CN114254537A - Multi-scale component model finite element grid generation method and device and storage medium - Google Patents
Multi-scale component model finite element grid generation method and device and storage medium Download PDFInfo
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Abstract
A multi-scale component model finite element mesh generation method, a device and a storage medium are provided, the method comprises the following steps: acquiring a multi-scale component model data file; establishing a circular traversal list for the multi-scale component model data file; circularly traversing the circular traversal list; acquiring circular traversal data; setting characteristic grid parameters according to the circulation traversal data; and carrying out meshing on the multi-scale component model according to the characteristic mesh parameters. According to the method, the automatic generation of the grids in the geometric regions with different magnitudes can be rapidly carried out on the complex multi-scale component model, and the grids among different scales are connected in a uniform transition mode according to the geometric index control function; the method is suitable for a complex model with different scales, the grids between different scales are in uniform transition, the grids between scales cannot be suddenly changed, and the grid quality is good.
Description
Technical Field
The invention belongs to the technical field of finite element mesh generation, and particularly relates to a method and a device for generating a multi-scale component model finite element mesh and a storage medium.
Background
When a complex multi-scale component model carries out CAE (Computer Aided Engineering) finite element pretreatment grid division in the professional fields of aviation, aerospace, vehicles, ships, machinery and the like, if the small grid size is required to be adopted in order to adapt to the characteristic requirement of the small-scale direction size, the quantity of the integrally generated grids is huge, and the subsequent calculation efficiency is influenced; if the feature requirement of the dimension in the large-scale direction is adapted, the large grid dimension needs to be adopted completely, which causes the generation of long and narrow units in the small-scale direction and can not meet the subsequent calculation precision requirement. Therefore, a high-quality and high-precision grid is important for the calculation result.
At present, for a model with complex multi-scale dimensions, a common finite element preprocessing mesh is divided into: the full-model meshing is carried out through the existing commercial software or open source software, and finally the complicated small-scale area is encrypted, but the process is various in operation and easy to make mistakes, the experience requirements on meshing workers are high, and the time and labor cost is high.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus and a storage medium for generating a multi-scale component model finite element mesh, which overcome or at least partially solve the above problems.
In order to solve the technical problem, the invention provides a method for generating a finite element mesh of a multi-scale component model, which comprises the following steps:
acquiring a multi-scale component model data file;
establishing a circular traversal list for the multi-scale component model data file;
circularly traversing the circular traversal list;
acquiring circular traversal data;
setting characteristic grid parameters according to the circulation traversal data;
and carrying out meshing on the multi-scale component model according to the characteristic mesh parameters.
Preferably, the acquiring the multi-scale component model data file comprises the steps of:
acquiring a point data file of the multi-scale component model;
using a point representation formula to represent the point data file;
acquiring an edge data file of the multi-scale component model;
using an edge representation formula to represent the edge data file;
acquiring a surface data file of the multi-scale component model;
and characterizing the face data file by using a face characterization formula.
Preferably, the step of establishing a circular traverse list for the multi-scale component model data file comprises the steps of:
carrying out normalization preprocessing on the multi-scale component model data file;
establishing a circular traversal list for the multi-scale component model data file along a preset sequence;
setting a first data point of the circular traverse list as a starting point;
setting a point to the left of the starting point as a starting reference point;
acquiring all detection points of the circular traversal list;
setting the left points of all the detection points as detection reference points;
and performing geometric feature marking on the starting point, the starting reference point, the detection point and the detection reference point.
Preferably, said cyclically traversing said cyclically traversed list comprises the steps of:
acquiring a starting point, a starting reference point, a detection point and a detection reference point of the circular traversal list;
scanning eight neighborhood data points of the starting point in a counterclockwise direction from the starting reference point;
starting to scan eight neighborhood data points corresponding to the detection points in a counterclockwise direction for each detection reference point;
and acquiring scanning sequences of all the detection points.
Preferably, the acquiring loop traversal data comprises the steps of:
acquiring a starting point geometric feature corresponding to a starting point in the circular traversal list;
acquiring geometric characteristics of detection points corresponding to the detection points in the circular traversal list;
calculating the geometric feature correlation degree of all the detection point geometric features and the starting point geometric features;
setting all the geometric features of the detection points with the geometric feature correlation degree meeting a preset value as feature vectors;
and assembling the feature vectors and obtaining a feature space matrix.
Preferably, the setting of the feature mesh parameters according to the loop traversal data comprises the steps of:
acquiring a first eigenvector of the characteristic space matrix;
assigning quantitative attributes to the first feature vector;
setting regional characteristic grid parameters according to the quantitative attributes;
setting parameters of a curved surface curvature characteristic grid according to the quantitative attributes;
setting small-geometric-size characteristic grid parameters according to the quantitative attributes;
and setting the characteristic grid parameters of the chamfer and fillet according to the quantitative attributes.
Preferably, the gridding the multi-scale component model according to the characteristic grid parameters comprises the following steps:
acquiring regional characteristic grid parameters, curved surface curvature characteristic grid parameters, small geometric dimension characteristic grid parameters and chamfer angle fillet characteristic grid parameters;
carrying out meshing on the multi-scale component model according to each characteristic mesh parameter to obtain a finite element mesh model;
and performing transition connection on the finite element mesh model by using a geometric exponential growth mode.
The application also provides a multi-scale component model finite element mesh generation device, the device includes:
the multi-scale component model data file acquisition module is used for acquiring a multi-scale component model data file;
the cyclic traversal list establishing module is used for establishing a cyclic traversal list for the multi-scale component model data file;
the circulating traversing list circulating module is used for circularly traversing the circulating traversing list;
the cyclic traversal data acquisition module is used for acquiring cyclic traversal data;
the characteristic grid parameter setting module is used for setting characteristic grid parameters according to the circulation traversal data;
and the meshing module is used for meshing the multi-scale component model according to the characteristic meshing parameters.
The present application also provides an electronic device, characterized in that the electronic device includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any of the aforementioned multi-scale component model finite element mesh generation methods.
The present application further provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform any one of the methods for multi-scale component model finite element mesh generation described above.
One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages: according to the multi-scale component model finite element grid generation method, the device and the storage medium, grids in different magnitude geometrical regions can be rapidly and automatically generated for a complex multi-scale component model, and the grids in different scales are connected in sequence and uniformly in a transition mode according to a geometrical index control function, so that compared with a traditional self-adaptive grid drawing method, the number of integral model grids can be reduced, the design period is greatly shortened, and the product design efficiency is improved; the method is suitable for a complex model with different scales, the grids between different scales are in uniform transition, the grids between scales cannot be suddenly changed, and the grid quality is good.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for generating a finite element mesh of a multi-scale component model according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a finite element mesh generation apparatus for a multi-scale component model according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of an electronic device according to the present invention;
FIG. 4 is a schematic structural diagram of a non-transitory computer-readable storage medium provided by the present invention;
fig. 5 is a plan view of a smartphone chip die model in a method for generating a finite element mesh of a multi-scale component model according to an embodiment of the present invention;
fig. 6 is mark points of different areas of a smart phone chip die model in a finite element mesh generation method of a multi-scale component model according to an embodiment of the present invention;
fig. 7 is a mesh division diagram of a smart phone chip die-casting model generated by a multi-scale component model finite element mesh generation method according to an embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to specific embodiments and examples, and the advantages and various effects of the present invention will be more clearly apparent therefrom. It will be understood by those skilled in the art that these specific embodiments and examples are for the purpose of illustrating the invention and are not to be construed as limiting the invention.
Throughout the specification, unless otherwise specifically noted, terms used herein should be understood as having meanings as commonly used in the art. Accordingly, unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. If there is a conflict, the present specification will control.
Unless otherwise specifically stated, various raw materials, reagents, instruments, equipment and the like used in the present invention are commercially available or can be prepared by existing methods.
In an embodiment of the present application, as shown in fig. 1, the present invention provides a method for generating a finite element mesh of a multi-scale component model, the method comprising the steps of:
s1: acquiring a multi-scale component model data file;
in an embodiment of the present application, the acquiring a multi-scale component model data file includes:
acquiring a point data file of the multi-scale component model;
using a point representation formula to represent the point data file;
acquiring an edge data file of the multi-scale component model;
using an edge representation formula to represent the edge data file;
acquiring a surface data file of the multi-scale component model;
and characterizing the face data file by using a face characterization formula.
In the embodiment of the present application, when a data file of a multi-scale component model is obtained, a point data file, an edge data file, and a surface data file of the multi-scale component model are obtained respectively, and are sequentially characterized by a point characterization formula, an edge characterization formula, and a surface characterization formula, where the obtained point characterization formula is:
node _ n (n ═ 1, 2, 3 …), the resulting edge characterization formula is: edge _ i (i ═ 1, 2, 3 …), the resulting table characterization equation is: face _ j (j ═ 1, 2, 3 …).
S2: establishing a circular traversal list for the multi-scale component model data file;
in an embodiment of the present application, the building a circular traversal list for the multi-scale component model data file includes:
carrying out normalization preprocessing on the multi-scale component model data file;
establishing a circular traversal list for the multi-scale component model data file along a preset sequence;
setting a first data point of the circular traverse list as a starting point;
setting a point to the left of the starting point as a starting reference point;
acquiring all detection points of the circular traversal list;
setting the left points of all the detection points as detection reference points;
and performing geometric feature marking on the starting point, the starting reference point, the detection point and the detection reference point.
In the embodiment of the application, when a circular traversal list is established for the multi-scale component model data file, firstly, normalization preprocessing is performed on the multi-scale component model data file, then, the multi-scale component model data file is traversed from left to right and from top to bottom to establish the circular traversal list, a first data point of the circular traversal list is found as a starting point and is marked as a0The point left of this point is taken as the starting reference point and is denoted as b0And simultaneously, circularly traversing all the detection points in the list and the corresponding left points thereof to be marked as detection reference points, and marking corresponding geometric characteristic marks.
S3: circularly traversing the circular traversal list;
in an embodiment of the present application, said circularly traversing list comprises the steps of:
acquiring a starting point, a starting reference point, a detection point and a detection reference point of the circular traversal list;
scanning eight neighborhood data points of the starting point in a counterclockwise direction from the starting reference point;
starting to scan eight neighborhood data points corresponding to the detection points in a counterclockwise direction for each detection reference point;
and acquiring scanning sequences of all the detection points.
In the embodiment of the present application, when the loop traversal list is traversed in a loop, all the detection points in the loop traversal list need to be scanned in a loop traversal manner, and the scanning is performed from the starting point. Specifically, eight neighborhood data points of the starting point are scanned in a counterclockwise direction from the starting reference point, then eight neighborhood data points of the corresponding detection point are scanned in a counterclockwise direction from each detection reference point, that is, any detection point is scanned by 8 adjacent points with the same dimension as the detection point and 9 × 2 points with upper and lower adjacent dimensions, that is, 26 points in total, and the scanning sequence obtained by scanning is sequentially marked as x ═ x [ x ] x [ -x ] m1 x2 … xn]TWherein, the element xiTo describe the children (descriptors), n represents the number of descriptors.
S4: acquiring circular traversal data;
in an embodiment of the present application, the acquiring loop traversal data includes:
acquiring a starting point geometric feature corresponding to a starting point in the circular traversal list;
acquiring geometric characteristics of detection points corresponding to the detection points in the circular traversal list;
calculating the geometric feature correlation degree of all the detection point geometric features and the starting point geometric features;
setting all the geometric features of the detection points with the geometric feature correlation degree meeting a preset value as feature vectors;
and assembling the feature vectors and obtaining a feature space matrix.
In the embodiment of the application, when the circular traversal list is circularly traversed, when the circular traversal stops, the geometric feature correlation degrees of all the geometric features of the detection points and the geometric features of the starting point are calculated, the geometric features of the detection points with the geometric feature correlation degrees meeting a preset value (for example, the geometric feature correlation degrees are within a preset range) are set as feature vectors, and the feature vectors are assembled to obtain the feature space matrix.
In the embodiment of the present application, the sweep obtained in step S3 is usedDrawing sequence x ═ x1 x2 … xn]TAccordingly, it can be obtained that the mean vector of the feature vectors is: m isxE { x }, the covariance matrix is: cx＝E{(x-mx)(x-mx)T}. Since x is an n-dimensional column vector, CxIs an n x n matrix. CiiRepresents the variance, C, of the i-th component of the vector xijRepresenting x in a vector xiAnd xjCovariance of (2), if xiAnd xjCorrelation, then CijNot equal to 0, otherwise, C ij0. When the first in the sequence of the tag is a0The point of correlation is nkThe space where all feature vectors can be obtained is an n-dimensional feature space (feature space), and the expression is:
s5: setting characteristic grid parameters according to the circulation traversal data;
in an embodiment of the present application, the setting of the feature mesh parameters according to the loop traversal data includes:
acquiring a first eigenvector of the characteristic space matrix;
assigning quantitative attributes to the first feature vector;
setting regional characteristic grid parameters according to the quantitative attributes;
setting parameters of a curved surface curvature characteristic grid according to the quantitative attributes;
setting small-geometric-size characteristic grid parameters according to the quantitative attributes;
and setting the characteristic grid parameters of the chamfer and fillet according to the quantitative attributes.
In the embodiment of the application, when the feature mesh parameters are set according to the circular traversal data, a first feature vector of a feature space matrix is obtained first, a quantitative attribute is given to the first feature vector, and then the region feature mesh parameters, the surface curvature feature mesh parameters, the small-geometry feature mesh parameters and the chamfer fillet feature mesh parameters are set according to the quantitative attribute.
In the embodiment of the present application, the first eigenvector of the feature space obtained in step S4 is assigned with a quantitative attribute, and is denoted as c ═ c0And setting grid parameters according to the quantitative attributes of the feature vectors. Specifically, for the region features with different scales, the grid parameter of the region features is hc＝[L/n](ii) a For the curved surface curvature characteristic, the grid parameter of the curved surface curvature characteristic is hc2Rsin (Φ/2); for small geometry features, the small geometry feature grid parameter is hc＝LABFor the chamfer fillet characteristic, the chamfer fillet characteristic grid parameter is hc＝RA。
S6: and carrying out meshing on the multi-scale component model according to the characteristic mesh parameters.
In an embodiment of the present application, the gridding the multi-scale component model according to the characteristic grid parameters includes:
acquiring regional characteristic grid parameters, curved surface curvature characteristic grid parameters, small geometric dimension characteristic grid parameters and chamfer angle fillet characteristic grid parameters;
carrying out meshing on the multi-scale component model according to each characteristic mesh parameter to obtain a finite element mesh model;
and performing transition connection on the finite element mesh model by using a geometric exponential growth mode.
In the embodiment of the present application, when the multi-scale component model is subjected to mesh partition according to the characteristic mesh parameters, the multi-scale component model is subjected to mesh partition according to each characteristic mesh parameter in step S5 to obtain a finite element mesh model, and then the finite element mesh model is subjected to transition connection by using a geometric index growth mode.
In the embodiment of the present application, specifically, the geometric exponential growth mode used is: deltan＝δ0(1+r)n-1Wherein, delta0、δnRespectively representing the height of the grid of the first layer and the height of the grid of the nth layer, and r is the change rate of the normal grid distance.
The present application is described in detail below with specific examples.
Fig. 5 is a plan view of a typical smart phone chip molding die model, which is a complex multi-scale assembly, and the model can be divided into an upper part, a middle part and a lower part, which are respectively marked as block _ n (n is 0, 1, 2), the uppermost bulk is a copper heat sink, the size of the heat sink is larger than that of the chip, and the four corners of the heat sink are loaded with the same load; the lower layer is a chip; the middle thin layer is a softened layer material (the dimensions are purposely enlarged for easy viewing in plan view) connecting the upper heat spreader and the bottom chip, and the thickness dimension of the softened layer is much smaller than the heat spreader dimension and the chip dimension.
In the embodiment of the application, the multi-scale component model data file corresponding to the smart phone chip die model is as follows: node ═ 0.0, 0.0; 2.0, 0.0; 2.0, 1.0; 0.0, 1.0; 0.05, 0.0; 1.95, 0; 1.95, -0.02; 0.05, -0.02; -0.2, -0.02; 2.2, -0.02; 2.2, -0.52; -0.2, -0.52 ];
edge＝[1，2；2，3；3，4；4，1；5，6；6，7；7，8；5，8；9，10；10，11；11，12；12，9]；
face{1}＝[1，2，3，4]；
face{2}＝[5，6，7，8]；
face{3}＝[9，10，11，12]；
in the embodiment of the present application, by performing the method provided by the present application on the smartphone chip stamper model in fig. 5, the marking points of different areas of the smartphone chip stamper model shown in fig. 6 and the grid division diagram of the smartphone chip stamper model shown in fig. 7 can be obtained.
In an embodiment of the present application, as shown in fig. 2, the present application further provides a multi-scale component model finite element mesh generation apparatus, including:
a multi-scale component model data file obtaining module 10, configured to obtain a multi-scale component model data file;
a circular traverse list establishing module 20, configured to establish a circular traverse list for the multi-scale component model data file;
a circular traverse list circulating module 30 for circularly traversing the circular traverse list;
a loop traversal data obtaining module 40, configured to obtain loop traversal data;
a feature mesh parameter setting module 50, configured to set a feature mesh parameter according to the loop traversal data;
and a meshing module 60, configured to perform meshing on the multi-scale component model according to the characteristic mesh parameters.
The multi-scale component model finite element mesh generation device provided by the application can execute the multi-scale component model finite element mesh generation method provided by the steps.
Referring now to FIG. 3, a block diagram of an electronic device 100 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 3, the electronic device 100 may include a processing means (e.g., a central processing unit, a graphic processor, etc.) 101 that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)102 or a program loaded from a storage means 108 into a Random Access Memory (RAM) 103. In the RAM 103, various programs and data necessary for the operation of the electronic apparatus 100 are also stored. The processing device 101, the ROM102, and the RAM 103 are connected to each other via a bus 104. An input/output (I/0) interface 105 is also connected to bus 104.
Generally, the following devices may be connected to the I/0 interface 105: input devices 106 including, for example, a touch screen, touch pad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; an output device 107 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage devices 108 including, for example, magnetic tape, hard disk, etc.; and a communication device 109. The communication means 109 may allow the electronic device 100 to communicate wirelessly or by wire with other devices to exchange data. While the figures illustrate an electronic device 100 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication means 109, or installed from the storage means 108, or installed from the ROM 102. The computer program, when executed by the processing device 101, performs the above-described functions defined in the methods of the embodiments of the present disclosure.
Referring now to FIG. 4, there is shown a schematic structural diagram of a computer-readable storage medium suitable for use in implementing embodiments of the present disclosure, the computer-readable storage medium storing a computer program which, when executed by a processor, is capable of implementing a method for multi-scale component model finite element mesh generation as described in any one of the above.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring at least two internet protocol addresses; sending a node evaluation request comprising the at least two internet protocol addresses to node evaluation equipment, wherein the node evaluation equipment selects the internet protocol addresses from the at least two internet protocol addresses and returns the internet protocol addresses; receiving an internet protocol address returned by the node evaluation equipment; wherein the obtained internet protocol address indicates an edge node in the content distribution network.
Alternatively, the computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: receiving a node evaluation request comprising at least two internet protocol addresses; selecting an internet protocol address from the at least two internet protocol addresses; returning the selected internet protocol address; wherein the received internet protocol address indicates an edge node in the content distribution network.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".
According to the multi-scale component model finite element grid generation method, the device and the storage medium, grids in different magnitude geometrical regions can be rapidly and automatically generated for a complex multi-scale component model, and the grids in different scales are connected in sequence and uniformly in a transition mode according to a geometrical index control function, so that compared with a traditional self-adaptive grid drawing method, the number of integral model grids can be reduced, the design period is greatly shortened, and the product design efficiency is improved; the method is suitable for a complex model with different scales, the grids between different scales are in uniform transition, the grids between scales cannot be suddenly changed, and the grid quality is good.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (10)
1. A method for generating a finite element mesh of a multi-scale component model, the method comprising the steps of:
acquiring a multi-scale component model data file;
establishing a circular traversal list for the multi-scale component model data file;
circularly traversing the circular traversal list;
acquiring circular traversal data;
setting characteristic grid parameters according to the circulation traversal data;
and carrying out meshing on the multi-scale component model according to the characteristic mesh parameters.
2. The method of generating a finite element mesh of a multi-scale component model according to claim 1, wherein the obtaining of the multi-scale component model data file comprises the steps of:
acquiring a point data file of the multi-scale component model;
using a point representation formula to represent the point data file;
acquiring an edge data file of the multi-scale component model;
using an edge representation formula to represent the edge data file;
acquiring a surface data file of the multi-scale component model;
and characterizing the face data file by using a face characterization formula.
3. The method for generating finite element meshes of a multi-scale component model according to claim 1, wherein the step of building a circular traverse list for the multi-scale component model data file comprises the steps of:
carrying out normalization preprocessing on the multi-scale component model data file;
establishing a circular traversal list for the multi-scale component model data file along a preset sequence;
setting a first data point of the circular traverse list as a starting point;
setting a point to the left of the starting point as a starting reference point;
acquiring all detection points of the circular traversal list;
setting the left points of all the detection points as detection reference points;
and performing geometric feature marking on the starting point, the starting reference point, the detection point and the detection reference point.
4. The method of generating a finite element mesh of a multi-scale component model according to claim 1, wherein the loop traversing the loop traversal list comprises the steps of:
acquiring a starting point, a starting reference point, a detection point and a detection reference point of the circular traversal list;
scanning eight neighborhood data points of the starting point in a counterclockwise direction from the starting reference point;
starting to scan eight neighborhood data points corresponding to the detection points in a counterclockwise direction for each detection reference point;
and acquiring scanning sequences of all the detection points.
5. The method of generating a finite element mesh of a multi-scale component model according to claim 1, wherein the acquiring of the cyclic traversal data comprises the steps of:
acquiring a starting point geometric feature corresponding to a starting point in the circular traversal list;
acquiring geometric characteristics of detection points corresponding to the detection points in the circular traversal list;
calculating the geometric feature correlation degree of all the detection point geometric features and the starting point geometric features;
setting all the geometric features of the detection points with the geometric feature correlation degree meeting a preset value as feature vectors;
and assembling the feature vectors and obtaining a feature space matrix.
6. The method of generating a finite element mesh of a multi-scale component model according to claim 1, wherein the setting of the characteristic mesh parameters according to the loop traversal data comprises the steps of:
acquiring a first eigenvector of the characteristic space matrix;
assigning quantitative attributes to the first feature vector;
setting regional characteristic grid parameters according to the quantitative attributes;
setting parameters of a curved surface curvature characteristic grid according to the quantitative attributes;
setting small-geometric-size characteristic grid parameters according to the quantitative attributes;
and setting the characteristic grid parameters of the chamfer and fillet according to the quantitative attributes.
7. A method of generating a multi-scale component model finite element mesh according to claim 1, wherein the meshing the multi-scale component model according to the characteristic mesh parameters comprises the steps of:
acquiring regional characteristic grid parameters, curved surface curvature characteristic grid parameters, small geometric dimension characteristic grid parameters and chamfer angle fillet characteristic grid parameters;
carrying out meshing on the multi-scale component model according to each characteristic mesh parameter to obtain a finite element mesh model;
and performing transition connection on the finite element mesh model by using a geometric exponential growth mode.
8. An apparatus for generating a finite element mesh for a multi-scale component model, the apparatus comprising:
the multi-scale component model data file acquisition module is used for acquiring a multi-scale component model data file;
the cyclic traversal list establishing module is used for establishing a cyclic traversal list for the multi-scale component model data file;
the circulating traversing list circulating module is used for circularly traversing the circulating traversing list;
the cyclic traversal data acquisition module is used for acquiring cyclic traversal data;
the characteristic grid parameter setting module is used for setting characteristic grid parameters according to the circulation traversal data;
and the meshing module is used for meshing the multi-scale component model according to the characteristic meshing parameters.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of generating a multi-scale component model finite element mesh as claimed in any of claims 1-7.
10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of generating a multi-scale component model finite element mesh of any of the preceding claims 1-7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116244865A (en) * | 2023-05-11 | 2023-06-09 | 陕西空天信息技术有限公司 | Method and device for finite element modeling of axial flow impeller and computer storage medium |
| CN117709129A (en) * | 2024-02-05 | 2024-03-15 | 国家超级计算天津中心 | Multi-scale simulation method, device, equipment and storage medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116244865A (en) * | 2023-05-11 | 2023-06-09 | 陕西空天信息技术有限公司 | Method and device for finite element modeling of axial flow impeller and computer storage medium |
| CN116244865B (en) * | 2023-05-11 | 2023-08-15 | 陕西空天信息技术有限公司 | Method and device for finite element modeling of axial flow impeller and computer storage medium |
| CN117709129A (en) * | 2024-02-05 | 2024-03-15 | 国家超级计算天津中心 | Multi-scale simulation method, device, equipment and storage medium |
| CN117709129B (en) * | 2024-02-05 | 2024-05-14 | 国家超级计算天津中心 | Multi-scale simulation method, device, equipment and storage medium |
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