polymer chains may recrystallize, and the short chains may diffuse;
the average molecular weight, the number of polymer chains, the crystallinity and the like of the cells can change the strength state, so that the obtained phase diagrams are different;
the intensity states at different times, the phase diagrams depicted are different;
reading a phase diagram, wherein different pixel points represent different phase diagram states;
under the same intensity state, identifying holes and cracks in an area formed by the pixel points;
calculating the area of the holes and the cracks;
judging the density of the holes and cracks;
calculating the strength according to the area and the density of the holes and the cracks;
the high polymer degradation strength analysis and calculation model based on the phase diagram image processing is used for predicting the strength value of the cellular at the time t and is regarded as the strength value of the whole material at the time t.
In the invention, different phase diagrams are obtained from the definition of the intensity angle, and the phase diagrams are used as the input of a hole and crack identification algorithm and traverse from the origin of the coordinate of the cell. When the regional holes formed by the target pixels are defined, marking the regional holes as holes; when the definition of the crack is met, marking the crack; stored into a collection of holes and cracks, respectively.
In the invention, pixels are traversed, the areas (the number of pixels is adopted) of holes and cracks are recorded, the larger the area is, the more dense the holes and cracks are, the larger the influence on the strength is, and the density degree of the holes and cracks is further determined.
The larger the total area of the seams in the region is, the greater the influence on the strength is; the larger the total area of the holes occupies the total area of the region, the greater the influence on the strength is.
In the present invention, a phase diagram is drawn based on the number average molecular weight of the cells, the number of polymer chains, and the strength state of the cells at time t. Reading the phase diagram, adopting different intensity calculation formulas in different intensity states, and finally adding the intensity values in all the states, namely the total intensity of the material at the time t.
In the present invention, the formula for calculating the diffusion of short chains (the number of units on the polymer chain is less than 8) is:
wherein, CeIs the ester bond concentration; colLow short chain concentration; r is1Under normal conditions; a hydrolysis rate constant; r is2Is a hydrolysis rate constant under an acidic condition; d is a diffusion coefficient; grad is the gradient; div is the divergence.
In the invention, according to the cell strength state at the time t, the strength formula in the state is adopted to calculate the strength of each state, and the method comprises the following steps:
first, crystalline phase Strength model
Based on the phase diagram, according to the shape of the crystalline phase, the proposed hole and crack recognition algorithm is adopted, and the intensity value of the crystalline phase is calculated according to the influence of the area and the density of the crystalline phase on the intensity, as follows:
σz＝σzh+σzc
in the formula, σzValue of crystalline phase intensity, σzhEffect of cracks on strength, σzcIs the effect of the pores on the strength.
Second, amorphous phase intensity model
The calculation formula of the strength change in the amorphous state is as follows:
σa＝σah+σac
in the formula, σaValue of crystalline phase intensity, σahEffect of cracks on strength, σacIs the effect of the pores on the strength.
Third, the space phase intensity model
The calculation formula of the intensity change under the empty phase is as follows:
σe＝σeh+σec
in the formula, σeAs intensity value of the null phase, σehEffect of cracks on strength, σecIs the effect of the pores on the strength.
In the present invention, the overall strength of the polymer counted by the strength of each cell as a function of degradation time includes:
accumulating the intensity values under the three states, and calculating the total intensity:
in the formula (I), the compound is shown in the specification,
for the required total strength, XA(t)、XZ(t)、XEAnd (t) is the proportion of the unit cells in three states of amorphous, crystalline and empty phase to the total number of the unit cells.
The accuracy of the number of the calculated results is related to the size of the number L of the partitions, and when the value of L is large, the time required by the computer for simulating the degradation process of the high polymer is long, and resources are occupied; when the value of L is small, the accuracy of a calculation result is low, and the accuracy of the model cannot be reflected.
The influence of crystallization, voids and molecular weight on strength has not yet been found in the prior art, and therefore, analysis and calculation of strength have been very difficult. The invention provides a method for analyzing and calculating the degradation strength of a high polymer based on phase diagram image processing aiming at simulating and predicting the change of the mechanical property of the high polymer in the degradation process based on the phase diagram.
As shown in fig. 2, the present invention provides a method for analyzing and calculating the degradation intensity of a high polymer based on phase diagram image processing, comprising:
1) at different times, the intensity phase diagrams are different, and the intensity states can be obtained by reading the phase diagrams;
2) the intensity states are divided into three categories: crystalline, amorphous, empty;
3) in different states, the calculation formulas of the strength are different;
4) under the condition of determining the strength state, identifying holes and cracks;
5) calculating the areas and the number of the holes and the cracks;
6) when the holes and cracks are dense, the influence on the strength is large, so that the density degree is analyzed;
7) substituting the intensity degree and the area into an intensity calculation formula;
8) the intensity values in the three intensity states are added, i.e. the total intensity.
The above eight points are specifically described below.
Firstly, the phase change in the polymer degradation process is discussed in a mesoscopic scale, the polymer is divided into mesoscopic cells, and each cell contains a macromolecular chain at the beginning of degradation to simulate the chain breakage, which leads to the reduction of molecular weight; the broken oligomer diffuses out of the matrix to form a hole; chain scission also leads to the formation of recrystallization; thus, different structural morphologies occur during degradation. Phases such as amorphous phase, crystalline phase and empty phase can be separated from the viewpoint of structural morphology. It has been found that some amorphous phase cells with sufficiently small molecular weight do not have much effect on the strength of the matrix, and therefore from the strength point of view, these amorphous phases with small molecular weight can be regarded as empty phases, for which we redefine the phases from the strength point of view, respectively: a degradation phase, a crystalline phase and a strength void phase.
1) Degradation phase
The molecular weight is not so small as to be lower than a certain critical value, and the critical value is called as the critical molecular weight of strength failure;
2) crystalline phase
All crystalline (including crystallization prior to degradation and recrystallization from degradation) cells exhibit a crystalline phase.
3) Strength empty phase
The oligomers diffuse out of the porous cells present outside the matrix and the cells whose molecular weight is below the critical molecular weight for strength failure due to degradation, defining the phase composed of these cells as a strength empty phase.
Further, as the polymer is degraded, the three phases are dynamically evolved, and the influence on the strength is dynamically changed along with the degradation process. Therefore, the image processing technology is adopted to carry out quantitative research on the phase diagram by capturing the dynamically changing phase and developing quantitative research from the phase angle so as to reveal the influence of micro-mesostructure change on the strength.
And further adopting an image processing method to read the phase diagram, and judging the intensity state of the cells according to different meanings represented by pixel points with different colors in the phase diagram. The cells with the strength state of crystalline phase or empty phase can be divided into two types of areas of holes and cracks for calculation according to the different shapes of the composition areas, and the density of the areas has great influence on the change of the strength value
Further, the definition of holes, cracks is as follows:
1) definition of cracks
The combination of the stripe-shaped cells adjacent in a single direction (transverse or longitudinal direction) is defined as a crack, as shown in fig. 1(a) and (b).
2) Definition of the holes
The combination of cells adjacent in both directions (transverse and longitudinal) is defined as a hole, as shown in fig. 5. The irregular shapes are equal to the processing of fig. 5(a) as shown in fig. 5(b) and (c).
3) Complex shape
As shown in fig. 6(a), the complex shape can be regarded as an assembly of holes and cracks, and such a diagram is divided into holes (fig. 6(b)) and cracks (fig. 6(c)), and the holes and cracks are treated separately according to their influence mechanisms on strength.
Furthermore, different phase diagrams are obtained from the definition of the intensity angle, and the phase diagrams are used as the input of a hole and crack identification algorithm and traverse from the origin of the coordinates of the cell. When the regional holes formed by the target pixels are defined, marking the regional holes as holes; when the definition of the crack is met, marking the crack; stored into a collection of holes and cracks, respectively. As the pixels are traversed, the area of the holes and cracks (here, the number of pixels is used) is recorded, the larger the area, the denser the holes and cracks, and the greater the impact on intensity.
The mechanical strength of each cell is further calculated, the material has the coexistence of crystalline state, amorphous state and hole state at the same time, and the calculation of the strength values of three different strength states adopts different calculation formulas.
1) Crystalline phase strength model
Based on the phase diagram, according to the shape of the crystalline phase, the proposed hole and crack recognition algorithm is adopted, and the intensity value of the crystalline phase is calculated according to the influence of the area and the density of the crystalline phase on the intensity, as follows:
in the formula, σzIs the strength value of the crystalline phase, αzhIs the number of cracks, alphazcIs the number of holes, SzhIs in the areaSum of areas of cracks, SzcIs the area sum of the holes in the area, phi,
Is a parameter related to the material properties, and l × l is the number of unit cells.
2) Amorphous phase intensity model
The calculation formula of the strength change in the amorphous state is as follows:
in the formula, σaIs the strength value of the crystalline phase, αahIs the number of cracks, alphaacIs the number of holes, SahIs the sum of the areas of the cracks in this region, SacIs the area sum of pores in the area, gamma and eta are parameters related to material property, and l is the number of unit cells.
3) Model of strength of empty phase
The cells with empty phase include two forms, one is cells in a porous state, and the other is cells in a degraded state or a non-degraded state, but the relative molecular mass is less than a specified molecular weight threshold value, and the cells which are considered to lose the supporting effect are called as the cells with empty phase in a strength state. According to the form of the hollow phase, the area and the density of holes and cracks in the phase diagram, establishing strength relation, and proposing a hollow phase strength model as follows:
in the formula, σeAs a value of the intensity of the null phase, αehIs the number of cracks, alphaecIs the number of holes, SehIs the sum of the areas of the cracks in this region, SecIs the sum of the areas of the pores in the region, mu and v are parameters related to the material properties, and l x l is the number of cells.
Further, the three intensity types of amorphous phase, crystalline phase and empty phase are calculated by different intensity calculation formulas, which can be expressed as follows:
the region accumulates the intensity values in the three states, and calculates the total intensity:
in the formula (I), the compound is shown in the specification,
for the required total strength, XA(t)、XZ(t)、XEAnd (t) is the proportion of the unit cells in three states of amorphous, crystalline and empty phase to the total number of the unit cells.
Further, phase diagrams at different times are sequentially read, and the intensity value is calculated.
The technical scheme of the invention has the following beneficial effects:
in the above scheme, in the degradation process of the raw polymer, the high molecular copolymer is dispersed into cells, and the strength state of the cells can be divided into three types: amorphous phase, crystalline phase, empty phase. The phase diagram changes continuously along with the degradation process, and the changed phase diagram needs to be dynamically captured and identified, which is the premise of quantitative research. Taking the strength phase as an example, the phase diagram can be divided into features such as holes and cracks according to the characteristics of the phase diagram and the influence on the strength. Mesoscopic cell points can be regarded as pixel points of the image, so that the phase diagram is analyzed and processed by using the image processing technology for reference. The strength of the cells in different states is calculated by using different phase strength calculation models, the strength of all the cells is counted to obtain the overall elastic strength of the material, the variation trend of the strength of the material in the degradation process is planned to be obtained, and a numerical basis is provided for the optimized design of the precision medical clinical equipment of the high-molecular degradable polymer in the aspect of mechanical properties.
The following describes an application scenario of the present invention.
Aiming at the existing high molecular polymer degradation model, the invention still does not find the influence of crystallization, gaps, molecular weight and component size on strength so far, and provides a high polymer degradation strength analysis and calculation method based on phase diagram image processing.
As shown in fig. 3, the method for analyzing and calculating degradation strength of a high polymer based on phase diagram image processing according to the embodiment of the present invention proposes a nearest neighbor-boundary extension algorithm (NNBE) to identify features having shapes of holes and cracks, including:
s101, sequentially reading the intensity phase diagrams according to a time sequence, and identifying holes and cracks;
s102, traversing from the origin of the cell coordinates, and naming a region composed of target pixels as a hole when the transverse direction and the longitudinal direction of the region are both more than or equal to N; when the longitudinal length of the composition area is more than or equal to N, or the transverse length of the composition area is more than or equal to N, the composition area is named as a crack;
s103, the computer firstly counts the number and the area of the holes, and if the target pixel point belongs to the hole, the access traversal mark of the target pixel point is set to be 1;
and S104, traversing the crack, firstly longitudinally traversing the crack, setting the access mark of the pixel to be 1 if the pixel belongs to the crack, adding the crack into a set for storing the crack, and transversely traversing the crack after the longitudinal traversal is finished, wherein the method is the same as the longitudinal method, and further the set for storing the crack and the hole can be respectively obtained.
And S105, circularly traversing according to the set of cracks and holes which are solved by the pictures or the states. Then, the minimum and maximum coordinate values are calculated according to the current fracture (hole) coordinates, and the range of the current area is determined;
s106, judging whether the coordinates in the current crack are marked or not, if so, not performing the 4 th step, and if not, performing the 4 th step;
and S107, performing outward rectangular expansion on the range of the current crack, increasing N pixel points for the first time, increasing 2 × N for the second time, repeating the process, traversing the current expansion range, and checking whether the crack and hole set exists in the currently traversed range. If the current crack (hole) exists, adding an adjacent crack (hole) set, adding 1 to the number of the current adjacent cracks, if no other areas except the current crack (hole) are adjacent or the total area of the formed areas does not account for 1/3 of the expanded area, stopping expansion, storing the adjacent cracks into the set, and ending the cycle;
s108, sequentially traversing each crack (hole) in the crack set until the completion;
and S109, calculating the intensity according to the density and the area to obtain an intensity value.
In this embodiment, the calculation of the strength of each cell requires the use of a model for calculating the degradation strength of polymers in different phases.
The intensity of the cell (i, j) at time t can be expressed as:
accumulating the intensity values under the three states, and calculating the total intensity:
in the formula (I), the compound is shown in the specification,
for the required total strength, XA(t)、XZ(t)、XEAnd (t) is the proportion of the unit cells in three states of amorphous, crystalline and empty phase to the total number of the unit cells.
In summary, the high polymer material is divided into L × L small grids by using a cellular automaton, each small grid is called a cell, and the neighborhoods adopt four von neumann neighborhoods. The larger the value of L is, the larger the number of the divided grids is represented, and the more accurate the calculation is. However, there is a disadvantage that the more the number of the divided grids is, the larger the calculation amount is, the longer the time is, and the experiment progress may be affected. Therefore, it is crucial to select a suitable L. According to the intensity state classification, the cell (i, j) can be divided into four states at the time t: amorphous state, empty state, crystalline state. At present, the prediction research on strength mostly stays at the level of amorphous high polymers, or only the constitutive relation is considered, and heterogeneous coexisting polymers are not involved. For the cells whose intensity phase state is empty, the influence of the intensity on the overall intensity is considered to be 0 by default. However, in practice, the cells are present in the phase diagram in the form of cracks or holes, whose presence weakens the overall strength, and this aspect requires correction. Therefore, the strength values under four different states and three different states are solved, and the total strength of the material can be obtained by accumulation and summation. Provides a numerical basis for the optimized design of the high-molecular degradable polymer precision medical clinical equipment in the aspect of mechanical property. The invention is suitable for different application fields of degradable polymer equipment.
In order to better understand the method for modeling and simulating the degradation strength of the high polymer provided in this embodiment, the method for modeling and simulating the degradation strength of the high polymer provided in this embodiment is described in detail by taking, as an example, a mixed high polymer degradation material of 60% PLLA and 40% PVA and a PLA material whose initial state is amorphous:
FIG. 4 is a definition of a fracture in the present invention, wherein FIG. 4(a) shows a transverse fracture and FIG. 4(b) shows a longitudinal fracture; FIG. 5 is a definition of neighbor-boundary extension algorithm holes; FIG. 6 is a definition of a complex shape for a neighbor-boundary extension algorithm; FIG. 7 is a graph showing the change in degradation strength of a mixed polymer-degradable material of 60% PLLA and 40% PVA, in which the yellow strength state is an amorphous phase, the red strength state is a crystalline phase, and the gray and black strength states are void phases; FIG. 8 is a comparison of the simulated values of molecular weight, crystallinity, and intensity of 60% PLLA and 40% PVA materials provided in accordance with an embodiment of the present invention with experimental values, green for crystallinity, blue for normalized intensity, and red for normalized molecular weight; FIG. 9 is a graph showing the degradation intensity change of a PLA degradation material, wherein the yellow intensity state is an amorphous phase, the red intensity 0 degree state is a crystalline phase, and the gray and black intensity states are void phases; fig. 10 is a comparison of the simulated values of molecular weight, crystallinity, and intensity of PLA material provided by the embodiments of the present invention with the experimental values, where green is crystallinity, blue is normalized intensity, and red is normalized molecular weight. The following description is made in conjunction with the drawings.
In this example 1, experiments by Tsuji and Muramatsu were performed, and the material used was a mixed polymer degradable material of 60% PLLA and 40% PVA. Setting the initial strength to 56MPa and the initial molecular weight MnO to 9.26X 104g/mol, initially the material is not crystalline. The degradation probability p is set to 0.1, the calculation parameters alpha and beta in the combination of the multi-term intensity model are set to 1.23 and 1.2, phi,
15 and 1.6, lambda,
The intensity state diagram was enlarged by 1.3 times for 23 and 2.6, and a portion of the phase diagram was taken and observed for changes in intensity state over different time periods, as shown in fig. 6. The simulated values of molecular weight, crystallinity and strength were compared with the experimental values, and the fitting effect was better, as shown in fig. 8.
The method comprises the following specific steps:
(1) reading the phase diagrams according to the difference of the phase diagrams at different moments;
(2) identifying holes and cracks, respectively adding the holes and the cracks into the hole and crack set after identification, and determining the area of the holes and the cracks;
(3) carrying out density division so as to determine an influence intensity factor;
(4) substituting the intensity factor and the area into a matched intensity calculation formula according to the intensity state;
(5) taking the ratio of the cells in the strength state to the total number of the cells, namely the ratio, and taking the product of the ratio and the strength value as a final strength value;
(6) adding the intensity values in the third intensity state to obtain a total intensity value of the material;
(7) comparing the simulated intensity value with the experimental intensity value, and continuously adjusting and optimizing parameters; obtaining an optimal model;
in this example 2, an experiment was conducted by professor Duek, using a PLA material in an initial state without crystallization, setting the initial strength to 190.4MPa and the initial molecular weight MnO to 1.61X 105g/mol. DescendThe solution probability p is set to 0.05, and the calculation parameters α and β in the combination of the polynomial intensity models are set to 1.35 and 3.6, φ, phi,
Are 95 and 3, lambda,
The intensity state diagram was enlarged 5 times for 51 and 2.6, and a portion of the phase diagram was extracted and observed for changes in intensity state over different time periods, as shown in fig. 8. The simulated values of molecular weight, crystallinity and strength were compared with the experimental values, and the fitting effect was better, as shown in fig. 10. The procedure is the same as in example 1 and will not be described in detail.
In example 1 and example 2, the comparison result of the calculated value and the experimental data of the sample is shown in fig. 8 and fig. 10, which verifies the correctness of the method for modeling and simulating the degradation strength of the high molecular polymer in this example. In previous researches, it is always assumed that the strength of the material is not affected by the cells in the porous state, the strength is 0, the relationship between the strength value of the crystalline state and the crystallinity and the molecular weight is unknown, and the simulation of the degradation process is based on the formula created by the result, so that the inapplicability exists. By reading different strength state values in the phase diagram, the simulated values of molecular weight, crystallization rate and strength in the degradation process are compared with the experimental values, the fitting effect is good, and the model has good applicability and accuracy.
As shown in fig. 11, the device for calculating the degradation strength of a polymer based on an intensity phase diagram according to the present invention includes:
a reading unit 31 that reads the intensity phase diagram of the polymer to be calculated;
a judging unit 32, which starts traversal from the origin of coordinates of the intensity phase diagram and judges the intensity state of the cell on each pixel point;
the obtaining unit 33 performs hole and crack recognition on the region composed of the pixels in the same strength state in the phase diagram according to a neighbor-boundary expansion algorithm, and obtains the region areas and the density of the holes and cracks in the regions in different strength states;
the first calculating unit 34 is used for calculating the intensities of the cells in different intensity states according to the area and the density of holes and cracks in the regions in different intensity states and a pre-established intensity calculating model;
the second calculating unit 35 calculates the total strength of the polymer based on the strengths of the unit cells in the different strength states.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-0nly Memory (ROM), a Random Access Memory (RAM), or the like.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A method for calculating the degradation strength of a polymer based on a strength phase diagram is characterized by comprising the following steps:
step 1, reading a strength phase diagram of a polymer to be calculated;
step 2, traversing from the origin of coordinates of the intensity phase diagram, and judging the intensity state of the cells on each pixel point;
step 3, according to a neighbor-boundary expansion algorithm, identifying holes and cracks in a region formed by pixel points in the same strength state in the phase diagram, and acquiring the region areas and the density degrees of the holes and the cracks in the regions in different strength states;
step 4, calculating the intensities of the cells in different intensity states according to the area and the density of holes and cracks in the areas in different intensity states and a pre-established intensity calculation model;
and 5, calculating the total strength of the polymer according to the strengths of the cells in different strength states.
2. The method of claim 1, wherein step 3 comprises:
s301, reading the phase diagrams in sequence according to a time sequence, and identifying holes and cracks;
s302, traversing from the coordinate origin of the cell, and judging that the region formed by the target pixel is a hole when the transverse direction and the longitudinal direction of the region are both more than or equal to N; when the area formed by the target pixels only meets the condition that the longitudinal length is more than or equal to N or only meets the condition that the transverse length is more than or equal to N, judging the area to be a crack;
s303, counting the number and the area of the holes; if the target pixel belongs to the hole, setting an access traversal mark of the target pixel to be 1;
s304, traversing the crack, specifically: firstly, longitudinally traversing the crack, if the access traversal identifier of the pixel point is 0 and belongs to the crack, setting the access identifier of the pixel point to be 1, and adding the crack into a set for storing the crack; after the longitudinal traversing is finished, the fracture is traversed transversely, the method is the same as that of the longitudinal traversing, and then a set of the fracture and the hole is obtained respectively;
s305, circularly traversing according to the crack and hole set which is solved by the phase diagram picture or the state; then, the minimum and maximum coordinate values are calculated according to the current coordinates of the cracks or holes, and the range of the current area is determined;
s306, judging whether the coordinates in the current crack are marked or not; if marked, executing the next step; if not, performing S304;
s307, performing outward rectangular expansion on the range of the current crack, increasing N pixel points for the first time, increasing 2 x N for the second time, repeating the same, traversing the current expansion range, and checking whether the crack or hole set exists in the currently traversed range; if so, adding an adjacent crack or hole set, and adding 1 to the number of the current adjacent cracks; if no other areas except the current crack or hole are adjacent or the total area of the composition area does not account for 1/3 of the expanded area, stopping the expansion, storing the adjacent cracks into a set, and ending the cycle;
s308, traversing each crack or hole in the crack set in sequence until the completion, and acquiring the holes in the regions with different strength states, the region areas of the cracks and the density degree.
3. The method of claim 1, wherein the step 4 comprises:
when the intensity state of the unit cell is a crystalline phase, calculating the intensity of the unit cell specifically comprises:
in the formula, σZIs the strength value of the crystalline phase, αzhIs the number of cracks in the zone, alphazcIs the number of holes in the area, SzhIs the sum of the areas of the cracks in the zone, SzcIs the sum of the areas of the holes in the zone, phi,
Is a predetermined parameter related to the material properties, l × l being the number of cells;
when the intensity state of the unit cell is an amorphous phase, calculating the intensity of the unit cell specifically comprises:
in the formula, σaIs the strength value of the crystalline phase, αahIs the number of cracks in the zone, alphaacIs the number of holes in the area, SahIs the sum of the areas of the cracks in the zone, SacIs the areaThe area sum of the inner holes, gamma and eta are preset parameters related to the material property, and l multiplied by l is the number of cells;
when the intensity state of the unit cell is a null phase, calculating the intensity of the unit cell specifically comprises:
in the formula, σeAs a value of the intensity of the null phase, αehIs the number of cracks in the zone, alphaecIs the number of holes in the area, SehIs the sum of the areas of the cracks in the zone, SecIs the sum of the areas of the holes in the area, mu and v are predetermined parameters related to the material properties, and l x l is the number of the unit cells.
4. The method of claim 3, wherein the step 5 comprises:
in the formula (I), the compound is shown in the specification,
as total intensity, XA(t)、XZ(t)、XE(t) the proportion of the unit cells in the three states of amorphous, crystalline and empty phase to the total number of the unit cells; sigmaZValue of crystalline phase intensity, σaValue of crystalline phase intensity, σeAnd the values are void phase intensity values.
5. The method of claim 1, wherein the pre-modeling method comprises:
step 21, reading a strength phase diagram of a polymer for modeling;
step 22, traversing from the origin of coordinates of the intensity phase diagram for modeling, and judging the intensity state of the cells on each pixel point;
step 23, according to a neighbor-boundary expansion algorithm, identifying holes and cracks in a region formed by pixels in the same strength state in the phase diagram for modeling, and acquiring the region areas and the density degrees of the holes and the cracks in the regions in different strength states;
step 24, calculating the intensities of the cells in different intensity states according to the intensity states of the cells and the initial value of the model;
step 25, calculating the total intensity for modeling of the polymer according to the intensities of the unit cells in the different intensity states;
and 26, comparing the total strength for modeling with the experimental value of the total strength of the polymer for modeling, and continuously adjusting the parameters of the model to obtain an optimal model as the built model.
6. The method according to claim 1, wherein step 1 is specifically:
reading a strength phase diagram of a polymer to be calculated, wherein a pixel point of the strength phase diagram is L; l is greater than a predetermined value.
7. An apparatus for calculating polymer degradation strength based on an intensity phase diagram, comprising:
a reading unit which reads the strength phase diagram of the polymer to be calculated;
the judging unit is used for traversing from the origin of coordinates of the intensity phase diagram and judging the intensity state of the cells on each pixel point;
the acquisition unit is used for identifying holes and cracks in the area formed by the pixels with the same strength state in the phase diagram according to a neighbor-boundary expansion algorithm, and acquiring the area and the density of the holes and the cracks in the areas with different strength states;
the first calculation unit is used for calculating the intensities of the cells in different intensity states according to the area and the density of holes and cracks in the regions in different intensity states and a pre-established intensity calculation model;
a second calculation unit that calculates the total strength of the polymer based on the strengths of the unit cells in the different strength states.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6993446B2 (en) * | 2003-03-17 | 2006-01-31 | Schlumberger Technology Corporation | Method and apparatus for predicting the time to failure of electronic devices at high temperatures |
| CN105868563A (en) * | 2016-04-01 | 2016-08-17 | 北京科技大学 | Modeling and simulating method for degradation process of degradable high polymer material |
| CN107908921A (en) * | 2017-11-08 | 2018-04-13 | 北京科技大学 | A kind of method for simulating not homogeneity phase polymer degradation Strength Changes |
| CN108334734A (en) * | 2017-09-04 | 2018-07-27 | 北京科技大学 | A kind of high-molecular copolymer degradation modeling and simulation method |
-
2019
- 2019-06-18 CN CN201910525798.4A patent/CN110334414B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6993446B2 (en) * | 2003-03-17 | 2006-01-31 | Schlumberger Technology Corporation | Method and apparatus for predicting the time to failure of electronic devices at high temperatures |
| CN105868563A (en) * | 2016-04-01 | 2016-08-17 | 北京科技大学 | Modeling and simulating method for degradation process of degradable high polymer material |
| CN108334734A (en) * | 2017-09-04 | 2018-07-27 | 北京科技大学 | A kind of high-molecular copolymer degradation modeling and simulation method |
| CN107908921A (en) * | 2017-11-08 | 2018-04-13 | 北京科技大学 | A kind of method for simulating not homogeneity phase polymer degradation Strength Changes |
Non-Patent Citations (1)
| Title |
|---|
| 《基于多尺度的生物医用高聚物降解强度模型》;张桃红 等;《高分子材料科学与工程》;20180731(第7期);121-125 * |
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